R-universe search: nearest

spatstat

spatstat.geom:Geometrical Functionality of the 'spatstat' Family

Defines spatial data types and supports geometrical operations on them. Data types include point patterns, windows (domains), pixel images, line segment patterns, tessellations and hyperframes. Capabilities include creation and manipulation of data (using command line or graphical interaction), plotting, geometrical operations (rotation, shift, rescale, affine transformation), convex hull, discretisation and pixellation, Dirichlet tessellation, Delaunay triangulation, pairwise distances, nearest-neighbour distances, distance transform, morphological operations (erosion, dilation, closing, opening), quadrat counting, geometrical measurement, geometrical covariance, colour maps, calculus on spatial domains, Gaussian blur, level sets of images, transects of images, intersections between objects, minimum distance matching. (Excludes spatial data on a network, which are supported by the package 'spatstat.linnet'.)

Maintained by Adrian Baddeley. Last updated 2 days ago.

classes-and-objects distance-calculation geometry geometry-processing images mensuration plotting point-patterns spatial-data spatial-data-analysis

42.3 match 7 stars 12.11 score 241 scripts 227 dependents

jlmelville

rnndescent:Nearest Neighbor Descent Method for Approximate Nearest Neighbors

The Nearest Neighbor Descent method for finding approximate nearest neighbors by Dong and co-workers (2010) <doi:10.1145/1963405.1963487>. Based on the 'Python' package 'PyNNDescent' <https://github.com/lmcinnes/pynndescent>.

Maintained by James Melville. Last updated 8 months ago.

approximate-nearest-neighbor-search cpp

49.5 match 11 stars 7.31 score 75 scripts

eddelbuettel

RcppAnnoy:'Rcpp' Bindings for 'Annoy', a Library for Approximate Nearest Neighbors

'Annoy' is a small C++ library for Approximate Nearest Neighbors written for efficient memory usage as well an ability to load from / save to disk. This package provides an R interface by relying on the 'Rcpp' package, exposing the same interface as the original Python wrapper to 'Annoy'. See <https://github.com/spotify/annoy> for more on 'Annoy'. 'Annoy' is released under Version 2.0 of the Apache License. Also included is a small Windows port of 'mmap' which is released under the MIT license.

Maintained by Dirk Eddelbuettel. Last updated 8 days ago.

annoy nearest nearest-neighbors cpp

25.4 match 72 stars 11.97 score 57 scripts 147 dependents

jlmelville

RcppHNSW:'Rcpp' Bindings for 'hnswlib', a Library for Approximate Nearest Neighbors

'Hnswlib' is a C++ library for Approximate Nearest Neighbors. This package provides a minimal R interface by relying on the 'Rcpp' package. See <https://github.com/nmslib/hnswlib> for more on 'hnswlib'. 'hnswlib' is released under Version 2.0 of the Apache License.

Maintained by James Melville. Last updated 3 months ago.

approximate-nearest-neighbor-search hnsw k-nearest-neighbors knn nearest-neighbor-search nmslib rcpp cpp

30.1 match 36 stars 10.07 score 63 scripts 77 dependents

jefferislab

RANN:Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric

Finds the k nearest neighbours for every point in a given dataset in O(N log N) time using Arya and Mount's ANN library (v1.1.3). There is support for approximate as well as exact searches, fixed radius searches and 'bd' as well as 'kd' trees. The distance is computed using the L2 (Euclidean) metric. Please see package 'RANN.L1' for the same functionality using the L1 (Manhattan, taxicab) metric.

Maintained by Gregory Jefferis. Last updated 7 months ago.

ann-library nearest-neighbors nearest-neighbours cpp

21.9 match 58 stars 12.21 score 1.3k scripts 190 dependents

joaquinauza

DetLifeInsurance:Life Insurance Premium and Reserves Valuation

Methods for valuation of life insurance premiums and reserves (including variable-benefit and fractional coverage) based on "Actuarial Mathematics" by Bowers, H.U. Gerber, J.C. Hickman, D.A. Jones and C.J. Nesbitt (1997, ISBN: 978-0938959465), "Actuarial Mathematics for Life Contingent Risks" by Dickson, David C. M., Hardy, Mary R. and Waters, Howard R (2009) <doi:10.1017/CBO9780511800146> and "Life Contingencies" by Jordan, C. W (1952) <doi:10.1017/S002026810005410X>. It also contains functions for equivalent interest and discount rate calculation, present and future values of annuities, and loan amortization schedule.

Maintained by Joaquin Auza. Last updated 5 years ago.

actuarial actuarial-science life-insurance

49.3 match 10 stars 4.70 score 3 scripts

paulnorthrop

donut:Nearest Neighbour Search with Variables on a Torus

Finds the k nearest neighbours in a dataset of specified points, adding the option to wrap certain variables on a torus. The user chooses the algorithm to use to find the nearest neighbours. Two such algorithms, provided by the packages 'RANN' <https://cran.r-project.org/package=RANN>, and 'nabor' <https://cran.r-project.org/package=nabor>, are suggested.

Maintained by Paul J. Northrop. Last updated 2 years ago.

degrees donut edges knn-algorithm knn-search nabor nearest nearest-neighbor nearest-neighbor-search nearest-neighbors nearest-neighbour-algorithm nearest-neighbours neighbors periodicity rann torus wrap

55.4 match 1 stars 4.18 score 5 scripts 1 dependents

mhahsler

dbscan:Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Related Algorithms

A fast reimplementation of several density-based algorithms of the DBSCAN family. Includes the clustering algorithms DBSCAN (density-based spatial clustering of applications with noise) and HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering points to identify the clustering structure), shared nearest neighbor clustering, and the outlier detection algorithms LOF (local outlier factor) and GLOSH (global-local outlier score from hierarchies). The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided. Hahsler, Piekenbrock and Doran (2019) <doi:10.18637/jss.v091.i01>.

Maintained by Michael Hahsler. Last updated 2 months ago.

clustering dbscan density-based-clustering hdbscan lof optics cpp

13.6 match 321 stars 15.62 score 1.6k scripts 84 dependents

spatstat

spatstat.explore:Exploratory Data Analysis for the 'spatstat' Family

Functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.

Maintained by Adrian Baddeley. Last updated 1 months ago.

cluster-detection confidence-intervals hypothesis-testing k-function roc-curves scan-statistics significance-testing simulation-envelopes spatial-analysis spatial-data-analysis spatial-sharpening spatial-smoothing spatial-statistics

20.6 match 1 stars 10.17 score 67 scripts 148 dependents

prodriguezsosa

conText:'a la Carte' on Text (ConText) Embedding Regression

A fast, flexible and transparent framework to estimate context-specific word and short document embeddings using the 'a la carte' embeddings approach developed by Khodak et al. (2018) <arXiv:1805.05388> and evaluate hypotheses about covariate effects on embeddings using the regression framework developed by Rodriguez et al. (2021)<https://github.com/prodriguezsosa/EmbeddingRegression>.

Maintained by Pedro L. Rodriguez. Last updated 11 months ago.

19.8 match 104 stars 9.40 score 1.7k scripts

bioc

BiocNeighbors:Nearest Neighbor Detection for Bioconductor Packages

Implements exact and approximate methods for nearest neighbor detection, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Exact searches can be performed using the k-means for k-nearest neighbors algorithm or with vantage point trees. Approximate searches can be performed using the Annoy or HNSW libraries. Searching on either Euclidean or Manhattan distances is supported. Parallelization is achieved for all methods by using BiocParallel. Functions are also provided to search for all neighbors within a given distance.

Maintained by Aaron Lun. Last updated 12 days ago.

clustering classification cpp

17.9 match 10.14 score 646 scripts 89 dependents

bnaras

pamr:Pam: Prediction Analysis for Microarrays

Some functions for sample classification in microarrays.

Maintained by Balasubramanian Narasimhan. Last updated 9 months ago.

21.7 match 7.90 score 256 scripts 14 dependents

cran

FNN:Fast Nearest Neighbor Search Algorithms and Applications

Cover-tree and kd-tree fast k-nearest neighbor search algorithms and related applications including KNN classification, regression and information measures are implemented.

Maintained by Shengqiao Li. Last updated 6 months ago.

cpp

16.6 match 5 stars 9.94 score 2.4k scripts 594 dependents

klausvigo

kknn:Weighted k-Nearest Neighbors

Weighted k-Nearest Neighbors for Classification, Regression and Clustering.

Maintained by Klaus Schliep. Last updated 4 years ago.

nearest-neighbor

14.7 match 23 stars 11.08 score 4.6k scripts 41 dependents

hannameyer

CAST:'caret' Applications for Spatial-Temporal Models

Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019) <doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021) <doi:10.1111/2041-210X.13650>; Milà et al. (2022) <doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022) <doi:10.1038/s41467-022-29838-9>; Linnenbrink et al. (2023) <doi:10.5194/egusphere-2023-1308>; Schumacher et al. (2024) <doi:10.5194/egusphere-2024-2730>. The package is described in detail in Meyer et al. (2024) <doi:10.48550/arXiv.2404.06978>.

Maintained by Hanna Meyer. Last updated 2 months ago.

autocorrelation caret feature-selection machine-learning overfitting predictive-modeling spatial spatio-temporal variable-selection

12.7 match 114 stars 11.97 score 298 scripts 1 dependents

topepo

caret:Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Maintained by Max Kuhn. Last updated 3 months ago.

7.4 match 1.6k stars 19.24 score 61k scripts 303 dependents

satijalab

Seurat:Tools for Single Cell Genomics

A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.

Maintained by Paul Hoffman. Last updated 1 years ago.

human-cell-atlas single-cell-genomics single-cell-rna-seq cpp

7.3 match 2.4k stars 16.86 score 50k scripts 73 dependents

jefferis

nabor:Wraps 'libnabo', a Fast K Nearest Neighbour Library for Low Dimensions

An R wrapper for 'libnabo', an exact or approximate k nearest neighbour library which is optimised for low dimensional spaces (e.g. 3D). 'libnabo' has speed and space advantages over the 'ANN' library wrapped by package 'RANN'. 'nabor' includes a knn function that is designed as a drop-in replacement for 'RANN' function nn2. In addition, objects which include the k-d tree search structure can be returned to speed up repeated queries of the same set of target points.

Maintained by Gregory Jefferis. Last updated 5 years ago.

libnabo nearest-neighbors cpp

14.2 match 22 stars 8.21 score 104 scripts 34 dependents

mlampros

KernelKnn:Kernel k Nearest Neighbors

Extends the simple k-nearest neighbors algorithm by incorporating numerous kernel functions and a variety of distance metrics. The package takes advantage of 'RcppArmadillo' to speed up the calculation of distances between observations.

Maintained by Lampros Mouselimis. Last updated 2 years ago.

cpp11 distance-metric kernel-methods knn rcpparmadillo openblas cpp openmp

12.4 match 17 stars 9.16 score 54 scripts 13 dependents

rsbivand

splancs:Spatial and Space-Time Point Pattern Analysis

The Splancs package was written as an enhancement to S-Plus for display and analysis of spatial point pattern data; it has been ported to R and is in "maintenance mode".

Maintained by Roger Bivand. Last updated 10 months ago.

fortran

12.7 match 1 stars 8.72 score 592 scripts 53 dependents

bioc

GenomicRanges:Representation and manipulation of genomic intervals

The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome. More specialized containers for representing and manipulating short alignments against a reference genome, or a matrix-like summarization of an experiment, are defined in the GenomicAlignments and SummarizedExperiment packages, respectively. Both packages build on top of the GenomicRanges infrastructure.

Maintained by Hervé Pagès. Last updated 4 months ago.

genetics infrastructure datarepresentation sequencing annotation genomeannotation coverage bioconductor-package core-package

6.2 match 44 stars 17.75 score 13k scripts 1.3k dependents

gmcmacran

dann:Discriminant Adaptive Nearest Neighbor Classification

Discriminant Adaptive Nearest Neighbor Classification is a variation of k nearest neighbors where the shape of the neighborhood is data driven. This package implements dann and sub_dann from Hastie (1996) <https://web.stanford.edu/~hastie/Papers/dann_IEEE.pdf>.

Maintained by Greg McMahan. Last updated 8 months ago.

openblas cpp

28.7 match 3.74 score 37 scripts

rspatial

terra:Spatial Data Analysis

Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).

Maintained by Robert J. Hijmans. Last updated 22 hours ago.

geospatial raster spatial vector onetbb proj gdal geos cpp

5.3 match 559 stars 17.64 score 17k scripts 851 dependents

spatstat

spatstat.linnet:Linear Networks Functionality of the 'spatstat' Family

Defines types of spatial data on a linear network and provides functionality for geometrical operations, data analysis and modelling of data on a linear network, in the 'spatstat' family of packages. Contains definitions and support for linear networks, including creation of networks, geometrical measurements, topological connectivity, geometrical operations such as inserting and deleting vertices, intersecting a network with another object, and interactive editing of networks. Data types defined on a network include point patterns, pixel images, functions, and tessellations. Exploratory methods include kernel estimation of intensity on a network, K-functions and pair correlation functions on a network, simulation envelopes, nearest neighbour distance and empty space distance, relative risk estimation with cross-validated bandwidth selection. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the function lppm() similar to glm(). Only Poisson models are implemented so far. Models may involve dependence on covariates and dependence on marks. Models are fitted by maximum likelihood. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. Random point patterns on a network can be generated using a variety of models.

Maintained by Adrian Baddeley. Last updated 2 months ago.

density-estimation heat-equation kernel-density-estimation network-analysis point-processes spatial-data-analysis statistical-analysis statistical-inference statistical-models

9.6 match 6 stars 9.64 score 35 scripts 43 dependents

bioc

SummarizedExperiment:A container (S4 class) for matrix-like assays

The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.

Maintained by Hervé Pagès. Last updated 5 months ago.

genetics infrastructure sequencing annotation coverage genomeannotation bioconductor-package core-package

5.1 match 34 stars 16.85 score 8.6k scripts 1.2k dependents

bioc

IRanges:Foundation of integer range manipulation in Bioconductor

Provides efficient low-level and highly reusable S4 classes for storing, manipulating and aggregating over annotated ranges of integers. Implements an algebra of range operations, including efficient algorithms for finding overlaps and nearest neighbors. Defines efficient list-like classes for storing, transforming and aggregating large grouped data, i.e., collections of atomic vectors and DataFrames.

