Showing 26 of total 26 results (show query)
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 2 months ago.
infrastructuredatarepresentationbioconductor-packagecore-package
22 stars 16.09 score 2.1k scripts 1.8k dependentsbioc
S4Vectors:Foundation of vector-like and list-like containers in Bioconductor
The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, Factor, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).
Maintained by Hervé Pagès. Last updated 2 months ago.
infrastructuredatarepresentationbioconductor-packagecore-package
18 stars 16.05 score 1.0k scripts 1.9k dependentsbioc
microbiome:Microbiome Analytics
Utilities for microbiome analysis.
Maintained by Leo Lahti. Last updated 5 months ago.
metagenomicsmicrobiomesequencingsystemsbiologyhitchiphitchip-atlashuman-microbiomemicrobiologymicrobiome-analysisphyloseqpopulation-study
293 stars 12.51 score 2.0k scripts 5 dependents
ncss-tech
aqp:Algorithms for Quantitative Pedology
The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Maintained by Dylan Beaudette. Last updated 1 months ago.
digital-soil-mappingncss-technrcspedologypedometricssoilsoil-surveyusda
55 stars 11.90 score 1.2k scripts 2 dependentsbioc
ggcyto:Visualize Cytometry data with ggplot
With the dedicated fortify method implemented for flowSet, ncdfFlowSet and GatingSet classes, both raw and gated flow cytometry data can be plotted directly with ggplot. ggcyto wrapper and some customed layers also make it easy to add gates and population statistics to the plot.
Maintained by Mike Jiang. Last updated 5 months ago.
immunooncologyflowcytometrycellbasedassaysinfrastructurevisualization
58 stars 11.25 score 362 scripts 5 dependents
choonghyunryu
dlookr:Tools for Data Diagnosis, Exploration, Transformation
A collection of tools that support data diagnosis, exploration, and transformation. Data diagnostics provides information and visualization of missing values, outliers, and unique and negative values to help you understand the distribution and quality of your data. Data exploration provides information and visualization of the descriptive statistics of univariate variables, normality tests and outliers, correlation of two variables, and the relationship between the target variable and predictor. Data transformation supports binning for categorizing continuous variables, imputes missing values and outliers, and resolves skewness. And it creates automated reports that support these three tasks.
Maintained by Choonghyun Ryu. Last updated 10 months ago.
212 stars 11.05 score 748 scripts 2 dependentsbioc
flowCore:flowCore: Basic structures for flow cytometry data
Provides S4 data structures and basic functions to deal with flow cytometry data.
Maintained by Mike Jiang. Last updated 5 months ago.
immunooncologyinfrastructureflowcytometrycellbasedassayscpp
10.17 score 1.7k scripts 59 dependents
flr
FLCore:Core Package of FLR, Fisheries Modelling in R
Core classes and methods for FLR, a framework for fisheries modelling and management strategy simulation in R. Developed by a team of fisheries scientists in various countries. More information can be found at <http://flr-project.org/>.
Maintained by Iago Mosqueira. Last updated 10 days ago.
fisheriesflrfisheries-modelling
16 stars 8.78 score 956 scripts 23 dependentsbioc
flowWorkspace:Infrastructure for representing and interacting with gated and ungated cytometry data sets.
This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.
Maintained by Greg Finak. Last updated 23 days ago.
immunooncologyflowcytometrydataimportpreprocessingdatarepresentationzlibopenblascpp
7.89 score 576 scripts 10 dependents
pmair78
smacof:Multidimensional Scaling
Implements the following approaches for multidimensional scaling (MDS) based on stress minimization using majorization (smacof): ratio/interval/ordinal/spline MDS on symmetric dissimilarity matrices, MDS with external constraints on the configuration, individual differences scaling (idioscal, indscal), MDS with spherical restrictions, and ratio/interval/ordinal/spline unfolding (circular restrictions, row-conditional). Various tools and extensions like jackknife MDS, bootstrap MDS, permutation tests, MDS biplots, gravity models, unidimensional scaling, drift vectors (asymmetric MDS), classical scaling, and Procrustes are implemented as well.
Maintained by Patrick Mair. Last updated 6 months ago.
5 stars 7.86 score 152 scripts 24 dependentsbioc
ncdfFlow:ncdfFlow: A package that provides HDF5 based storage for flow cytometry data.
Provides HDF5 storage based methods and functions for manipulation of flow cytometry data.
Maintained by Mike Jiang. Last updated 3 months ago.
immunooncologyflowcytometryzlibcpp
7.56 score 96 scripts 11 dependents
cytomining
cytominer:Methods for Image-Based Cell Profiling
`cytominer` is a suite of common functions used to process high-dimensional readouts from image-based cell profiling experiments.
Maintained by Shantanu Singh. Last updated 2 years ago.
50 stars 6.89 score 44 scripts
bioc
NanoStringNCTools:NanoString nCounter Tools
Tools for NanoString Technologies nCounter Technology. Provides support for reading RCC files into an ExpressionSet derived object. Also includes methods for QC and normalizaztion of NanoString data.
