R-universe search: profiling

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 29 days ago.

digital-soil-mapping ncss-tech nrcs pedology pedometrics soil soil-survey usda

76.6 match 55 stars 11.90 score 1.2k scripts 2 dependents

adokter

bioRad:Biological Analysis and Visualization of Weather Radar Data

Extract, visualize and summarize aerial movements of birds and insects from weather radar data. See Dokter, A. M. et al. (2018) "bioRad: biological analysis and visualization of weather radar data" <doi:10.1111/ecog.04028> for a software paper describing package and methodologies.

Maintained by Adriaan M. Dokter. Last updated 20 days ago.

aeroecology enram eumetnet-opera lifewatch movement-ecology nexrad oscibio radar weather-radar wsr-88d

69.3 match 29 stars 8.65 score 56 scripts

cddesja

profileR:Profile Analysis of Multivariate Data in R

A suite of multivariate methods and data visualization tools to implement profile analysis and cross-validation techniques described in Davison & Davenport (2002) <DOI: 10.1037/1082-989X.7.4.468>, Bulut (2013), and other published and unpublished resources. The package includes routines to perform criterion-related profile analysis, profile analysis via multidimensional scaling, moderated profile analysis, generalizability theory, profile analysis by group, and a within-person factor model to derive score profiles.

Maintained by Christopher David Desjardins. Last updated 2 years ago.

90.1 match 3 stars 5.65 score 50 scripts

modeloriented

ingredients:Effects and Importances of Model Ingredients

Collection of tools for assessment of feature importance and feature effects. Key functions are: feature_importance() for assessment of global level feature importance, ceteris_paribus() for calculation of the what-if plots, partial_dependence() for partial dependence plots, conditional_dependence() for conditional dependence plots, accumulated_dependence() for accumulated local effects plots, aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles, generic print() and plot() for better usability of selected explainers, generic plotD3() for interactive, D3 based explanations, and generic describe() for explanations in natural language. The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.

Maintained by Przemyslaw Biecek. Last updated 2 years ago.

44.2 match 37 stars 10.38 score 83 scripts 22 dependents

r-prof

profile:Read, Manipulate, and Write Profiler Data

Defines a data structure for profiler data, and methods to read and write from the 'Rprof' and 'pprof' file formats.

Maintained by Kirill Müller. Last updated 3 months ago.

60.3 match 12 stars 7.38 score 44 scripts 1 dependents

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

70.1 match 5 stars 6.23 score 19 scripts

bioc

PhyloProfile:PhyloProfile

PhyloProfile is a tool for exploring complex phylogenetic profiles. Phylogenetic profiles, presence/absence patterns of genes over a set of species, are commonly used to trace the functional and evolutionary history of genes across species and time. With PhyloProfile we can enrich regular phylogenetic profiles with further data like sequence/structure similarity, to make phylogenetic profiling more meaningful. Besides the interactive visualisation powered by R-Shiny, the package offers a set of further analysis features to gain insights like the gene age estimation or core gene identification.

Maintained by Vinh Tran. Last updated 7 days ago.

software visualization datarepresentation multiplecomparison functionalprediction dimensionreduction bioinformatics heatmap interactive-visualizations orthologs phylogenetic-profile shiny

48.3 match 33 stars 7.77 score 10 scripts

matrix-profile-foundation

tsmp:Time Series with Matrix Profile

A toolkit implementing the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.

Maintained by Francisco Bischoff. Last updated 3 years ago.

algorithm matrix-profile motif-search time-series cpp

49.5 match 72 stars 7.29 score 179 scripts 1 dependents

dankelley

oce:Analysis of Oceanographic Data

Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature. This package is discussed extensively by Kelley (2018) "Oceanographic Analysis with R" <doi:10.1007/978-1-4939-8844-0>.