Maintained by Hervé Pagès. Last updated 1 months ago.

infrastructure datarepresentation bioconductor-package core-package

5.6 match 22 stars 15.09 score 2.1k scripts 1.8k dependents

r-spatial

sf:Simple Features for R

Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL' <doi: 10.5281/zenodo.5884351> for reading and writing data, to 'GEOS' <doi: 10.5281/zenodo.11396894> for geometrical operations, and to 'PROJ' <doi: 10.5281/zenodo.5884394> for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree) coordinates.

Maintained by Edzer Pebesma. Last updated 16 days ago.

gdal geos proj spatial cpp

3.7 match 1.4k stars 22.42 score 117k scripts 1.2k dependents

njtierney

brolgar:Browse Over Longitudinal Data Graphically and Analytically in R

Provides a framework of tools to summarise, visualise, and explore longitudinal data. It builds upon the tidy time series data frames used in the 'tsibble' package, and is designed to integrate within the 'tidyverse', and 'tidyverts' (for time series) ecosystems. The methods implemented include calculating features for understanding longitudinal data, including calculating summary statistics such as quantiles, medians, and numeric ranges, sampling individual series, identifying individual series representative of a group, and extending the facet system in 'ggplot2' to facilitate exploration of samples of data. These methods are fully described in the paper "brolgar: An R package to Browse Over Longitudinal Data Graphically and Analytically in R", Nicholas Tierney, Dianne Cook, Tania Prvan (2020) <doi:10.32614/RJ-2022-023>.

Maintained by Nicholas Tierney. Last updated 2 months ago.

9.1 match 109 stars 8.73 score 141 scripts

jfrench

smerc:Statistical Methods for Regional Counts

Implements statistical methods for analyzing the counts of areal data, with a focus on the detection of spatial clusters and clustering. The package has a heavy emphasis on spatial scan methods, which were first introduced by Kulldorff and Nagarwalla (1995) <doi:10.1002/sim.4780140809> and Kulldorff (1997) <doi:10.1080/03610929708831995>.

Maintained by Joshua French. Last updated 5 months ago.

cpp

12.9 match 3 stars 6.11 score 45 scripts 3 dependents

michaeldorman

nngeo:k-Nearest Neighbor Join for Spatial Data

K-nearest neighbor search for projected and non-projected 'sf' spatial layers. Nearest neighbor search uses (1) C code from 'GeographicLib' for lon-lat point layers, (2) function knn() from package 'nabor' for projected point layers, or (3) function st_distance() from package 'sf' for line or polygon layers. The package also includes several other utility functions for spatial analysis.

Maintained by Michael Dorman. Last updated 11 months ago.

8.0 match 81 stars 9.70 score 600 scripts 6 dependents

bioc

CatsCradle:This package provides methods for analysing spatial transcriptomics data and for discovering gene clusters

This package addresses two broad areas. It allows for in-depth analysis of spatial transcriptomic data by identifying tissue neighbourhoods. These are contiguous regions of tissue surrounding individual cells. 'CatsCradle' allows for the categorisation of neighbourhoods by the cell types contained in them and the genes expressed in them. In particular, it produces Seurat objects whose individual elements are neighbourhoods rather than cells. In addition, it enables the categorisation and annotation of genes by producing Seurat objects whose elements are genes.

Maintained by Michael Shapiro. Last updated 1 months ago.

biologicalquestion statisticalmethod geneexpression singlecell transcriptomics spatial

11.7 match 3 stars 6.50 score

bioc

matter:Out-of-core statistical computing and signal processing

Toolbox for larger-than-memory scientific computing and visualization, providing efficient out-of-core data structures using files or shared memory, for dense and sparse vectors, matrices, and arrays, with applications to nonuniformly sampled signals and images.

Maintained by Kylie A. Bemis. Last updated 3 months ago.

infrastructure datarepresentation dataimport dimensionreduction preprocessing cpp

7.3 match 57 stars 9.52 score 64 scripts 2 dependents

jeffreyevans

yaImpute:Nearest Neighbor Observation Imputation and Evaluation Tools

Performs nearest neighbor-based imputation using one or more alternative approaches to processing multivariate data. These include methods based on canonical correlation: analysis, canonical correspondence analysis, and a multivariate adaptation of the random forest classification and regression techniques of Leo Breiman and Adele Cutler. Additional methods are also offered. The package includes functions for comparing the results from running alternative techniques, detecting imputation targets that are notably distant from reference observations, detecting and correcting for bias, bootstrapping and building ensemble imputations, and mapping results.

Maintained by Jeffrey S. Evans. Last updated 6 months ago.

imputation cpp

8.8 match 3 stars 7.40 score 94 scripts 12 dependents

ssnn-airr

shazam:Immunoglobulin Somatic Hypermutation Analysis

Provides a computational framework for analyzing mutations in immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of antigen-driven selection pressure, mutational load quantification, building of somatic hypermutation (SHM) models, and model-dependent distance calculations. Also includes empirically derived models of SHM for both mice and humans. Citations: Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>, Yaari, et al (2012) <doi:10.1093/nar/gks457>, Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>, Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.

Maintained by Susanna Marquez. Last updated 2 months ago.

8.4 match 7.43 score 222 scripts 2 dependents

lindbrook

cholera:Amend, Augment and Aid Analysis of John Snow's Cholera Map

Amends errors, augments data and aids analysis of John Snow's map of the 1854 London cholera outbreak.

Maintained by lindbrook. Last updated 1 days ago.

cholera data-visualization datasets epidemiology john-snow public-health triangulation-delaunay voronoi voronoi-polygons

6.7 match 136 stars 9.33 score 95 scripts

kosukeimai

MatchIt:Nonparametric Preprocessing for Parametric Causal Inference

Selects matched samples of the original treated and control groups with similar covariate distributions -- can be used to match exactly on covariates, to match on propensity scores, or perform a variety of other matching procedures. The package also implements a series of recommendations offered in Ho, Imai, King, and Stuart (2007) <DOI:10.1093/pan/mpl013>. (The 'gurobi' package, which is not on CRAN, is optional and comes with an installation of the Gurobi Optimizer, available at <https://www.gurobi.com>.)

Maintained by Noah Greifer. Last updated 2 days ago.

cpp openmp

4.1 match 220 stars 15.03 score 2.4k scripts 21 dependents

stuart-lab

Signac:Analysis of Single-Cell Chromatin Data

A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2021) <doi:10.1038/s41592-021-01282-5>.

Maintained by Tim Stuart. Last updated 7 months ago.

atac bioinformatics single-cell zlib cpp

5.1 match 349 stars 12.19 score 3.7k scripts 1 dependents

neurodata

lolR:Linear Optimal Low-Rank Projection

Supervised learning techniques designed for the situation when the dimensionality exceeds the sample size have a tendency to overfit as the dimensionality of the data increases. To remedy this High dimensionality; low sample size (HDLSS) situation, we attempt to learn a lower-dimensional representation of the data before learning a classifier. That is, we project the data to a situation where the dimensionality is more manageable, and then are able to better apply standard classification or clustering techniques since we will have fewer dimensions to overfit. A number of previous works have focused on how to strategically reduce dimensionality in the unsupervised case, yet in the supervised HDLSS regime, few works have attempted to devise dimensionality reduction techniques that leverage the labels associated with the data. In this package and the associated manuscript Vogelstein et al. (2017) <arXiv:1709.01233>, we provide several methods for feature extraction, some utilizing labels and some not, along with easily extensible utilities to simplify cross-validative efforts to identify the best feature extraction method. Additionally, we include a series of adaptable benchmark simulations to serve as a standard for future investigative efforts into supervised HDLSS. Finally, we produce a comprehensive comparison of the included algorithms across a range of benchmark simulations and real data applications.

Maintained by Eric Bridgeford. Last updated 4 years ago.

8.4 match 20 stars 7.28 score 80 scripts

dgrun

RaceID:Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Application of 'RaceID' allows inference of cell types and prediction of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) <DOI:10.1038/nmeth.4662>). 'VarID2' is part of this package and allows quantification of biological gene expression noise at single-cell resolution (Rosales-Alvarez, R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, D. (2023) <DOI:10.1186/s13059-023-02974-1>).

Maintained by Dominic Grün. Last updated 4 months ago.

cpp

12.9 match 4.74 score 110 scripts

antoniofabio

tseriesChaos:Analysis of Nonlinear Time Series

Routines for the analysis of nonlinear time series. This work is largely inspired by the TISEAN project, by Rainer Hegger, Holger Kantz and Thomas Schreiber: <http://www.mpipks-dresden.mpg.de/~tisean/>.

Maintained by Antonio Fabio Di Narzo. Last updated 6 years ago.

11.7 match 3 stars 5.12 score 106 scripts 6 dependents

andrisignorell

DescTools:Tools for Descriptive Statistics

A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.

Maintained by Andri Signorell. Last updated 7 hours ago.

fortran cpp

3.4 match 87 stars 16.70 score 7.7k scripts 99 dependents

bioimaginggroup

bioimagetools:Tools for Microscopy Imaging

Tools for 3D imaging, mostly for biology/microscopy. Read and write TIFF stacks. Functions for segmentation, filtering and analyzing 3D point patterns.

Maintained by Volker Schmid. Last updated 3 years ago.

biology microscopy

10.8 match 4 stars 5.30 score 33 scripts 1 dependents

ludovikcoba

rrecsys:Environment for Evaluating Recommender Systems

Processes standard recommendation datasets (e.g., a user-item rating matrix) as input and generates rating predictions and lists of recommended items. Standard algorithm implementations which are included in this package are the following: Global/Item/User-Average baselines, Weighted Slope One, Item-Based KNN, User-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according to the standard offline evaluation methodology (Shani, et al. (2011) <doi:10.1007/978-0-387-85820-3_8>) for recommender systems using measures such as MAE, RMSE, Precision, Recall, F1, AUC, NDCG, RankScore and coverage measures. The package (Coba, et al.(2017) <doi: 10.1007/978-3-319-60042-0_36>) is intended for rapid prototyping of recommendation algorithms and education purposes.

Maintained by Ludovik Çoba. Last updated 3 years ago.

cpp

8.3 match 23 stars 6.84 score 25 scripts

bioc

xcms:LC-MS and GC-MS Data Analysis

Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.

Maintained by Steffen Neumann. Last updated 2 days ago.

immunooncology massspectrometry metabolomics bioconductor feature-detection mass-spectrometry peak-detection cpp

3.9 match 196 stars 14.31 score 984 scripts 11 dependents

opengeos

whitebox:'WhiteboxTools' R Frontend

An R frontend for the 'WhiteboxTools' library, which is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. 'WhiteboxTools' can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. 'WhiteboxTools' also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. Suggested citation: Lindsay (2016) <doi:10.1016/j.cageo.2016.07.003>.

Maintained by Andrew Brown. Last updated 5 months ago.

geomorphometry geoprocessing geospatial gis hydrology remote-sensing rstudio

5.8 match 173 stars 9.65 score 203 scripts 2 dependents

njtierney

maxcovr:A Set of Tools For Solving The Maximal Covering Location Problem

Solving the "maximal covering location problem" as described by Church can be difficult for users not familiar with linear programming. maxcovr provides functions to make it easy to solve this problem, and tools to calculate facility coverage.

Maintained by Nicholas Tierney. Last updated 4 months ago.

distance linear-programming cpp

9.1 match 44 stars 6.06 score 43 scripts

r-lidar

lidR:Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.

Maintained by Jean-Romain Roussel. Last updated 1 months ago.

als forestry las laz lidar point-cloud remote-sensing openblas cpp openmp

3.8 match 623 stars 14.47 score 844 scripts 8 dependents

plangfelder

WGCNA:Weighted Correlation Network Analysis

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.

Maintained by Peter Langfelder. Last updated 6 months ago.

cpp

5.5 match 54 stars 9.65 score 5.3k scripts 32 dependents

ropensci

PostcodesioR:API Wrapper Around 'Postcodes.io'

Free UK geocoding using data from Office for National Statistics. It is using several functions to get information about post codes, outward codes, reverse geocoding, nearest post codes/outward codes, validation, or randomly generate a post code. API wrapper around <https://postcodes.io>.

Maintained by Eryk Walczak. Last updated 2 years ago.

api-wrapper geocoder geographic-data peer-reviewed postcode uk

8.1 match 41 stars 6.49 score 50 scripts

r-spatial

spdep:Spatial Dependence: Weighting Schemes, Statistics

A collection of functions to create spatial weights matrix objects from polygon 'contiguities', from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial 'autocorrelation', including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunção/Reis' (1999) <doi:10.1002/(SICI)1097-0258(19990830)18:16%3C2147::AID-SIM179%3E3.0.CO;2-I> Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x> and multicoloured join count statistics, 'APLE' ('Li 'et al.' ) <doi:10.1111/j.1538-4632.2007.00708.x>, local 'Moran's I', 'Gearys C' ('Anselin' 1995) <doi:10.1111/j.1538-4632.1995.tb00338.x> and 'Getis/Ord' G ('Ord' and 'Getis' 1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>, 'saddlepoint' approximations ('Tiefelsdorf' 2002) <doi:10.1111/j.1538-4632.2002.tb01084.x> and exact tests for global and local 'Moran's I' ('Bivand et al.' 2009) <doi:10.1016/j.csda.2008.07.021> and 'LOSH' local indicators of spatial heteroscedasticity ('Ord' and 'Getis') <doi:10.1007/s00168-011-0492-y>. The implementation of most of these measures is described in 'Bivand' and 'Wong' (2018) <doi:10.1007/s11749-018-0599-x>, with further extensions in 'Bivand' (2022) <doi:10.1111/gean.12319>. 'Lagrange' multiplier tests for spatial dependence in linear models are provided ('Anselin et al'. 1996) <doi:10.1016/0166-0462(95)02111-6>, as are 'Rao' score tests for hypothesised spatial 'Durbin' models based on linear models ('Koley' and 'Bera' 2023) <doi:10.1080/17421772.2023.2256810>. A local indicators for categorical data (LICD) implementation based on 'Carrer et al.' (2021) <doi:10.1016/j.jas.2020.105306> and 'Bivand et al.' (2017) <doi:10.1016/j.spasta.2017.03.003> was added in 1.3-7. From 'spdep' and 'spatialreg' versions >= 1.2-1, the model fitting functions previously present in this package are defunct in 'spdep' and may be found in 'spatialreg'.