Maintained by Maddy Griswold. Last updated 5 months ago.
geneexpressiontranscriptioncellbasedassaysdataimporttranscriptomicsproteomicsmrnamicroarrayproprietaryplatformsrnaseq
6.35 score 94 scripts 4 dependents
quantsulting
ghyp:Generalized Hyperbolic Distribution and Its Special Cases
Detailed functionality for working with the univariate and multivariate Generalized Hyperbolic distribution and its special cases (Hyperbolic (hyp), Normal Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t and Gaussian distribution). Especially, it contains fitting procedures, an AIC-based model selection routine, and functions for the computation of density, quantile, probability, random variates, expected shortfall and some portfolio optimization and plotting routines as well as the likelihood ratio test. In addition, it contains the Generalized Inverse Gaussian distribution. See Chapter 3 of A. J. McNeil, R. Frey, and P. Embrechts. Quantitative risk management: Concepts, techniques and tools. Princeton University Press, Princeton (2005).
Maintained by Marc Weibel. Last updated 7 months ago.
5.55 score 90 scripts 8 dependents
mrc-ide
gonovax:Deterministic Compartmental Model of Gonorrhoea with Vaccination
Model for gonorrhoea vaccination, using odin.
Maintained by Lilith Whittles. Last updated 16 days ago.
3 stars 4.56 score
serafinialessio
dformula:Data Manipulation using Formula
A tool for manipulating data using the generic formula. A single formula allows to easily add, replace and remove variables before running the analysis.
Maintained by Alessio Serafini. Last updated 8 months ago.
3.70 score 1 scripts
lawremi
rsolr:R to Solr Interface
A comprehensive R API for querying Apache Solr databases. A Solr core is represented as a data frame or list that supports Solr-side filtering, sorting, transformation and aggregation, all through the familiar base R API. Queries are processed lazily, i.e., a query is only sent to the database when the data are required.
Maintained by Michael Lawrence. Last updated 3 years ago.
9 stars 3.65 score 6 scripts
chemhouse-group
rchemo:Dimension Reduction, Regression and Discrimination for Chemometrics
Data exploration and prediction with focus on high dimensional data and chemometrics. The package was initially designed about partial least squares regression and discrimination models and variants, in particular locally weighted PLS models (LWPLS). Then, it has been expanded to many other methods for analyzing high dimensional data. The name 'rchemo' comes from the fact that the package is orientated to chemometrics, but most of the provided methods are fully generic to other domains. Functions such as transform(), predict(), coef() and summary() are available. Tuning the predictive models is facilitated by generic functions gridscore() (validation dataset) and gridcv() (cross-validation). Faster versions are also available for models based on latent variables (LVs) (gridscorelv() and gridcvlv()) and ridge regularization (gridscorelb() and gridcvlb()).
Maintained by Marion Brandolini-Bunlon. Last updated 7 months ago.
3 stars 3.52 score 11 scripts
navdeep-g
h2o4gpu:Interface to 'H2O4GPU'
Interface to 'H2O4GPU' <https://github.com/h2oai/h2o4gpu>, a collection of 'GPU' solvers for machine learning algorithms.
Maintained by Navdeep Gill. Last updated 4 years ago.
1 stars 3.24 score 35 scripts
rohelab
invertiforms:Invertible Transforms for Matrices
Provides composable invertible transforms for (sparse) matrices.
Maintained by Alex Hayes. Last updated 2 years ago.
1 stars 3.18 score 4 scripts 1 dependents
noramvillanueva
seq2R:Simple Method to Detect Compositional Changes in Genomic Sequences
This software is useful for loading '.fasta' or '.gbk' files, and for retrieving sequences from 'GenBank' dataset <https://www.ncbi.nlm.nih.gov/genbank/>. This package allows to detect differences or asymmetries based on nucleotide composition by using local linear kernel smoothers. Also, it is possible to draw inference about critical points (i. e. maximum or minimum points) related with the derivative curves. Additionally, bootstrap methods have been used for estimating confidence intervals and speed computational techniques (binning techniques) have been implemented in 'seq2R'.
Maintained by Nora M. Villanueva. Last updated 4 months ago.
bootstrapchange-pointsdna-sequencesgenome-analysismachine-learningnonparametric-statisticsregressionfortran
3.00 score 10 scripts
rnorm
CatEncoders:Encoders for Categorical Variables
Contains some commonly used categorical variable encoders, such as 'LabelEncoder' and 'OneHotEncoder'. Inspired by the encoders implemented in Python 'sklearn.preprocessing' package (see <http://scikit-learn.org/stable/modules/preprocessing.html>).
Maintained by nl zhang. Last updated 8 years ago.
1 stars 2.48 score 25 scripts 4 dependents
igordot
phenomenalist:Analysis Toolkit for PhenoCycler (CODEX) Data in R
A collection of tools for cleaning, clustering, and plotting PhenoCycler (CODEX) data.
Maintained by Igor Dolgalev. Last updated 1 years ago.
3 stars 2.18 score 1 scripts
jackdunnnz
iai:Interface to 'Interpretable AI' Modules
An interface to the algorithms of 'Interpretable AI' <https://www.interpretable.ai> from the R programming language. 'Interpretable AI' provides various modules, including 'Optimal Trees' for classification, regression, prescription and survival analysis, 'Optimal Imputation' for missing data imputation and outlier detection, and 'Optimal Feature Selection' for exact sparse regression. The 'iai' package is an open-source project. The 'Interpretable AI' software modules are proprietary products, but free academic and evaluation licenses are available.
Maintained by Jack Dunn. Last updated 5 months ago.
1 stars 2.00 score 7 scripts
rarabzadeh
RHMS:Hydrologic Modelling System for R Users
Hydrologic modelling system is an object oriented tool for simulation and analysis of hydrologic events. The package proposes functions and methods for construction, simulation, visualization, and calibration of a hydrologic model.
Maintained by Rezgar Arabzadeh. Last updated 4 years ago.
1 stars 1.30 score 10 scripts