Maintained by Dan Kelley. Last updated 2 days ago.

oceanography fortran cpp

20.3 match 146 stars 15.42 score 4.2k scripts 18 dependents

obiba

opalr:'Opal' Data Repository Client and 'DataSHIELD' Utils

Data integration Web application for biobanks by 'OBiBa'. 'Opal' is the core database application for biobanks. Participant data, once collected from any data source, must be integrated and stored in a central data repository under a uniform model. 'Opal' is such a central repository. It can import, process, validate, query, analyze, report, and export data. 'Opal' is typically used in a research center to analyze the data acquired at assessment centres. Its ultimate purpose is to achieve seamless data-sharing among biobanks. This 'Opal' client allows to interact with 'Opal' web services and to perform operations on the R server side. 'DataSHIELD' administration tools are also provided.

Maintained by Yannick Marcon. Last updated 2 months ago.

37.6 match 3 stars 7.76 score 179 scripts 2 dependents

shixiangwang

sigminer:Extract, Analyze and Visualize Mutational Signatures for Genomic Variations

Genomic alterations including single nucleotide substitution, copy number alteration, etc. are the major force for cancer initialization and development. Due to the specificity of molecular lesions caused by genomic alterations, we can generate characteristic alteration spectra, called 'signature' (Wang, Shixiang, et al. (2021) <DOI:10.1371/journal.pgen.1009557> & Alexandrov, Ludmil B., et al. (2020) <DOI:10.1038/s41586-020-1943-3> & Steele Christopher D., et al. (2022) <DOI:10.1038/s41586-022-04738-6>). This package helps users to extract, analyze and visualize signatures from genomic alteration records, thus providing new insight into cancer study.

Maintained by Shixiang Wang. Last updated 5 months ago.

bayesian-nmf bioinformatics cancer-research cnv copynumber-signatures cosmic-signatures dbs easy-to-use indel mutational-signatures nmf nmf-extraction sbs signature-extraction somatic-mutations somatic-variants visualization cpp

29.7 match 150 stars 9.48 score 123 scripts 2 dependents

fherla

sarp.snowprofile.alignment:Snow Profile Alignment, Aggregation, and Clustering

Snow profiles describe the vertical (1D) stratigraphy of layered snow with different layer characteristics, such as grain type, hardness, deposition date, and many more. Hence, they represent a data format similar to multivariate time series containing categorical, ordinal, and numerical data types. Use this package to align snow profiles by matching their individual layers based on Dynamic Time Warping (DTW). The aligned profiles can then be assessed with an independent, global similarity measure that is geared towards avalanche hazard assessment. Finally, through exploiting data aggregation and clustering methods, the similarity measure provides the foundation for grouping and summarizing snow profiles according to similar hazard conditions. In particular, this package allows for averaging large numbers of snow profiles with DTW Barycenter Averaging and thereby facilitates the computation of individual layer distributions and summary statistics that are relevant for avalanche forecasting purposes. For more background information refer to Herla, Horton, Mair, and Haegeli (2021) <doi:10.5194/gmd-14-239-2021>, Herla, Mair, and Haegeli (2022) <doi:10.5194/tc-16-3149-2022>, and Horton, Herla, and Haegeli (2024) <doi:10.5194/egusphere-2024-1609>.

Maintained by Florian Herla. Last updated 7 months ago.

73.8 match 3.45 score 14 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 3 days ago.

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

16.9 match 196 stars 14.31 score 984 scripts 11 dependents

openanalytics

patientProfilesVis:Visualization of Patient Profiles

Creation of patient profile visualizations for exploration, diagnostic or monitoring purposes during a clinical trial. These static visualizations display a patient-specific overview of the evolution during the trial time frame of parameters of interest (as laboratory, ECG, vital signs), presence of adverse events, exposure to a treatment; associated with metadata patient information, as demography, concomitant medication. The visualizations can be tailored for specific domain(s) or endpoint(s) of interest. Visualizations are exported into patient profile report(s) or can be embedded in custom report(s).

Maintained by Laure Cougnaud. Last updated 9 months ago.

46.7 match 7 stars 5.15 score 9 scripts

bioc

similaRpeak:Metrics to estimate a level of similarity between two ChIP-Seq profiles

This package calculates metrics which quantify the level of similarity between ChIP-Seq profiles. More specifically, the package implements six pseudometrics specialized in pattern similarity detection in ChIP-Seq profiles.