Maintained by Roger Bivand. Last updated 18 days ago.

spatial-autocorrelation spatial-dependence spatial-weights

3.1 match 131 stars 16.62 score 6.0k scripts 107 dependents

mlampros

nmslibR:Non Metric Space (Approximate) Library

A Non-Metric Space Library ('NMSLIB' <https://github.com/nmslib/nmslib>) wrapper, which according to the authors "is an efficient cross-platform similarity search library and a toolkit for evaluation of similarity search methods. The goal of the 'NMSLIB' <https://github.com/nmslib/nmslib> Library is to create an effective and comprehensive toolkit for searching in generic non-metric spaces. Being comprehensive is important, because no single method is likely to be sufficient in all cases. Also note that exact solutions are hardly efficient in high dimensions and/or non-metric spaces. Hence, the main focus is on approximate methods". The wrapper also includes Approximate Kernel k-Nearest-Neighbor functions based on the 'NMSLIB' <https://github.com/nmslib/nmslib> 'Python' Library.

Maintained by Lampros Mouselimis. Last updated 2 years ago.

approximate-nearest-neighbor-search nmslib non-metric python reticulate cpp openmp

10.1 match 12 stars 5.14 score 23 scripts

bioc

scmap:A tool for unsupervised projection of single cell RNA-seq data

Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.

Maintained by Vladimir Kiselev. Last updated 5 months ago.

immunooncology singlecell software classification supportvectormachine rnaseq visualization transcriptomics datarepresentation transcription sequencing preprocessing geneexpression dataimport bioconductor-package human-cell-atlas projection-mapping single-cell-rna-seq openblas cpp

5.7 match 95 stars 8.82 score 172 scripts

bioc

batchelor:Single-Cell Batch Correction Methods

Implements a variety of methods for batch correction of single-cell (RNA sequencing) data. This includes methods based on detecting mutually nearest neighbors, as well as several efficient variants of linear regression of the log-expression values. Functions are also provided to perform global rescaling to remove differences in depth between batches, and to perform a principal components analysis that is robust to differences in the numbers of cells across batches.

Maintained by Aaron Lun. Last updated 3 days ago.

sequencing rnaseq software geneexpression transcriptomics singlecell batcheffect normalization cpp

5.5 match 9.10 score 1.2k scripts 10 dependents

bioc

singleCellTK:Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

The Single Cell Toolkit (SCTK) in the singleCellTK package provides an interface to popular tools for importing, quality control, analysis, and visualization of single cell RNA-seq data. SCTK allows users to seamlessly integrate tools from various packages at different stages of the analysis workflow. A general "a la carte" workflow gives users the ability access to multiple methods for data importing, calculation of general QC metrics, doublet detection, ambient RNA estimation and removal, filtering, normalization, batch correction or integration, dimensionality reduction, 2-D embedding, clustering, marker detection, differential expression, cell type labeling, pathway analysis, and data exporting. Curated workflows can be used to run Seurat and Celda. Streamlined quality control can be performed on the command line using the SCTK-QC pipeline. Users can analyze their data using commands in the R console or by using an interactive Shiny Graphical User Interface (GUI). Specific analyses or entire workflows can be summarized and shared with comprehensive HTML reports generated by Rmarkdown. Additional documentation and vignettes can be found at camplab.net/sctk.

Maintained by Joshua David Campbell. Last updated 24 days ago.

singlecell geneexpression differentialexpression alignment clustering immunooncology batcheffect normalization qualitycontrol dataimport gui

4.9 match 181 stars 10.16 score 252 scripts

datastorm-open

visNetwork:Network Visualization using 'vis.js' Library

Provides an R interface to the 'vis.js' JavaScript charting library. It allows an interactive visualization of networks.

Maintained by Benoit Thieurmel. Last updated 2 years ago.

3.3 match 549 stars 15.14 score 4.1k scripts 195 dependents

bioc

pcaMethods:A collection of PCA methods

Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany.

Maintained by Henning Redestig. Last updated 5 months ago.

bayesian cpp

3.8 match 49 stars 13.10 score 538 scripts 73 dependents

bioc

tidytof:Analyze High-dimensional Cytometry Data Using Tidy Data Principles

This package implements an interactive, scientific analysis pipeline for high-dimensional cytometry data built using tidy data principles. It is specifically designed to play well with both the tidyverse and Bioconductor software ecosystems, with functionality for reading/writing data files, data cleaning, preprocessing, clustering, visualization, modeling, and other quality-of-life functions. tidytof implements a "grammar" of high-dimensional cytometry data analysis.

Maintained by Timothy Keyes. Last updated 5 months ago.

singlecell flowcytometry bioinformatics cytometry data-science single-cell tidyverse cpp

6.7 match 19 stars 7.26 score 35 scripts

bioc

edgeR:Empirical Analysis of Digital Gene Expression Data in R

Differential expression analysis of sequence count data. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models, quasi-likelihood, and gene set enrichment. Can perform differential analyses of any type of omics data that produces read counts, including RNA-seq, ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral counts. RNA-seq analyses can be conducted at the gene or isoform level, and tests can be conducted for differential exon or transcript usage.

Maintained by Yunshun Chen. Last updated 5 days ago.

alternativesplicing batcheffect bayesian biomedicalinformatics cellbiology chipseq clustering coverage differentialexpression differentialmethylation differentialsplicing dnamethylation epigenetics functionalgenomics geneexpression genesetenrichment genetics immunooncology multiplecomparison normalization pathways proteomics qualitycontrol regression rnaseq sage sequencing singlecell systemsbiology timecourse transcription transcriptomics openblas

3.5 match 13.40 score 17k scripts 255 dependents

mlr-org

mlr3learners:Recommended Learners for 'mlr3'

Recommended Learners for 'mlr3'. Extends 'mlr3' with interfaces to essential machine learning packages on CRAN. This includes, but is not limited to: (penalized) linear and logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, naive Bayes, support vector machines, and gradient boosting.

Maintained by Marc Becker. Last updated 4 months ago.

classification learners machine-learning mlr3 regression

4.1 match 91 stars 11.51 score 1.5k scripts 10 dependents

cran

class:Functions for Classification

Various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps.

Maintained by Brian Ripley. Last updated 2 months ago.

6.0 match 1 stars 7.83 score 2.2k dependents

satijalab

SeuratObject:Data Structures for Single Cell Data

Defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. Provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.

Maintained by Paul Hoffman. Last updated 1 years ago.

cpp

4.0 match 25 stars 11.69 score 1.2k scripts 88 dependents

bioc

ChIPpeakAnno:Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments, or any experiments that result in large number of genomic interval data

The package encompasses a range of functions for identifying the closest gene, exon, miRNA, or custom features—such as highly conserved elements and user-supplied transcription factor binding sites. Additionally, users can retrieve sequences around the peaks and obtain enriched Gene Ontology (GO) or Pathway terms. In version 2.0.5 and beyond, new functionalities have been introduced. These include features for identifying peaks associated with bi-directional promoters along with summary statistics (peaksNearBDP), summarizing motif occurrences in peaks (summarizePatternInPeaks), and associating additional identifiers with annotated peaks or enrichedGO (addGeneIDs). The package integrates with various other packages such as biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest, and stat to enhance its analytical capabilities.

Maintained by Jianhong Ou. Last updated 2 months ago.

annotation chipseq chipchip

5.2 match 8.75 score 584 scripts 6 dependents

biooss

sensitivity:Global Sensitivity Analysis of Model Outputs and Importance Measures

A collection of functions for sensitivity analysis of model outputs (factor screening, global sensitivity analysis and robustness analysis), for variable importance measures of data, as well as for interpretability of machine learning models. Most of the functions have to be applied on scalar output, but several functions support multi-dimensional outputs.

Maintained by Bertrand Iooss. Last updated 7 months ago.

cpp

6.7 match 17 stars 6.74 score 472 scripts 8 dependents

rpolars

polars:Lightning-Fast 'DataFrame' Library

Lightning-fast 'DataFrame' library written in 'Rust'. Convert R data to 'Polars' data and vice versa. Perform fast, lazy, larger-than-memory and optimized data queries. 'Polars' is interoperable with the package 'arrow', as both are based on the 'Apache Arrow' Columnar Format.

Maintained by Soren Welling. Last updated 3 days ago.

arrow polars rust

3.8 match 499 stars 12.01 score 1.0k scripts 2 dependents

juanmartinsantos

rgnoisefilt:Elimination of Noisy Samples in Regression Datasets using Noise Filters

Traditional noise filtering methods aim at removing noisy samples from a classification dataset. This package adapts classic and recent filtering techniques for use in regression problems, and it also incorporates methods specifically designed for regression data. In order to do this, it uses approaches proposed in the specialized literature, such as Martin et al. (2021) [<doi:10.1109/ACCESS.2021.3123151>] and Arnaiz-Gonzalez et al. (2016) [<doi:10.1016/j.eswa.2015.12.046>]. Thus, the goal of the implemented noise filters is to eliminate samples with noise in regression datasets.

Maintained by Juan Martin. Last updated 1 years ago.

11.0 match 2 stars 4.00 score 3 scripts

bioc

plyranges:A fluent interface for manipulating GenomicRanges

A dplyr-like interface for interacting with the common Bioconductor classes Ranges and GenomicRanges. By providing a grammatical and consistent way of manipulating these classes their accessiblity for new Bioconductor users is hopefully increased.

Maintained by Michael Love. Last updated 5 months ago.

infrastructure datarepresentation workflowstep coverage bioconductor data-analysis dplyr genomic-ranges genomics tidy-data

3.5 match 143 stars 12.60 score 1.9k scripts 20 dependents

bioc

CMA:Synthesis of microarray-based classification

This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.

Maintained by Roman Hornung. Last updated 5 months ago.

classification decisiontree

8.5 match 5.09 score 61 scripts

uligges

klaR:Classification and Visualization

Miscellaneous functions for classification and visualization, e.g. regularized discriminant analysis, sknn() kernel-density naive Bayes, an interface to 'svmlight' and stepclass() wrapper variable selection for supervised classification, partimat() visualization of classification rules and shardsplot() of cluster results as well as kmodes() clustering for categorical data, corclust() variable clustering, variable extraction from different variable clustering models and weight of evidence preprocessing.

Maintained by Uwe Ligges. Last updated 1 years ago.

5.7 match 5 stars 7.61 score 1.4k scripts 13 dependents

cran

iCAMP:Infer Community Assembly Mechanisms by Phylogenetic-Bin-Based Null Model Analysis

To implement a general framework to quantitatively infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis, abbreviated as 'iCAMP' (Ning et al 2020) <doi:10.1038/s41467-020-18560-z>. It can quantitatively assess the relative importance of different community assembly processes, such as selection, dispersal, and drift, for both communities and each phylogenetic group ('bin'). Each bin usually consists of different taxa from a family or an order. The package also provides functions to implement some other published methods, including neutral taxa percentage (Burns et al 2016) <doi:10.1038/ismej.2015.142> based on neutral theory model and quantifying assembly processes based on entire-community null models ('QPEN', Stegen et al 2013) <doi:10.1038/ismej.2013.93>. It also includes some handy functions, particularly for big datasets, such as phylogenetic and taxonomic null model analysis at both community and bin levels, between-taxa niche difference and phylogenetic distance calculation, phylogenetic signal test within phylogenetic groups, midpoint root of big trees, etc. Version 1.3.x mainly improved the function for 'QPEN' and added function 'icamp.cate()' to summarize 'iCAMP' results for different categories of taxa (e.g. core versus rare taxa).

Maintained by Daliang Ning. Last updated 3 years ago.

18.7 match 2 stars 2.26 score 1 dependents

bioc

recountmethylation:Access and analyze public DNA methylation array data compilations

Resources for cross-study analyses of public DNAm array data from NCBI GEO repo, produced using Illumina's Infinium HumanMethylation450K (HM450K) and MethylationEPIC (EPIC) platforms. Provided functions enable download, summary, and filtering of large compilation files. Vignettes detail background about file formats, example analyses, and more. Note the disclaimer on package load and consult the main manuscripts for further info.

Maintained by Sean K Maden. Last updated 5 months ago.

dnamethylation epigenetics microarray methylationarray experimenthub

6.5 match 9 stars 6.28 score 9 scripts

skembel

picante:Integrating Phylogenies and Ecology

Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) <doi:10.1093/bioinformatics/btq166>.

Maintained by Steven W. Kembel. Last updated 2 years ago.

3.6 match 34 stars 11.42 score 1.1k scripts 16 dependents

thothorn

ipred:Improved Predictors

Improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.

Maintained by Torsten Hothorn. Last updated 8 months ago.

3.8 match 10.76 score 3.3k scripts 411 dependents

welch-lab

cytosignal:What the Package Does (One Line, Title Case)

What the package does (one paragraph).

Maintained by Jialin Liu. Last updated 6 days ago.

openblas cpp

6.7 match 16 stars 5.95 score 6 scripts

bioc

ChemmineR:Cheminformatics Toolkit for R

ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.

Maintained by Thomas Girke. Last updated 5 months ago.

cheminformatics biomedicalinformatics pharmacogenetics pharmacogenomics microtitreplateassay cellbasedassays visualization infrastructure dataimport clustering proteomics metabolomics cpp

4.3 match 14 stars 9.42 score 253 scripts 12 dependents

stevecondylios

priceR:Economics and Pricing Tools

Functions to aid in micro and macro economic analysis and handling of price and currency data. Includes extraction of relevant inflation and exchange rate data from World Bank API, data cleaning/parsing, and standardisation. Inflation adjustment calculations as found in Principles of Macroeconomics by Gregory Mankiw et al (2014). Current and historical end of day exchange rates for 171 currencies from the European Central Bank Statistical Data Warehouse (2020) <https://sdw.ecb.europa.eu/curConverter.do>.

Maintained by Steve Condylios. Last updated 7 months ago.

data-science econometrics economics finance modeling r-programming statistics

5.4 match 59 stars 7.37 score 102 scripts

igraph

igraph:Network Analysis and Visualization

Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.

Maintained by Kirill Müller. Last updated 11 hours ago.

complex-networks graph-algorithms graph-theory mathematics network-analysis network-graph fortran libxml2 glpk openblas cpp

1.9 match 582 stars 21.11 score 31k scripts 1.9k dependents

ropensci

weatherOz:An API Client for Australian Weather and Climate Data Resources

Provides automated downloading, parsing and formatting of weather data for Australia through API endpoints provided by the Department of Primary Industries and Regional Development ('DPIRD') of Western Australia and by the Science and Technology Division of the Queensland Government's Department of Environment and Science ('DES'). As well as the Bureau of Meteorology ('BOM') of the Australian government precis and coastal forecasts, and downloading and importing radar and satellite imagery files. 'DPIRD' weather data are accessed through public 'APIs' provided by 'DPIRD', <https://www.agric.wa.gov.au/weather-api-20>, providing access to weather station data from the 'DPIRD' weather station network. Australia-wide weather data are based on data from the Australian Bureau of Meteorology ('BOM') data and accessed through 'SILO' (Scientific Information for Land Owners) Jeffrey et al. (2001) <doi:10.1016/S1364-8152(01)00008-1>. 'DPIRD' data are made available under a Creative Commons Attribution 3.0 Licence (CC BY 3.0 AU) license <https://creativecommons.org/licenses/by/3.0/au/deed.en>. SILO data are released under a Creative Commons Attribution 4.0 International licence (CC BY 4.0) <https://creativecommons.org/licenses/by/4.0/>. 'BOM' data are (c) Australian Government Bureau of Meteorology and released under a Creative Commons (CC) Attribution 3.0 licence or Public Access Licence ('PAL') as appropriate, see <http://www.bom.gov.au/other/copyright.shtml> for further details.

Maintained by Rodrigo Pires. Last updated 20 days ago.

dpird bom meteorological-data weather-forecast australia weather weather-data meteorology western-australia australia-bureau-of-meteorology western-australia-agriculture australia-agriculture australia-climate australia-weather api-client climate data rainfall weather-api

4.6 match 32 stars 8.54 score 40 scripts

jhmadsen

DDoutlier:Distance & Density-Based Outlier Detection

Outlier detection in multidimensional domains. Implementation of notable distance and density-based outlier algorithms. Allows users to identify local outliers by comparing observations to their nearest neighbors, reverse nearest neighbors, shared neighbors or natural neighbors. For distance-based approaches, see Knorr, M., & Ng, R. T. (1997) <doi:10.1145/782010.782021>, Angiulli, F., & Pizzuti, C. (2002) <doi:10.1007/3-540-45681-3_2>, Hautamaki, V., & Ismo, K. (2004) <doi:10.1109/ICPR.2004.1334558> and Zhang, K., Hutter, M. & Jin, H. (2009) <doi:10.1007/978-3-642-01307-2_84>. For density-based approaches, see Tang, J., Chen, Z., Fu, A. W. C., & Cheung, D. W. (2002) <doi:10.1007/3-540-47887-6_53>, Jin, W., Tung, A. K. H., Han, J., & Wang, W. (2006) <doi:10.1007/11731139_68>, Schubert, E., Zimek, A. & Kriegel, H-P. (2014) <doi:10.1137/1.9781611973440.63>, Latecki, L., Lazarevic, A. & Prokrajac, D. (2007) <doi:10.1007/978-3-540-73499-4_6>, Papadimitriou, S., Gibbons, P. B., & Faloutsos, C. (2003) <doi:10.1109/ICDE.2003.1260802>, Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) <doi:10.1145/342009.335388>, Kriegel, H.-P., Kröger, P., Schubert, E., & Zimek, A. (2009) <doi:10.1145/1645953.1646195>, Zhu, Q., Feng, Ji. & Huang, J. (2016) <doi:10.1016/j.patrec.2016.05.007>, Huang, J., Zhu, Q., Yang, L. & Feng, J. (2015) <doi:10.1016/j.knosys.2015.10.014>, Tang, B. & Haibo, He. (2017) <doi:10.1016/j.neucom.2017.02.039> and Gao, J., Hu, W., Zhang, X. & Wu, Ou. (2011) <doi:10.1007/978-3-642-20847-8_23>.

Maintained by Jacob H. Madsen. Last updated 6 years ago.

7.7 match 12 stars 5.00 score 56 scripts 1 dependents

ropensci

geonames:Interface to the "Geonames" Spatial Query Web Service

The web service at <https://www.geonames.org/> provides a number of spatial data queries, including administrative area hierarchies, city locations and some country postal code queries. A (free) username is required and rate limits exist.

Maintained by Barry Rowlingson. Last updated 6 years ago.

4.5 match 37 stars 8.45 score 165 scripts 21 dependents

urbananalyst

dodgr:Distances on Directed Graphs

Distances on dual-weighted directed graphs using priority-queue shortest paths (Padgham (2019) <doi:10.32866/6945>). Weighted directed graphs have weights from A to B which may differ from those from B to A. Dual-weighted directed graphs have two sets of such weights. A canonical example is a street network to be used for routing in which routes are calculated by weighting distances according to the type of way and mode of transport, yet lengths of routes must be calculated from direct distances.

Maintained by Mark Padgham. Last updated 5 days ago.

distance openstreetmap router shortest-paths street-networks cpp

3.3 match 129 stars 11.53 score 229 scripts 4 dependents

nsaph-software

GPCERF:Gaussian Processes for Estimating Causal Exposure Response Curves

Provides a non-parametric Bayesian framework based on Gaussian process priors for estimating causal effects of a continuous exposure and detecting change points in the causal exposure response curves using observational data. Ren, B., Wu, X., Braun, D., Pillai, N., & Dominici, F.(2021). "Bayesian modeling for exposure response curve via gaussian processes: Causal effects of exposure to air pollution on health outcomes." arXiv preprint <doi:10.48550/arXiv.2105.03454>.

Maintained by Boyu Ren. Last updated 11 months ago.

cpp

5.9 match 9 stars 6.33 score 16 scripts

ericarcher

swfscMisc:Miscellaneous Functions for Southwest Fisheries Science Center

Collection of conversion, analytical, geodesic, mapping, and plotting functions. Used to support packages and code written by researchers at the Southwest Fisheries Science Center of the National Oceanic and Atmospheric Administration.

Maintained by Eric Archer. Last updated 11 months ago.

jags cpp

6.0 match 2 stars 6.18 score 101 scripts 20 dependents

fridleylab

spatialTIME:Spatial Analysis of Vectra Immunoflourescent Data

Visualization and analysis of Vectra Immunoflourescent data. Options for calculating both the univariate and bivariate Ripley's K are included. Calculations are performed using a permutation-based approach presented by Wilson et al. <doi:10.1101/2021.04.27.21256104>.

Maintained by Fridley Lab. Last updated 7 months ago.

6.1 match 4 stars 6.08 score 30 scripts

bioc

GenomicDistributions:GenomicDistributions: fast analysis of genomic intervals with Bioconductor

If you have a set of genomic ranges, this package can help you with visualization and comparison. It produces several kinds of plots, for example: Chromosome distribution plots, which visualize how your regions are distributed over chromosomes; feature distance distribution plots, which visualizes how your regions are distributed relative to a feature of interest, like Transcription Start Sites (TSSs); genomic partition plots, which visualize how your regions overlap given genomic features such as promoters, introns, exons, or intergenic regions. It also makes it easy to compare one set of ranges to another.

Maintained by Kristyna Kupkova. Last updated 5 months ago.

software genomeannotation genomeassembly datarepresentation sequencing coverage functionalgenomics visualization

5.0 match 26 stars 7.44 score 25 scripts

cran

interp:Interpolation Methods

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide FOSS replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions. Linear interpolation is implemented in interp::interp(..., method="linear"), this corresponds to the call akima::interp(..., linear=TRUE) which is the default setting and covers most of akima::interp use cases in depending packages. A re-implementation of Akimas irregular grid spline interpolation (akima::interp(..., linear=FALSE)) is now also available via interp::interp(..., method="akima"). Estimators for partial derivatives are now also available in interp::locpoly(), these are a prerequisite for the spline interpolation. The basic part is a GPLed triangulation algorithm (sweep hull algorithm by David Sinclair) providing the starting point for the irregular grid interpolator. As side effect this algorithm is also used to provide replacements for almost all functions of the tripack package which also suffers from the same ACM license restrictions. All functions are designed to be backward compatible with their akima / tripack counterparts.

Maintained by Albrecht Gebhardt. Last updated 1 years ago.

fortran cpp

4.0 match 1 stars 9.06 score 228 scripts 286 dependents

gpiras

sphet:Estimation of Spatial Autoregressive Models with and without Heteroskedastic Innovations

Functions for fitting Cliff-Ord-type spatial autoregressive models with and without heteroskedastic innovations using Generalized Method of Moments estimation are provided. Some support is available for fitting spatial HAC models, and for fitting with non-spatial endogeneous variables using instrumental variables.

Maintained by Gianfranco Piras. Last updated 6 days ago.

4.9 match 8 stars 7.43 score 188 scripts 3 dependents

eitsupi

neopolars:R Bindings for the 'polars' Rust Library

Lightning-fast 'DataFrame' library written in 'Rust'. Convert R data to 'Polars' data and vice versa. Perform fast, lazy, larger-than-memory and optimized data queries. 'Polars' is interoperable with the package 'arrow', as both are based on the 'Apache Arrow' Columnar Format.

Maintained by Tatsuya Shima. Last updated 1 days ago.

rust cargo

7.5 match 40 stars 4.86 score 1 scripts

symbolixau

googleway:Accesses Google Maps APIs to Retrieve Data and Plot Maps

Provides a mechanism to plot a 'Google Map' from 'R' and overlay it with shapes and markers. Also provides access to 'Google Maps' APIs, including places, directions, roads, distances, geocoding, elevation and timezone.

Maintained by David Cooley. Last updated 6 months ago.

google-map google-maps google-maps-api google-maps-javascript-api spatial spatial-analysis

3.8 match 236 stars 9.67 score 536 scripts 2 dependents

bioc

HGC:A fast hierarchical graph-based clustering method

HGC (short for Hierarchical Graph-based Clustering) is an R package for conducting hierarchical clustering on large-scale single-cell RNA-seq (scRNA-seq) data. The key idea is to construct a dendrogram of cells on their shared nearest neighbor (SNN) graph. HGC provides functions for building graphs and for conducting hierarchical clustering on the graph. The users with old R version could visit https://github.com/XuegongLab/HGC/tree/HGC4oldRVersion to get HGC package built for R 3.6.

Maintained by XGlab. Last updated 5 months ago.

singlecell software clustering rnaseq graphandnetwork dnaseq cpp

7.5 match 4.70 score 25 scripts

jeffreyevans

spatialEco:Spatial Analysis and Modelling Utilities

Utilities to support spatial data manipulation, query, sampling and modelling in ecological applications. Functions include models for species population density, spatial smoothing, multivariate separability, point process model for creating pseudo- absences and sub-sampling, Quadrant-based sampling and analysis, auto-logistic modeling, sampling models, cluster optimization, statistical exploratory tools and raster-based metrics.

Maintained by Jeffrey S. Evans. Last updated 13 days ago.

biodiversity conservation ecology r-spatial raster spatial vector

3.7 match 110 stars 9.55 score 736 scripts 2 dependents

kharchenkolab

N2R:Fast and Scalable Approximate k-Nearest Neighbor Search Methods using 'N2' Library

Implements methods to perform fast approximate K-nearest neighbor search on input matrix. Algorithm based on the 'N2' implementation of an approximate nearest neighbor search using hierarchical Navigable Small World (NSW) graphs. The original algorithm is described in "Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs", Y. Malkov and D. Yashunin, <doi:10.1109/TPAMI.2018.2889473>, <arXiv:1603.09320>.

Maintained by Evan Biederstedt. Last updated 1 years ago.

cpp

6.9 match 10 stars 5.08 score 3 scripts 2 dependents

zarquon42b

Morpho:Calculations and Visualisations Related to Geometric Morphometrics

A toolset for Geometric Morphometrics and mesh processing. This includes (among other stuff) mesh deformations based on reference points, permutation tests, detection of outliers, processing of sliding semi-landmarks and semi-automated surface landmark placement.

Maintained by Stefan Schlager. Last updated 5 months ago.

openblas cpp openmp

3.5 match 51 stars 10.00 score 218 scripts 13 dependents

sfirke

janitor:Simple Tools for Examining and Cleaning Dirty Data

The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and explore duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness.

Maintained by Sam Firke. Last updated 3 months ago.

data-analysis data-cleaning data-science dirty-data excel pivot-tables spss tabulations tidyverse

1.8 match 1.4k stars 19.15 score 35k scripts 231 dependents

mlampros

OpenImageR:An Image Processing Toolkit

Incorporates functions for image preprocessing, filtering and image recognition. The package takes advantage of 'RcppArmadillo' to speed up computationally intensive functions. The histogram of oriented gradients descriptor is a modification of the 'findHOGFeatures' function of the 'SimpleCV' computer vision platform, the average_hash(), dhash() and phash() functions are based on the 'ImageHash' python library. The Gabor Feature Extraction functions are based on 'Matlab' code of the paper, "CloudID: Trustworthy cloud-based and cross-enterprise biometric identification" by M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, Expert Systems with Applications, vol. 42, no. 21, pp. 7905-7916, 2015, <doi:10.1016/j.eswa.2015.06.025>. The 'SLIC' and 'SLICO' superpixel algorithms were explained in detail in (i) "SLIC Superpixels Compared to State-of-the-art Superpixel Methods", Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, num. 11, p. 2274-2282, May 2012, <doi:10.1109/TPAMI.2012.120> and (ii) "SLIC Superpixels", Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, EPFL Technical Report no. 149300, June 2010.

Maintained by Lampros Mouselimis. Last updated 2 years ago.

filtering gabor-feature-extraction gabor-filters hog-features image image-hashing processing rcpparmadillo recognition slic slico superpixels openblas cpp openmp

3.5 match 60 stars 9.86 score 358 scripts 8 dependents

tidymodels

recipes:Preprocessing and Feature Engineering Steps for Modeling

A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.

Maintained by Max Kuhn. Last updated 6 days ago.

1.8 match 584 stars 18.71 score 7.2k scripts 380 dependents

symbolrush

osrmr:Wrapper for the 'OSRM' API

Wrapper around the 'Open Source Routing Machine (OSRM)' API <http://project-osrm.org/>. 'osrmr' works with API versions 4 and 5 and can handle servers that run locally as well as the 'OSRM' webserver.

Maintained by Adrian Staempfli. Last updated 4 years ago.

11.0 match 3.06 score 23 scripts

chrhennig

fpc:Flexible Procedures for Clustering

Various methods for clustering and cluster validation. Fixed point clustering. Linear regression clustering. Clustering by merging Gaussian mixture components. Symmetric and asymmetric discriminant projections for visualisation of the separation of groupings. Cluster validation statistics for distance based clustering including corrected Rand index. Standardisation of cluster validation statistics by random clusterings and comparison between many clustering methods and numbers of clusters based on this. Cluster-wise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength, Fang and Wang's bootstrap stability. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Variable-wise statistics for cluster interpretation. DBSCAN clustering. Interface functions for many clustering methods implemented in R, including estimating the number of clusters with kmeans, pam and clara. Modality diagnosis for Gaussian mixtures. For an overview see package?fpc.

Maintained by Christian Hennig. Last updated 6 months ago.

3.6 match 11 stars 9.25 score 2.6k scripts 70 dependents

mlr-org

mlr3extralearners:Extra Learners For mlr3

Extra learners for use in mlr3.