Maintained by Astrid Deschênes. Last updated 5 months ago.

biologicalquestion chipseq genetics multiplecomparison differentialexpression bioconductor bioconductor-package chip-profiles chip-seq metrics

39.9 match 7 stars 5.62 score 7 scripts

wviechtb

metafor:Meta-Analysis Package for R

A comprehensive collection of functions for conducting meta-analyses in R. The package includes functions to calculate various effect sizes or outcome measures, fit equal-, fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analyses, and create various types of meta-analytical plots (e.g., forest, funnel, radial, L'Abbe, Baujat, bubble, and GOSH plots). For meta-analyses of binomial and person-time data, the package also provides functions that implement specialized methods, including the Mantel-Haenszel method, Peto's method, and a variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects logistic and Poisson regression models). Finally, the package provides functionality for fitting meta-analytic multivariate/multilevel models that account for non-independent sampling errors and/or true effects (e.g., due to the inclusion of multiple treatment studies, multiple endpoints, or other forms of clustering). Network meta-analyses and meta-analyses accounting for known correlation structures (e.g., due to phylogenetic relatedness) can also be conducted. An introduction to the package can be found in Viechtbauer (2010) <doi:10.18637/jss.v036.i03>.

Maintained by Wolfgang Viechtbauer. Last updated 2 days ago.

meta-analysis mixed-effects multilevel-models multivariate

13.7 match 246 stars 16.30 score 4.9k scripts 92 dependents

bioc

BPRMeth:Model higher-order methylation profiles

The BPRMeth package is a probabilistic method to quantify explicit features of methylation profiles, in a way that would make it easier to formally use such profiles in downstream modelling efforts, such as predicting gene expression levels or clustering genomic regions or cells according to their methylation profiles.

Maintained by Chantriolnt-Andreas Kapourani. Last updated 5 months ago.

immunooncology dnamethylation geneexpression generegulation epigenetics genetics clustering featureextraction regression rnaseq bayesian kegg sequencing coverage singlecell openblas cpp

35.8 match 5.75 score 94 scripts 1 dependents

bioc

ChIPseeker:ChIPseeker for ChIP peak Annotation, Comparison, and Visualization

This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets, and incorporate GEO database for user to compare the own dataset with those deposited in database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes.

Maintained by Guangchuang Yu. Last updated 5 months ago.

annotation chipseq software visualization multiplecomparison atac-seq chip-seq comparison epigenetics epigenomics

14.0 match 234 stars 13.02 score 1.6k scripts 5 dependents

bioc

goProfiles:goProfiles: an R package for the statistical analysis of functional profiles

The package implements methods to compare lists of genes based on comparing the corresponding 'functional profiles'.

Maintained by Alex Sanchez. Last updated 5 months ago.

annotation go geneexpression genesetenrichment graphandnetwork microarray multiplecomparison pathways software

32.9 match 5.48 score 6 scripts 1 dependents

dkaschek

dMod:Dynamic Modeling and Parameter Estimation in ODE Models

The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.

Maintained by Daniel Kaschek. Last updated 10 days ago.

21.6 match 20 stars 8.35 score 251 scripts

paterijk

MCDA:Support for the Multicriteria Decision Aiding Process

Support for the analyst in a Multicriteria Decision Aiding (MCDA) process with algorithms, preference elicitation and data visualisation functions. Sébastien Bigaret, Richard Hodgett, Patrick Meyer, Tatyana Mironova, Alexandru Olteanu (2017) Supporting the multi-criteria decision aiding process : R and the MCDA package, Euro Journal On Decision Processes, Volume 5, Issue 1 - 4, pages 169 - 194 <doi:10.1007/s40070-017-0064-1>.

Maintained by Patrick Meyer. Last updated 2 years ago.