Maintained by Sebastian Fischer. Last updated 4 months ago.

machine-learning mlr3

3.6 match 94 stars 9.16 score 474 scripts

paobranco

UBL:An Implementation of Re-Sampling Approaches to Utility-Based Learning for Both Classification and Regression Tasks

Provides a set of functions that can be used to obtain better predictive performance on cost-sensitive and cost/benefits tasks (for both regression and classification). This includes re-sampling approaches that modify the original data set biasing it towards the user preferences.

Maintained by Paula Branco. Last updated 3 months ago.

fortran

5.2 match 33 stars 6.39 score 165 scripts 1 dependents

cran

MDSMap:High Density Genetic Linkage Mapping using Multidimensional Scaling

Estimate genetic linkage maps for markers on a single chromosome (or in a single linkage group) from pairwise recombination fractions or intermarker distances using weighted metric multidimensional scaling. The methods are suitable for autotetraploid as well as diploid populations. Options for assessing the fit to a known map are also provided. Methods are discussed in detail in Preedy and Hackett (2016) <doi:10.1007/s00122-016-2761-8>.

Maintained by Bram Boskamp. Last updated 7 years ago.

10.7 match 3.08 score 1 dependents

edzer

intervals:Tools for Working with Points and Intervals

Tools for working with and comparing sets of points and intervals.

Maintained by Edzer Pebesma. Last updated 7 months ago.

cpp

3.5 match 11 stars 9.40 score 122 scripts 90 dependents

bioc

Biobase:Biobase: Base functions for Bioconductor

Functions that are needed by many other packages or which replace R functions.

Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.

infrastructure bioconductor-package core-package

2.0 match 9 stars 16.45 score 6.6k scripts 1.8k dependents

kwstat

corrgram:Plot a Correlogram

Calculates correlation of variables and displays the results graphically. Included panel functions can display points, shading, ellipses, and correlation values with confidence intervals. See Friendly (2002) <doi:10.1198/000313002533>.

Maintained by Kevin Wright. Last updated 8 months ago.

3.0 match 18 stars 10.93 score 1.3k scripts 3 dependents

luukvdmeer

sfnetworks:Tidy Geospatial Networks

Provides a tidy approach to spatial network analysis, in the form of classes and functions that enable a seamless interaction between the network analysis package 'tidygraph' and the spatial analysis package 'sf'.

Maintained by Lucas van der Meer. Last updated 3 months ago.

geospatial-networks network-analysis rspatial simple-features spatial-analysis spatial-data-science spatial-networks tidygraph tidyverse

3.4 match 372 stars 9.63 score 332 scripts 6 dependents

tidymodels

parsnip:A Common API to Modeling and Analysis Functions

A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', 'H2O', etc).

Maintained by Max Kuhn. Last updated 4 days ago.

2.0 match 612 stars 16.37 score 3.4k scripts 69 dependents

jkrijthe

RSSL:Implementations of Semi-Supervised Learning Approaches for Classification

A collection of implementations of semi-supervised classifiers and methods to evaluate their performance. The package includes implementations of, among others, Implicitly Constrained Learning, Moment Constrained Learning, the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic Likelihood estimation, S4VM and WellSVM.

Maintained by Jesse Krijthe. Last updated 1 years ago.

openblas cpp

5.4 match 58 stars 6.05 score 128 scripts 1 dependents

besanson

FastKNN:Fast k Nearest Neighbor

This are different Functions related to the k Nearest Neighbo classifier. The distance matrix is an input making the computation faster and allowing other distances than euclidean.

Maintained by Gaston Besanson. Last updated 10 years ago.

8.2 match 3.97 score 62 scripts 1 dependents

kisungyou

Rdimtools:Dimension Reduction and Estimation Methods

We provide linear and nonlinear dimension reduction techniques. Intrinsic dimension estimation methods for exploratory analysis are also provided. For more details on the package, see the paper by You and Shung (2022) <doi:10.1016/j.simpa.2022.100414>.

Maintained by Kisung You. Last updated 2 years ago.

dimension-estimation dimension-reduction manifold-learning subspace-learning openblas cpp openmp

3.9 match 52 stars 8.37 score 186 scripts 8 dependents

alaninglis

vivid:Variable Importance and Variable Interaction Displays

A suite of plots for displaying variable importance and two-way variable interaction jointly. Can also display partial dependence plots laid out in a pairs plot or 'zenplots' style.

Maintained by Alan Inglis. Last updated 8 months ago.

4.4 match 21 stars 7.39 score 39 scripts

r-forge

Matrix:Sparse and Dense Matrix Classes and Methods

A rich hierarchy of sparse and dense matrix classes, including general, symmetric, triangular, and diagonal matrices with numeric, logical, or pattern entries. Efficient methods for operating on such matrices, often wrapping the 'BLAS', 'LAPACK', and 'SuiteSparse' libraries.

Maintained by Martin Maechler. Last updated 7 days ago.

openblas

1.9 match 1 stars 17.23 score 33k scripts 12k dependents

janusza

RoughSets:Data Analysis Using Rough Set and Fuzzy Rough Set Theories

Implementations of algorithms for data analysis based on the rough set theory (RST) and the fuzzy rough set theory (FRST). We not only provide implementations for the basic concepts of RST and FRST but also popular algorithms that derive from those theories. The methods included in the package can be divided into several categories based on their functionality: discretization, feature selection, instance selection, rule induction and classification based on nearest neighbors. RST was introduced by Zdzisław Pawlak in 1982 as a sophisticated mathematical tool to model and process imprecise or incomplete information. By using the indiscernibility relation for objects/instances, RST does not require additional parameters to analyze the data. FRST is an extension of RST. The FRST combines concepts of vagueness and indiscernibility that are expressed with fuzzy sets (as proposed by Zadeh, in 1965) and RST.

Maintained by Christoph Bergmeir. Last updated 5 years ago.

cpp

5.7 match 37 stars 5.61 score 185 scripts

dvrbts

labdsv:Ordination and Multivariate Analysis for Ecology

A variety of ordination and community analyses useful in analysis of data sets in community ecology. Includes many of the common ordination methods, with graphical routines to facilitate their interpretation, as well as several novel analyses.

Maintained by David W. Roberts. Last updated 2 years ago.

fortran

5.3 match 3 stars 6.08 score 452 scripts 13 dependents

computationalstylistics

stylo:Stylometric Multivariate Analyses

Supervised and unsupervised multivariate methods, supplemented by GUI and some visualizations, to perform various analyses in the field of computational stylistics, authorship attribution, etc. For further reference, see Eder et al. (2016), <https://journal.r-project.org/archive/2016/RJ-2016-007/index.html>. You are also encouraged to visit the Computational Stylistics Group's website <https://computationalstylistics.github.io/>, where a reasonable amount of information about the package and related projects are provided.

Maintained by Maciej Eder. Last updated 2 months ago.

3.8 match 187 stars 8.58 score 462 scripts

ropensci

fingertipsR:Fingertips Data for Public Health

Fingertips (<http://fingertips.phe.org.uk/>) contains data for many indicators of public health in England. The underlying data is now more easily accessible by making use of the API.

Maintained by Annabel Westermann. Last updated 1 years ago.

api-wrapper fingertips health open-data peer-reviewed public-health public-health-england

4.0 match 96 stars 7.89 score 268 scripts 1 dependents

jeremygelb

spNetwork:Spatial Analysis on Network

Perform spatial analysis on network. Implement several methods for spatial analysis on network: Network Kernel Density estimation, building of spatial matrices based on network distance ('listw' objects from 'spdep' package), K functions estimation for point pattern analysis on network, k nearest neighbours on network, reachable area calculation, and graph generation References: Okabe et al (2019) <doi:10.1080/13658810802475491>; Okabe et al (2012, ISBN:978-0470770818);Baddeley et al (2015, ISBN:9781482210200).

Maintained by Jeremy Gelb. Last updated 2 days ago.

kernel kernel-density-estimation network network-analysis spatial spatial-analysis spatial-data-analysis cpp

4.1 match 38 stars 7.69 score 52 scripts

elvanceyhan

nnspat:Nearest Neighbor Methods for Spatial Patterns

Contains the functions for testing the spatial patterns (of segregation, spatial symmetry, association, disease clustering, species correspondence and reflexivity) based on nearest neighbor relations, especially using contingency tables such as nearest neighbor contingency tables (Ceyhan (2010) <doi:10.1007/s10651-008-0104-x> and Ceyhan (2017) <doi:10.1016/j.jkss.2016.10.002> and references therein), nearest neighbor symmetry contingency tables (Ceyhan (2014) <doi:10.1155/2014/698296>), species correspondence contingency tables and reflexivity contingency tables (Ceyhan (2018) <doi:10.2436/20.8080.02.72>) for two (or higher) dimensional data. Also contains functions for generating patterns of segregation, association, uniformity in a multi-class setting (Ceyhan (2014) <doi:10.1007/s00477-013-0824-9>), and various non-random labeling patterns for disease clustering in two dimensional cases (Ceyhan (2014) <doi:10.1002/sim.6053>), and for visualization of all these patterns for the two dimensional data. The tests are usually (asymptotic) normal z-tests and chi-square tests.

Maintained by Elvan Ceyhan. Last updated 3 years ago.

10.9 match 2.90 score 16 scripts

bioc

RAIDS:Accurate Inference of Genetic Ancestry from Cancer Sequences

This package implements specialized algorithms that enable genetic ancestry inference from various cancer sequences sources (RNA, Exome and Whole-Genome sequences). This package also implements a simulation algorithm that generates synthetic cancer-derived data. This code and analysis pipeline was designed and developed for the following publication: Belleau, P et al. Genetic Ancestry Inference from Cancer-Derived Molecular Data across Genomic and Transcriptomic Platforms. Cancer Res 1 January 2023; 83 (1): 49–58.

Maintained by Pascal Belleau. Last updated 5 months ago.

genetics software sequencing wholegenome principalcomponent geneticvariability dimensionreduction biocviews ancestry cancer-genomics exome-sequencing genomics inference r-language rna-seq rna-sequencing whole-genome-sequencing

5.0 match 5 stars 6.23 score 19 scripts

franciscomartinezdelrio

tsfknn:Time Series Forecasting Using Nearest Neighbors

Allows forecasting time series using nearest neighbors regression Francisco Martinez, Maria P. Frias, Maria D. Perez-Godoy and Antonio J. Rivera (2019) <doi:10.1007/s10462-017-9593-z>. When the forecasting horizon is higher than 1, two multi-step ahead forecasting strategies can be used. The model built is autoregressive, that is, it is only based on the observations of the time series. The nearest neighbors used in a prediction can be consulted and plotted.

Maintained by Francisco Martinez. Last updated 1 years ago.

cpp

5.6 match 11 stars 5.54 score 63 scripts

animint

animint2:Animated Interactive Grammar of Graphics

Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.

Maintained by Toby Hocking. Last updated 27 days ago.

3.4 match 64 stars 8.87 score 173 scripts

core-bioinformatics

ClustAssess:Tools for Assessing Clustering

A set of tools for evaluating clustering robustness using proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014) <doi:10.1038/srep06207>), as well as similarity across methods and method stability using element-centric clustering comparison (Gates et al. (2019) <doi:10.1038/s41598-019-44892-y>). Additionally, this package enables stability-based parameter assessment for graph-based clustering pipelines typical in single-cell data analysis.

Maintained by Andi Munteanu. Last updated 1 months ago.

software singlecell rnaseq atacseq normalization preprocessing dimensionreduction visualization qualitycontrol clustering classification annotation geneexpression differentialexpression bioinformatics genomics machine-learning parameter-optimization robustness single-cell unsupervised-learning cpp

5.3 match 23 stars 5.70 score 18 scripts

rvalavi

blockCV:Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation

Creating spatially or environmentally separated folds for cross-validation to provide a robust error estimation in spatially structured environments; Investigating and visualising the effective range of spatial autocorrelation in continuous raster covariates and point samples to find an initial realistic distance band to separate training and testing datasets spatially described in Valavi, R. et al. (2019) <doi:10.1111/2041-210X.13107>.

Maintained by Roozbeh Valavi. Last updated 5 months ago.

cross-validation spatial spatial-cross-validation spatial-modelling species-distribution-modelling cpp

2.8 match 113 stars 10.49 score 302 scripts 3 dependents

mobiodiv

mobr:Measurement of Biodiversity

Functions for calculating metrics for the measurement biodiversity and its changes across scales, treatments, and gradients. The methods implemented in this package are described in: Chase, J.M., et al. (2018) <doi:10.1111/ele.13151>, McGlinn, D.J., et al. (2019) <doi:10.1111/2041-210X.13102>, McGlinn, D.J., et al. (2020) <doi:10.1101/851717>, and McGlinn, D.J., et al. (2023) <doi:10.1101/2023.09.19.558467>.

Maintained by Daniel McGlinn. Last updated 5 months ago.

biodiversity conservation ecology rarefaction species statistics

3.4 match 23 stars 8.59 score 93 scripts

bioc

smoppix:Analyze Single Molecule Spatial Omics Data Using the Probabilistic Index

Test for univariate and bivariate spatial patterns in spatial omics data with single-molecule resolution. The tests implemented allow for analysis of nested designs and are automatically calibrated to different biological specimens. Tests for aggregation, colocalization, gradients and vicinity to cell edge or centroid are provided.

Maintained by Stijn Hawinkel. Last updated 28 days ago.

transcriptomics spatial singlecell cpp

5.6 match 1 stars 5.18 score 4 scripts

liviobaetscher

ElevDistr:Calculate the Distance to the Nearest Local Treeline

A method to calculate the distance to the climatic tree line for large data sets of coordinates (World Geodetic System 1984) with geographical uncertainty. The default thresholds and the treeline definition is based on Paulsen and Körner (2014) <doi:10.1007/s00035-014-0124-0>, users are free to decide what climate layers they would like to use.

Maintained by Livio Bätscher. Last updated 5 months ago.

6.5 match 4.40 score 3 scripts

tkonopka

umap:Uniform Manifold Approximation and Projection

Uniform manifold approximation and projection is a technique for dimension reduction. The algorithm was described by McInnes and Healy (2018) in <arXiv:1802.03426>. This package provides an interface for two implementations. One is written from scratch, including components for nearest-neighbor search and for embedding. The second implementation is a wrapper for 'python' package 'umap-learn' (requires separate installation, see vignette for more details).

Maintained by Tomasz Konopka. Last updated 11 months ago.

dimensionality-reduction umap cpp

2.2 match 132 stars 12.74 score 3.6k scripts 43 dependents

ropensci

GSODR:Global Surface Summary of the Day ('GSOD') Weather Data Client

Provides automated downloading, parsing, cleaning, unit conversion and formatting of Global Surface Summary of the Day ('GSOD') weather data from the from the USA National Centers for Environmental Information ('NCEI'). Units are converted from from United States Customary System ('USCS') units to International System of Units ('SI'). Stations may be individually checked for number of missing days defined by the user, where stations with too many missing observations are omitted. Only stations with valid reported latitude and longitude values are permitted in the final data. Additional useful elements, saturation vapour pressure ('es'), actual vapour pressure ('ea') and relative humidity ('RH') are calculated from the original data using the improved August-Roche-Magnus approximation (Alduchov & Eskridge 1996) and included in the final data set. The resulting metadata include station identification information, country, state, latitude, longitude, elevation, weather observations and associated flags. For information on the 'GSOD' data from 'NCEI', please see the 'GSOD' 'readme.txt' file available from, <https://www1.ncdc.noaa.gov/pub/data/gsod/readme.txt>.

Maintained by Adam H. Sparks. Last updated 11 days ago.

us-ncei meteorological-data global-weather weather weather-data meteorology station-data surface-weather data-access us-ncdc daily-data daily-weather global-data gsod historical-data historical-weather ncdc ncei weather-information weather-stations

3.2 match 94 stars 8.70 score 116 scripts

mlr-org

mlr3spatiotempcv:Spatiotemporal Resampling Methods for 'mlr3'

Extends the mlr3 machine learning framework with spatio-temporal resampling methods to account for the presence of spatiotemporal autocorrelation (STAC) in predictor variables. STAC may cause highly biased performance estimates in cross-validation if ignored. A JSS article is available at <doi:10.18637/jss.v111.i07>.

Maintained by Patrick Schratz. Last updated 4 months ago.

cross-validation mlr3 resampling resampling-methods spatial temporal

3.4 match 50 stars 8.09 score 123 scripts

bioc

ELMER:Inferring Regulatory Element Landscapes and Transcription Factor Networks Using Cancer Methylomes

ELMER is designed to use DNA methylation and gene expression from a large number of samples to infere regulatory element landscape and transcription factor network in primary tissue.

Maintained by Tiago Chedraoui Silva. Last updated 5 months ago.

dnamethylation geneexpression motifannotation software generegulation transcription network

3.7 match 7.42 score 176 scripts

statistikat

VIM:Visualization and Imputation of Missing Values

New tools for the visualization of missing and/or imputed values are introduced, which can be used for exploring the data and the structure of the missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods may help to identify the mechanism generating the missing values and allows to explore the data including missing values. In addition, the quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot methods. A graphical user interface available in the separate package VIMGUI allows an easy handling of the implemented plot methods.

Maintained by Matthias Templ. Last updated 7 months ago.

hotdeck imputation-methods model-predictions visualization cpp

1.9 match 85 stars 14.44 score 2.6k scripts 19 dependents

ltorgo

DMwR2:Functions and Data for the Second Edition of "Data Mining with R"

Functions and data accompanying the second edition of the book "Data Mining with R, learning with case studies" by Luis Torgo, published by CRC Press.

Maintained by Luis Torgo. Last updated 8 years ago.

3.6 match 27 stars 7.46 score 380 scripts 2 dependents

bioc

Oscope:Oscope - A statistical pipeline for identifying oscillatory genes in unsynchronized single cell RNA-seq

Oscope is a statistical pipeline developed to identifying and recovering the base cycle profiles of oscillating genes in an unsynchronized single cell RNA-seq experiment. The Oscope pipeline includes three modules: a sine model module to search for candidate oscillator pairs; a K-medoids clustering module to cluster candidate oscillators into groups; and an extended nearest insertion module to recover the base cycle order for each oscillator group.

Maintained by Ning Leng. Last updated 5 months ago.

immunooncology statisticalmethod rnaseq sequencing geneexpression

5.5 match 4.92 score 14 scripts 1 dependents

momx

Momocs:Morphometrics using R

The goal of 'Momocs' is to provide a complete, convenient, reproducible and open-source toolkit for 2D morphometrics. It includes most common 2D morphometrics approaches on outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. It allows reproducible, complex morphometrics analyses and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.

Maintained by Vincent Bonhomme. Last updated 1 years ago.

morphometrics

3.6 match 51 stars 7.42 score 346 scripts

braverock

PerformanceAnalytics:Econometric Tools for Performance and Risk Analysis

Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.

Maintained by Brian G. Peterson. Last updated 3 months ago.

1.7 match 222 stars 15.93 score 4.8k scripts 20 dependents

bioc

GenomicFeatures:Query the gene models of a given organism/assembly

Extract the genomic locations of genes, transcripts, exons, introns, and CDS, for the gene models stored in a TxDb object. A TxDb object is a small database that contains the gene models of a given organism/assembly. Bioconductor provides a small collection of TxDb objects in the form of ready-to-install TxDb packages for the most commonly studied organisms. Additionally, the user can easily make a TxDb object (or package) for the organism/assembly of their choice by using the tools from the txdbmaker package.

Maintained by H. Pagès. Last updated 4 months ago.

genetics infrastructure annotation sequencing genomeannotation bioconductor-package core-package

1.8 match 26 stars 15.34 score 5.3k scripts 339 dependents

geodacenter

rgeoda:R Library for Spatial Data Analysis

Provides spatial data analysis functionalities including Exploratory Spatial Data Analysis, Spatial Cluster Detection and Clustering Analysis, Regionalization, etc. based on the C++ source code of 'GeoDa', which is an open-source software tool that serves as an introduction to spatial data analysis. The 'GeoDa' software and its documentation are available at <https://geodacenter.github.io>.

Maintained by Xun Li. Last updated 9 days ago.

dataanalysis geoda geospatial cpp

3.4 match 73 stars 7.85 score 179 scripts 1 dependents

boopsboops

spider:Species Identity and Evolution in R

Analysis of species limits and DNA barcoding data. Included are functions for generating important summary statistics from DNA barcode data, assessing specimen identification efficacy, testing and optimizing divergence threshold limits, assessment of diagnostic nucleotides, and calculation of the probability of reciprocal monophyly. Additionally, a sliding window function offers opportunities to analyse information across a gene, often used for marker design in degraded DNA studies. Further information on the package has been published in Brown et al (2012) <doi:10.1111/j.1755-0998.2011.03108.x>.

Maintained by Rupert A. Collins. Last updated 6 years ago.

dna-barcode edna evolution species-delimitation species-identity

5.1 match 2 stars 5.20 score 66 scripts 1 dependents

rcurtin

mlpack:'Rcpp' Integration for the 'mlpack' Library

A fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. See also Curtin et al. (2023) <doi:10.21105/joss.05026>.

Maintained by Ryan Curtin. Last updated 3 months ago.

openblas cpp openmp

7.2 match 3.71 score 20 scripts 8 dependents

bnprks

BPCells:Single Cell Counts Matrices to PCA

> Efficient operations for single cell ATAC-seq fragments and RNA counts matrices. Interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.

Maintained by Benjamin Parks. Last updated 1 months ago.

zlib hdf5 cpp

3.5 match 184 stars 7.48 score 172 scripts

pgiraudoux

pgirmess:Spatial Analysis and Data Mining for Field Ecologists

Set of tools for reading, writing and transforming spatial and seasonal data, model selection and specific statistical tests for ecologists. It includes functions to interpolate regular positions of points between landmarks, to discretize polylines into regular point positions, link distant observations to points and convert a bounding box in a spatial object. It also provides miscellaneous functions for field ecologists such as spatial statistics and inference on diversity indexes, writing data.frame with Chinese characters.

Maintained by Patrick Giraudoux. Last updated 1 years ago.

3.6 match 5 stars 7.32 score 422 scripts 2 dependents

bbbruce

nncc:Nearest Neighbors Matching of Case-Control Data

Provides nearest-neighbors matching and analysis of case-control data. Cui, Z., Marder, E. P., Click, E. S., Hoekstra, R. M., & Bruce, B. B. (2022) <doi:10.1097/EDE.0000000000001504>.

Maintained by Beau Bruce. Last updated 1 years ago.

9.7 match 2.70 score 3 scripts

maximilianaxer

quaxnat:Estimation of Natural Regeneration Potential

Functions for estimating the potential dispersal of tree species using regeneration densities and dispersal distances to nearest seed trees. A quantile regression is implemented to determine the dispersal potential. Spatial prediction can be used to identify natural regeneration potential for forest restoration as described in Axer et al (2021) <doi:10.1016/j.foreco.2020.118802>.

Maintained by Maximilian Axer. Last updated 5 months ago.

7.3 match 1 stars 3.54 score 2 scripts

juanv66x

viralx:Explainers for Regression Models in HIV Research

A dedicated viral-explainer model tool designed to empower researchers in the field of HIV research, particularly in viral load and CD4 (Cluster of Differentiation 4) lymphocytes regression modeling. Drawing inspiration from the 'tidymodels' framework for rigorous model building of Max Kuhn and Hadley Wickham (2020) <https://www.tidymodels.org>, and the 'DALEXtra' tool for explainability by Przemyslaw Biecek (2020) <doi:10.48550/arXiv.2009.13248>. It aims to facilitate interpretable and reproducible research in biostatistics and computational biology for the benefit of understanding HIV dynamics.

Maintained by Juan Pablo Acuña González. Last updated 4 months ago.

8.6 match 3.00 score 1 scripts

certara

tidyvpc:VPC Percentiles and Prediction Intervals

Perform a Visual Predictive Check (VPC), while accounting for stratification, censoring, and prediction correction. Using piping from 'magrittr', the intuitive syntax gives users a flexible and powerful method to generate VPCs using both traditional binning and a new binless approach Jamsen et al. (2018) <doi:10.1002/psp4.12319> with Additive Quantile Regression (AQR) and Locally Estimated Scatterplot Smoothing (LOESS) prediction correction.

Maintained by James Craig. Last updated 4 months ago.

3.3 match 11 stars 7.81 score 47 scripts 1 dependents

cran

e1071:Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien

Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, generalized k-nearest neighbour ...

Maintained by David Meyer. Last updated 6 months ago.

cpp

2.3 match 29 stars 11.26 score 2.0k dependents

joeguinness

GpGp:Fast Gaussian Process Computation Using Vecchia's Approximation

Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) <http://www.jstor.org/stable/2345768>, and the reordering and grouping methods are from Guinness (2018) <doi:10.1080/00401706.2018.1437476>. Model fitting employs a Fisher scoring algorithm described in Guinness (2019) <doi:10.48550/arXiv.1905.08374>.

Maintained by Joseph Guinness. Last updated 5 months ago.

openblas cpp openmp

4.1 match 10 stars 6.16 score 160 scripts 6 dependents

bioc

SPIAT:Spatial Image Analysis of Tissues

SPIAT (**Sp**atial **I**mage **A**nalysis of **T**issues) is an R package with a suite of data processing, quality control, visualization and data analysis tools. SPIAT is compatible with data generated from single-cell spatial proteomics platforms (e.g. OPAL, CODEX, MIBI, cellprofiler). SPIAT reads spatial data in the form of X and Y coordinates of cells, marker intensities and cell phenotypes. SPIAT includes six analysis modules that allow visualization, calculation of cell colocalization, categorization of the immune microenvironment relative to tumor areas, analysis of cellular neighborhoods, and the quantification of spatial heterogeneity, providing a comprehensive toolkit for spatial data analysis.

Maintained by Yuzhou Feng. Last updated 14 hours ago.

biomedicalinformatics cellbiology spatial clustering dataimport immunooncology qualitycontrol singlecell software visualization

2.9 match 22 stars 8.59 score 69 scripts

promerpr

scanstatistics:Space-Time Anomaly Detection using Scan Statistics

Detection of anomalous space-time clusters using the scan statistics methodology. Focuses on prospective surveillance of data streams, scanning for clusters with ongoing anomalies. Hypothesis testing is made possible by Monte Carlo simulation. Allévius (2018) <doi:10.21105/joss.00515>.

Maintained by Paul Romer Present. Last updated 2 years ago.

cpp

5.1 match 1 stars 4.81 score 43 scripts

bioc

scran:Methods for Single-Cell RNA-Seq Data Analysis

Implements miscellaneous functions for interpretation of single-cell RNA-seq data. Methods are provided for assignment of cell cycle phase, detection of highly variable and significantly correlated genes, identification of marker genes, and other common tasks in routine single-cell analysis workflows.

Maintained by Aaron Lun. Last updated 5 months ago.

immunooncology normalization sequencing rnaseq software geneexpression transcriptomics singlecell clustering bioconductor-package human-cell-atlas single-cell-rna-seq openblas cpp

1.9 match 41 stars 13.14 score 7.6k scripts 36 dependents

dandls

counterfactuals:Counterfactual Explanations

Modular and unified R6-based interface for counterfactual explanation methods. The following methods are currently implemented: Burghmans et al. (2022) <doi:10.48550/arXiv.2104.07411>, Dandl et al. (2020) <doi:10.1007/978-3-030-58112-1_31> and Wexler et al. (2019) <doi:10.1109/TVCG.2019.2934619>. Optional extensions allow these methods to be applied to a variety of models and use cases. Once generated, the counterfactuals can be analyzed and visualized by provided functionalities.

Maintained by Susanne Dandl. Last updated 5 months ago.

interpretable-machine-learning local-explanations model-agnostic-explanations

3.4 match 21 stars 7.14 score 22 scripts

chrhennig

prabclus:Functions for Clustering and Testing of Presence-Absence, Abundance and Multilocus Genetic Data

Distance-based parametric bootstrap tests for clustering with spatial neighborhood information. Some distance measures, Clustering of presence-absence, abundance and multilocus genetic data for species delimitation, nearest neighbor based noise detection. Genetic distances between communities. Tests whether various distance-based regressions are equal. Try package?prabclus for on overview.

Maintained by Christian Hennig. Last updated 6 months ago.

4.1 match 1 stars 5.99 score 90 scripts 71 dependents

bioc

miloR:Differential neighbourhood abundance testing on a graph

Milo performs single-cell differential abundance testing. Cell states are modelled as representative neighbourhoods on a nearest neighbour graph. Hypothesis testing is performed using either a negative bionomial generalized linear model or negative binomial generalized linear mixed model.

Maintained by Mike Morgan. Last updated 5 months ago.

singlecell multiplecomparison functionalgenomics software openblas cpp openmp

2.3 match 357 stars 10.49 score 340 scripts 1 dependents

ms609

TreeDist:Calculate and Map Distances Between Phylogenetic Trees

Implements measures of tree similarity, including information-based generalized Robinson-Foulds distances (Phylogenetic Information Distance, Clustering Information Distance, Matching Split Information Distance; Smith 2020) <doi:10.1093/bioinformatics/btaa614>; Jaccard-Robinson-Foulds distances (Bocker et al. 2013) <doi:10.1007/978-3-642-40453-5_13>, including the Nye et al. (2006) metric <doi:10.1093/bioinformatics/bti720>; the Matching Split Distance (Bogdanowicz & Giaro 2012) <doi:10.1109/TCBB.2011.48>; Maximum Agreement Subtree distances; the Kendall-Colijn (2016) distance <doi:10.1093/molbev/msw124>, and the Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. (1996) <doi:10.1007/3-540-61332-3_168>. Includes tools for visualizing mappings of tree space (Smith 2022) <doi:10.1093/sysbio/syab100>, for identifying islands of trees (Silva and Wilkinson 2021) <doi:10.1093/sysbio/syab015>, for calculating the median of sets of trees, and for computing the information content of trees and splits.

Maintained by Martin R. Smith. Last updated 1 months ago.

phylogenetics tree-distance phylogenetic-trees tree-distances trees cpp

2.3 match 32 stars 10.32 score 97 scripts 5 dependents

bioc

bumphunter:Bump Hunter

Tools for finding bumps in genomic data

Maintained by Tamilselvi Guharaj. Last updated 5 months ago.

dnamethylation epigenetics infrastructure multiplecomparison immunooncology

2.0 match 16 stars 11.74 score 210 scripts 42 dependents

swarm-lab

swaRm:Processing Collective Movement Data

Function library for processing collective movement data (e.g. fish schools, ungulate herds, baboon troops) collected from GPS trackers or computer vision tracking software.

Maintained by Simon Garnier. Last updated 1 years ago.

animal-behavior animal-behaviour collective-behavior collective-behaviour

4.3 match 21 stars 5.50 score 8 scripts 1 dependents

idem-lab

sdmtools:Utility tools for Species Distribution Modelling

What the package does (one paragraph).

Maintained by Gerry Ryan. Last updated 3 months ago.

3.8 match 9 stars 6.13 score 674 scripts

suyusung

arm:Data Analysis Using Regression and Multilevel/Hierarchical Models

Functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.

Maintained by Yu-Sung Su. Last updated 5 months ago.

1.9 match 25 stars 12.38 score 3.3k scripts 89 dependents

reddertar

smotefamily:A Collection of Oversampling Techniques for Class Imbalance Problem Based on SMOTE

A collection of various oversampling techniques developed from SMOTE is provided. SMOTE is a oversampling technique which synthesizes a new minority instance between a pair of one minority instance and one of its K nearest neighbor. Other techniques adopt this concept with other criteria in order to generate balanced dataset for class imbalance problem.

Maintained by Wacharasak Siriseriwan. Last updated 1 years ago.

3.9 match 2 stars 5.93 score 512 scripts 8 dependents

tagteam

prodlim:Product-Limit Estimation for Censored Event History Analysis

Fast and user friendly implementation of nonparametric estimators for censored event history (survival) analysis. Kaplan-Meier and Aalen-Johansen method.

Maintained by Thomas A. Gerds. Last updated 12 days ago.

1.9 match 7 stars 12.18 score 1000 scripts 462 dependents

insightrx

clinPK:Clinical Pharmacokinetics Toolkit

Provides equations commonly used in clinical pharmacokinetics and clinical pharmacology, such as equations for dose individualization, compartmental pharmacokinetics, drug exposure, anthropomorphic calculations, clinical chemistry, and conversion of common clinical parameters. Where possible and relevant, it provides multiple published and peer-reviewed equations within the respective R function.

Maintained by Ron Keizer. Last updated 2 months ago.

clinical-research pharmacokinetics

3.4 match 30 stars 6.72 score 55 scripts

hwborchers

pracma:Practical Numerical Math Functions

Provides a large number of functions from numerical analysis and linear algebra, numerical optimization, differential equations, time series, plus some well-known special mathematical functions. Uses 'MATLAB' function names where appropriate to simplify porting.

Maintained by Hans W. Borchers. Last updated 1 years ago.

1.8 match 29 stars 12.34 score 6.6k scripts 931 dependents

ropensci

stplanr:Sustainable Transport Planning

Tools for transport planning with an emphasis on spatial transport data and non-motorized modes. The package was originally developed to support the 'Propensity to Cycle Tool', a publicly available strategic cycle network planning tool (Lovelace et al. 2017) <doi:10.5198/jtlu.2016.862>, but has since been extended to support public transport routing and accessibility analysis (Moreno-Monroy et al. 2017) <doi:10.1016/j.jtrangeo.2017.08.012> and routing with locally hosted routing engines such as 'OSRM' (Lowans et al. 2023) <doi:10.1016/j.enconman.2023.117337>. The main functions are for creating and manipulating geographic "desire lines" from origin-destination (OD) data (building on the 'od' package); calculating routes on the transport network locally and via interfaces to routing services such as <https://cyclestreets.net/> (Desjardins et al. 2021) <doi:10.1007/s11116-021-10197-1>; and calculating route segment attributes such as bearing. The package implements the 'travel flow aggregration' method described in Morgan and Lovelace (2020) <doi:10.1177/2399808320942779> and the 'OD jittering' method described in Lovelace et al. (2022) <doi:10.32866/001c.33873>. Further information on the package's aim and scope can be found in the vignettes and in a paper in the R Journal (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053>, and in a paper outlining the landscape of open source software for geographic methods in transport planning (Lovelace, 2021) <doi:10.1007/s10109-020-00342-2>.

Maintained by Robin Lovelace. Last updated 7 months ago.

cycle cycling desire-lines origin-destination peer-reviewed pubic-transport route-network routes routing spatial transport transport-planning transportation walking

1.8 match 427 stars 12.31 score 684 scripts 3 dependents

rfastofficial

Rfast:A Collection of Efficient and Extremely Fast R Functions

A collection of fast (utility) functions for data analysis. Column and row wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions. References: a) Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>. b) Tsagris M. and Papadakis M. (2018). Forward regression in R: from the extreme slow to the extreme fast. Journal of Data Science, 16(4): 771--780. <doi:10.6339/JDS.201810_16(4).00006>. c) Chatzipantsiou C., Dimitriadis M., Papadakis M. and Tsagris M. (2020). Extremely Efficient Permutation and Bootstrap Hypothesis Tests Using Hypothesis Tests Using R. Journal of Modern Applied Statistical Methods, 18(2), eP2898. <doi:10.48550/arXiv.1806.10947>. d) Tsagris M., Papadakis M., Alenazi A. and Alzeley O. (2024). Computationally Efficient Outlier Detection for High-Dimensional Data Using the MDP Algorithm. Computation, 12(9): 185. <doi:10.3390/computation12090185>. e) Tsagris M. and Papadakis M. (2025). Fast and light-weight energy statistics using the R package Rfast. <doi:10.48550/arXiv.2501.02849>.

Maintained by Manos Papadakis. Last updated 17 days ago.

openblas cpp openmp

1.8 match 147 stars 12.54 score 1.2k scripts 166 dependents

yihui

animation:A Gallery of Animations in Statistics and Utilities to Create Animations

Provides functions for animations in statistics, covering topics in probability theory, mathematical statistics, multivariate statistics, non-parametric statistics, sampling survey, linear models, time series, computational statistics, data mining and machine learning. These functions may be helpful in teaching statistics and data analysis. Also provided in this package are a series of functions to save animations to various formats, e.g. Flash, 'GIF', HTML pages, 'PDF' and videos. 'PDF' animations can be inserted into 'Sweave' / 'knitr' easily.

Maintained by Yihui Xie. Last updated 2 years ago.

animation statistical-computing statistical-graphics statistics

1.8 match 208 stars 12.08 score 2.5k scripts 29 dependents

bioc

hiAnnotator:Functions for annotating GRanges objects

hiAnnotator contains set of functions which allow users to annotate a GRanges object with custom set of annotations. The basic philosophy of this package is to take two GRanges objects (query & subject) with common set of seqnames (i.e. chromosomes) and return associated annotation per seqnames and rows from the query matching seqnames and rows from the subject (i.e. genes or cpg islands). The package comes with three types of annotation functions which calculates if a position from query is: within a feature, near a feature, or count features in defined window sizes. Moreover, each function is equipped with parallel backend to utilize the foreach package. In addition, the package is equipped with wrapper functions, which finds appropriate columns needed to make a GRanges object from a common data frame.

Maintained by Nirav V Malani. Last updated 5 months ago.

software annotation

4.7 match 4.65 score 15 scripts 1 dependents

kharchenkolab

sccore:Core Utilities for Single-Cell RNA-Seq

Core utilities for single-cell RNA-seq data analysis. Contained within are utility functions for working with differential expression (DE) matrices and count matrices, a collection of functions for manipulating and plotting data via 'ggplot2', and functions to work with cell graphs and cell embeddings. Graph-based methods include embedding kNN cell graphs into a UMAP <doi:10.21105/joss.00861>, collapsing vertices of each cluster in the graph, and propagating graph labels.

Maintained by Evan Biederstedt. Last updated 1 years ago.

cpp

3.4 match 12 stars 6.44 score 36 scripts 9 dependents

jfrench

smacpod:Statistical Methods for the Analysis of Case-Control Point Data

Statistical methods for analyzing case-control point data. Methods include the ratio of kernel densities, the difference in K Functions, the spatial scan statistic, and q nearest neighbors of cases.

Maintained by Joshua French. Last updated 5 months ago.

5.7 match 3.69 score 49 scripts

jlmelville

uwot:The Uniform Manifold Approximation and Projection (UMAP) Method for Dimensionality Reduction

An implementation of the Uniform Manifold Approximation and Projection dimensionality reduction by McInnes et al. (2018) <doi:10.48550/arXiv.1802.03426>. It also provides means to transform new data and to carry out supervised dimensionality reduction. An implementation of the related LargeVis method of Tang et al. (2016) <doi:10.48550/arXiv.1602.00370> is also provided. This is a complete re-implementation in R (and C++, via the 'Rcpp' package): no Python installation is required. See the uwot website (<https://github.com/jlmelville/uwot>) for more documentation and examples.

Maintained by James Melville. Last updated 20 days ago.

dimensionality-reduction umap cpp

1.3 match 328 stars 15.74 score 2.0k scripts 140 dependents

reinhardfurrer

spam:SPArse Matrix

Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>; see 'citation("spam")' for details.

Maintained by Reinhard Furrer. Last updated 2 months ago.

fortran openblas cpp

2.3 match 1 stars 9.26 score 420 scripts 433 dependents

dmurdoch

orientlib:Support for Orientation Data

Representations, conversions and display of orientation SO(3) data. See the orientlib help topic for details.

Maintained by Duncan Murdoch. Last updated 2 years ago.

6.3 match 1 stars 3.29 score 20 scripts

bioc

StabMap:Stabilised mosaic single cell data integration using unshared features

StabMap performs single cell mosaic data integration by first building a mosaic data topology, and for each reference dataset, traverses the topology to project and predict data onto a common embedding. Mosaic data should be provided in a list format, with all relevant features included in the data matrices within each list object. The output of stabMap is a joint low-dimensional embedding taking into account all available relevant features. Expression imputation can also be performed using the StabMap embedding and any of the original data matrices for given reference and query cell lists.

Maintained by Shila Ghazanfar. Last updated 5 months ago.

singlecell dimensionreduction software

3.5 match 5.95 score 60 scripts

murrayefford

secr:Spatially Explicit Capture-Recapture

Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

Maintained by Murray Efford. Last updated 3 days ago.

cpp

2.0 match 3 stars 10.18 score 410 scripts 5 dependents

dmurdoch

plotrix:Various Plotting Functions

Lots of plots, various labeling, axis and color scaling functions. The author/maintainer died in September 2023.

Maintained by Duncan Murdoch. Last updated 1 years ago.

1.8 match 5 stars 11.31 score 9.2k scripts 361 dependents

r-forge

deSolve:Solvers for Initial Value Problems of Differential Equations ('ODE', 'DAE', 'DDE')

Functions that solve initial value problems of a system of first-order ordinary differential equations ('ODE'), of partial differential equations ('PDE'), of differential algebraic equations ('DAE'), and of delay differential equations. The functions provide an interface to the FORTRAN functions 'lsoda', 'lsodar', 'lsode', 'lsodes' of the 'ODEPACK' collection, to the FORTRAN functions 'dvode', 'zvode' and 'daspk' and a C-implementation of solvers of the 'Runge-Kutta' family with fixed or variable time steps. The package contains routines designed for solving 'ODEs' resulting from 1-D, 2-D and 3-D partial differential equations ('PDE') that have been converted to 'ODEs' by numerical differencing.

Maintained by Thomas Petzoldt. Last updated 1 years ago.

fortran openblas

1.7 match 12.33 score 8.0k scripts 427 dependents

squidlobster

castor:Efficient Phylogenetics on Large Trees

Efficient phylogenetic analyses on massive phylogenies comprising up to millions of tips. Functions include pruning, rerooting, calculation of most-recent common ancestors, calculating distances from the tree root and calculating pairwise distances. Calculation of phylogenetic signal and mean trait depth (trait conservatism), ancestral state reconstruction and hidden character prediction of discrete characters, simulating and fitting models of trait evolution, fitting and simulating diversification models, dating trees, comparing trees, and reading/writing trees in Newick format. Citation: Louca, Stilianos and Doebeli, Michael (2017) <doi:10.1093/bioinformatics/btx701>.

Maintained by Stilianos Louca. Last updated 4 months ago.

cpp

3.5 match 2 stars 5.75 score 450 scripts 9 dependents

cogbrainhealthlab

VertexWiseR:Simplified Vertex-Wise Analyses of Whole-Brain and Hippocampal Surface

Provides functions to run statistical analyses on surface-based neuroimaging data, computing measures including cortical thickness and surface area of the whole-brain and of the hippocampi. It can make use of 'FreeSurfer', 'fMRIprep' and 'HCP' preprocessed datasets and 'HippUnfold' hippocampal segmentation outputs for a given sample by restructuring the data values into a single file. The single file can then be used by the package for analyses independently from its base dataset and without need for its access.

Maintained by Charly Billaud. Last updated 7 days ago.

3.4 match 1 stars 5.84 score 12 scripts

bioc

scrapper:Bindings to C++ Libraries for Single-Cell Analysis

Implements R bindings to C++ code for analyzing single-cell (expression) data, mostly from various libscran libraries. Each function performs an individual step in the single-cell analysis workflow, ranging from quality control to clustering and marker detection. It is mostly intended for other Bioconductor package developers to build more user-friendly end-to-end workflows.

Maintained by Aaron Lun. Last updated 5 days ago.

normalization rnaseq software geneexpression transcriptomics singlecell batcheffect qualitycontrol differentialexpression featureextraction principalcomponent clustering openblas cpp

3.6 match 5.55 score 32 scripts

marinapapa

swaRmverse:Swarm Space Creation

Provides a pipeline for the comparative analysis of collective movement data (e.g. fish schools, bird flocks, baboon troops) by processing 2-dimensional positional data (x,y,t) from GPS trackers or computer vision tracking systems, discretizing events of collective motion, calculating a set of established metrics that characterize each event, and placing the events in a multi-dimensional swarm space constructed from these metrics. The swarm space concept, the metrics and data sets included are described in: Papadopoulou Marina, Furtbauer Ines, O'Bryan Lisa R., Garnier Simon, Georgopoulou Dimitra G., Bracken Anna M., Christensen Charlotte and King Andrew J. (2023) <doi:10.1098/rstb.2022.0068>.

Maintained by Marina Papadopoulou. Last updated 5 months ago.

3.9 match 2 stars 5.13 score 15 scripts

r-forge

wordspace:Distributional Semantic Models in R

An interactive laboratory for research on distributional semantic models ('DSM', see <https://en.wikipedia.org/wiki/Distributional_semantics> for more information).

Maintained by Stephanie Evert. Last updated 3 months ago.

cpp openmp

4.0 match 4.95 score 150 scripts 2 dependents

ropensci

drake:A Pipeline Toolkit for Reproducible Computation at Scale

A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://docs.ropensci.org/drake/> and the online manual <https://books.ropensci.org/drake/>.

Maintained by William Michael Landau. Last updated 3 months ago.

data-science drake high-performance-computing makefile peer-reviewed pipeline reproducibility reproducible-research ropensci workflow

1.7 match 1.3k stars 11.49 score 1.7k scripts 1 dependents

mmaechler

sfsmisc:Utilities from 'Seminar fuer Statistik' ETH Zurich

Useful utilities ['goodies'] from Seminar fuer Statistik ETH Zurich, some of which were ported from S-plus in the 1990s. For graphics, have pretty (Log-scale) axes eaxis(), an enhanced Tukey-Anscombe plot, combining histogram and boxplot, 2d-residual plots, a 'tachoPlot()', pretty arrows, etc. For robustness, have a robust F test and robust range(). For system support, notably on Linux, provides 'Sys.*()' functions with more access to system and CPU information. Finally, miscellaneous utilities such as simple efficient prime numbers, integer codes, Duplicated(), toLatex.numeric() and is.whole().

Maintained by Martin Maechler. Last updated 5 months ago.

1.8 match 11 stars 10.87 score 566 scripts 119 dependents

cmlmagneville

mFD:Compute and Illustrate the Multiple Facets of Functional Diversity

Computing functional traits-based distances between pairs of species for species gathered in assemblages allowing to build several functional spaces. The package allows to compute functional diversity indices assessing the distribution of species (and of their dominance) in a given functional space for each assemblage and the overlap between assemblages in a given functional space, see: Chao et al. (2018) <doi:10.1002/ecm.1343>, Maire et al. (2015) <doi:10.1111/geb.12299>, Mouillot et al. (2013) <doi:10.1016/j.tree.2012.10.004>, Mouillot et al. (2014) <doi:10.1073/pnas.1317625111>, Ricotta and Szeidl (2009) <doi:10.1016/j.tpb.2009.10.001>. Graphical outputs are included. Visit the 'mFD' website for more information, documentation and examples.

Maintained by Camille Magneville. Last updated 3 months ago.

2.7 match 26 stars 7.35 score 61 scripts

spatstat

spatstat.random:Random Generation Functionality for the 'spatstat' Family

Functionality for random generation of spatial data in the 'spatstat' family of packages. Generates random spatial patterns of points according to many simple rules (complete spatial randomness, Poisson, binomial, random grid, systematic, cell), randomised alteration of patterns (thinning, random shift, jittering), simulated realisations of random point processes including simple sequential inhibition, Matern inhibition models, Neyman-Scott cluster processes (using direct, Brix-Kendall, or hybrid algorithms), log-Gaussian Cox processes, product shot noise cluster processes and Gibbs point processes (using Metropolis-Hastings birth-death-shift algorithm, alternating Gibbs sampler, or coupling-from-the-past perfect simulation). Also generates random spatial patterns of line segments, random tessellations, and random images (random noise, random mosaics). Excludes random generation on a linear network, which is covered by the separate package 'spatstat.linnet'.

Maintained by Adrian Baddeley. Last updated 2 days ago.

point-processes random-generation simulation spatial-sampling spatial-simulation cpp

1.8 match 5 stars 10.82 score 84 scripts 175 dependents

yuelyu21

SCIntRuler:Guiding the Integration of Multiple Single-Cell RNA-Seq Datasets

The accumulation of single-cell RNA-seq (scRNA-seq) studies highlights the potential benefits of integrating multiple datasets. By augmenting sample sizes and enhancing analytical robustness, integration can lead to more insightful biological conclusions. However, challenges arise due to the inherent diversity and batch discrepancies within and across studies. SCIntRuler, a novel R package, addresses these challenges by guiding the integration of multiple scRNA-seq datasets.

Maintained by Yue Lyu. Last updated 5 months ago.

sequencing geneticvariability singlecell cpp

4.0 match 2 stars 4.85 score 3 scripts

apache

apache.sedona:R Interface for Apache Sedona

R interface for 'Apache Sedona' based on 'sparklyr' (<https://sedona.apache.org>).

Maintained by Apache Sedona. Last updated 14 hours ago.

cluster-computing geospatial java python scala spatial-analysis spatial-query spatial-sql

1.8 match 2.0k stars 10.72 score 105 scripts

tnagler

kdecopula:Kernel Smoothing for Bivariate Copula Densities

Provides fast implementations of kernel smoothing techniques for bivariate copula densities, in particular density estimation and resampling.

Maintained by Thomas Nagler. Last updated 7 years ago.

openblas cpp

3.4 match 8 stars 5.63 score 31 scripts 1 dependents

bioc

genomation:Summary, annotation and visualization of genomic data

A package for summary and annotation of genomic intervals. Users can visualize and quantify genomic intervals over pre-defined functional regions, such as promoters, exons, introns, etc. The genomic intervals represent regions with a defined chromosome position, which may be associated with a score, such as aligned reads from HT-seq experiments, TF binding sites, methylation scores, etc. The package can use any tabular genomic feature data as long as it has minimal information on the locations of genomic intervals. In addition, It can use BAM or BigWig files as input.

Maintained by Altuna Akalin. Last updated 5 months ago.

annotation sequencing visualization cpgisland cpp

1.7 match 75 stars 11.09 score 738 scripts 5 dependents

bioc

msImpute:Imputation of label-free mass spectrometry peptides

MsImpute is a package for imputation of peptide intensity in proteomics experiments. It additionally contains tools for MAR/MNAR diagnosis and assessment of distortions to the probability distribution of the data post imputation. The missing values are imputed by low-rank approximation of the underlying data matrix if they are MAR (method = "v2"), by Barycenter approach if missingness is MNAR ("v2-mnar"), or by Peptide Identity Propagation (PIP).

Maintained by Soroor Hediyeh-zadeh. Last updated 5 months ago.

massspectrometry proteomics software label-free-proteomics low-rank-approximation

3.7 match 14 stars 5.15 score 7 scripts

natesmith07

truh:An R package for Two-Sample Nonparametric Testing Under Heterogeneity

This R package implements the TRUH test statistic for two sample testing under heterogeneity. TRUH incorporates the underlying heterogeneity and imbalance in the samples, and provides a conservative test for the composite null hypothesis that the two samples arise from the same mixture distribution but may differ with respect to the mixing weights. See Trambak Banerjee, Bhaswar B. Bhattacharya, Gourab Mukherjee Ann. Appl. Stat. 14(4): 1777-1805 (December 2020). <DOI: 10.1214/20-AOAS1362> for more details.

Maintained by Nathan Smith. Last updated 4 years ago.

5.1 match 3.70 score 6 scripts

mnwright

bnnSurvival:Bagged k-Nearest Neighbors Survival Prediction

Implements a bootstrap aggregated (bagged) version of the k-nearest neighbors survival probability prediction method (Lowsky et al. 2013). In addition to the bootstrapping of training samples, the features can be subsampled in each baselearner to break the correlation between them. The Rcpp package is used to speed up the computation.

Maintained by Marvin N. Wright. Last updated 8 years ago.

cpp

6.8 match 1 stars 2.70 score 5 scripts

emilhvitfeldt

fastTextR:An Interface to the 'fastText' Library

An interface to the 'fastText' library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. An example how to use 'fastTextR' can be found in the 'README' file.

Maintained by Emil Hvitfeldt. Last updated 1 years ago.

cpp

3.3 match 4 stars 5.50 score 44 scripts 2 dependents

nicholasjcooper

NCmisc:Miscellaneous Functions for Creating Adaptive Functions and Scripts

A set of handy functions. Includes a versatile one line progress bar, one line function timer with detailed output, time delay function, text histogram, object preview, CRAN package search, simpler package installer, Linux command install check, a flexible Mode function, top function, simulation of correlated data, and more.

Maintained by Nicholas Cooper. Last updated 2 years ago.

4.8 match 3.86 score 172 scripts 5 dependents

jcatwood

nntmvn:Draw Samples of Truncated Multivariate Normal Distributions

Draw samples from truncated multivariate normal distribution using the sequential nearest neighbor (SNN) method introduced in "Scalable Sampling of Truncated Multivariate Normals Using Sequential Nearest-Neighbor Approximation" <doi:10.48550/arXiv.2406.17307>.

Maintained by Jian Cao. Last updated 1 months ago.

cpp

6.4 match 2.85 score 3 scripts

usepa

spsurvey:Spatial Sampling Design and Analysis

A design-based approach to statistical inference, with a focus on spatial data. Spatially balanced samples are selected using the Generalized Random Tessellation Stratified (GRTS) algorithm. The GRTS algorithm can be applied to finite resources (point geometries) and infinite resources (linear / linestring and areal / polygon geometries) and flexibly accommodates a diverse set of sampling design features, including stratification, unequal inclusion probabilities, proportional (to size) inclusion probabilities, legacy (historical) sites, a minimum distance between sites, and two options for replacement sites (reverse hierarchical order and nearest neighbor). Data are analyzed using a wide range of analysis functions that perform categorical variable analysis, continuous variable analysis, attributable risk analysis, risk difference analysis, relative risk analysis, change analysis, and trend analysis. spsurvey can also be used to summarize objects, visualize objects, select samples that are not spatially balanced, select panel samples, measure the amount of spatial balance in a sample, adjust design weights, and more. For additional details, see Dumelle et al. (2023) <doi:10.18637/jss.v105.i03>.

Maintained by Michael Dumelle. Last updated 7 months ago.

ord

2.0 match 15 stars 8.98 score 241 scripts 1 dependents

ropensci

spatsoc:Group Animal Relocation Data by Spatial and Temporal Relationship

Detects spatial and temporal groups in GPS relocations (Robitaille et al. (2019) <doi:10.1111/2041-210X.13215>). It can be used to convert GPS relocations to gambit-of-the-group format to build proximity-based social networks In addition, the randomizations function provides data-stream randomization methods suitable for GPS data.

Maintained by Alec L. Robitaille. Last updated 1 months ago.

animal gps network social spatial

1.8 match 24 stars 9.97 score 145 scripts 3 dependents

joycekang

symphony:Efficient and Precise Single-Cell Reference Atlas Mapping

Implements the Symphony single-cell reference building and query mapping algorithms and additional functions described in Kang et al <https://www.nature.com/articles/s41467-021-25957-x>.

Maintained by Joyce Kang. Last updated 2 years ago.

openblas cpp

4.6 match 3.83 score 134 scripts

bioc

bluster:Clustering Algorithms for Bioconductor

Wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.

Maintained by Aaron Lun. Last updated 5 months ago.

immunooncology software geneexpression transcriptomics singlecell clustering cpp

1.9 match 9.43 score 636 scripts 51 dependents

grasia

knnp:Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel)

Two main functionalities are provided. One of them is predicting values with k-nearest neighbors algorithm and the other is optimizing the parameters k and d of the algorithm. These are carried out in parallel using multiple threads.

Maintained by Daniel Bastarrica Lacalle. Last updated 5 years ago.

knearest-neighbor-algorithm parallel time-series-forecasting

6.5 match 1 stars 2.70 score 8 scripts

r-spatial

RSAGA:SAGA Geoprocessing and Terrain Analysis

Provides access to geocomputing and terrain analysis functions of the geographical information system (GIS) 'SAGA' (System for Automated Geoscientific Analyses) from within R by running the command line version of SAGA. This package furthermore provides several R functions for handling ASCII grids, including a flexible framework for applying local functions (including predict methods of fitted models) and focal functions to multiple grids. SAGA GIS is available under GPL-2 / LGPL-2 licences from <https://sourceforge.net/projects/saga-gis/>.

Maintained by Alexander Brenning. Last updated 1 months ago.

2.0 match 23 stars 8.72 score 275 scripts

bioc

pRoloc:A unifying bioinformatics framework for spatial proteomics

The pRoloc package implements machine learning and visualisation methods for the analysis and interogation of quantitiative mass spectrometry data to reliably infer protein sub-cellular localisation.

Maintained by Lisa Breckels. Last updated 27 days ago.

immunooncology proteomics massspectrometry classification clustering qualitycontrol bioconductor proteomics-data spatial-proteomics visualisation openblas cpp

2.0 match 15 stars 8.71 score 101 scripts 2 dependents

aleksandarsekulic

meteo:RFSI & STRK Interpolation for Meteo and Environmental Variables

Random Forest Spatial Interpolation (RFSI, Sekulić et al. (2020) <doi:10.3390/rs12101687>) and spatio-temporal geostatistical (spatio-temporal regression Kriging (STRK)) interpolation for meteorological (Kilibarda et al. (2014) <doi:10.1002/2013JD020803>, Sekulić et al. (2020) <doi:10.1007/s00704-019-03077-3>) and other environmental variables. Contains global spatio-temporal models calculated using publicly available data.

Maintained by Aleksandar Sekulić. Last updated 6 months ago.

3.4 match 18 stars 5.06 score 64 scripts