28.2 match 30 stars 6.04 score 182 scripts

femiguez

apsimx:Inspect, Read, Edit and Run 'APSIM' "Next Generation" and 'APSIM' Classic

The functions in this package inspect, read, edit and run files for 'APSIM' "Next Generation" ('JSON') and 'APSIM' "Classic" ('XML'). The files with an 'apsim' extension correspond to 'APSIM' Classic (7.x) - Windows only - and the ones with an 'apsimx' extension correspond to 'APSIM' "Next Generation". For more information about 'APSIM' see (<https://www.apsim.info/>) and for 'APSIM' next generation (<https://apsimnextgeneration.netlify.app/>).

Maintained by Fernando Miguez. Last updated 3 days ago.

apsim apsimx

17.3 match 59 stars 9.71 score 68 scripts 2 dependents

bioc

seqCAT:High Throughput Sequencing Cell Authentication Toolkit

The seqCAT package uses variant calling data (in the form of VCF files) from high throughput sequencing technologies to authenticate and validate the source, function and characteristics of biological samples used in scientific endeavours.

Maintained by Erik Fasterius. Last updated 5 months ago.

coverage genomicvariation sequencing variantannotation

41.5 match 4.00 score

trackerproject

trackeR:Infrastructure for Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices

Provides infrastructure for handling running, cycling and swimming data from GPS-enabled tracking devices within R. The package provides methods to extract, clean and organise workout and competition data into session-based and unit-aware data objects of class 'trackeRdata' (S3 class). The information can then be visualised, summarised, and analysed through flexible and extensible methods. Frick and Kosmidis (2017) <doi: 10.18637/jss.v082.i07>, which is updated and maintained as one of the vignettes, provides detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality.

Maintained by Ioannis Kosmidis. Last updated 1 years ago.

25.3 match 90 stars 6.37 score 58 scripts 1 dependents

bioc

MutationalPatterns:Comprehensive genome-wide analysis of mutational processes

Mutational processes leave characteristic footprints in genomic DNA. This package provides a comprehensive set of flexible functions that allows researchers to easily evaluate and visualize a multitude of mutational patterns in base substitution catalogues of e.g. healthy samples, tumour samples, or DNA-repair deficient cells. The package covers a wide range of patterns including: mutational signatures, transcriptional and replicative strand bias, lesion segregation, genomic distribution and association with genomic features, which are collectively meaningful for studying the activity of mutational processes. The package works with single nucleotide variants (SNVs), insertions and deletions (Indels), double base substitutions (DBSs) and larger multi base substitutions (MBSs). The package provides functionalities for both extracting mutational signatures de novo and determining the contribution of previously identified mutational signatures on a single sample level. MutationalPatterns integrates with common R genomic analysis workflows and allows easy association with (publicly available) annotation data.

Maintained by Mark van Roosmalen. Last updated 5 months ago.

genetics somaticmutation

21.6 match 7.27 score 251 scripts 1 dependents

henrikbengtsson

profmem:Simple Memory Profiling for R

A simple and light-weight API for memory profiling of R expressions. The profiling is built on top of R's built-in memory profiler ('utils::Rprofmem()'), which records every memory allocation done by R (also native code).

Maintained by Henrik Bengtsson. Last updated 4 years ago.

memory-profiler performance ram

16.7 match 36 stars 9.13 score 141 scripts 11 dependents

bioc

clusterProfiler:A universal enrichment tool for interpreting omics data

This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios. It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation. Datasets obtained from multiple treatments and time points can be analyzed and compared in a single run, easily revealing functional consensus and differences among distinct conditions.

Maintained by Guangchuang Yu. Last updated 4 months ago.

annotation clustering genesetenrichment go kegg multiplecomparison pathways reactome visualization enrichment-analysis gsea

8.8 match 1.1k stars 17.03 score 11k scripts 48 dependents

emilopezcano

SixSigma:Six Sigma Tools for Quality Control and Improvement

Functions and utilities to perform Statistical Analyses in the Six Sigma way. Through the DMAIC cycle (Define, Measure, Analyze, Improve, Control), you can manage several Quality Management studies: Gage R&R, Capability Analysis, Control Charts, Loss Function Analysis, etc. Data frames used in the books "Six Sigma with R" [ISBN 978-1-4614-3652-2] and "Quality Control with R" [ISBN 978-3-319-24046-6], are also included in the package.

Maintained by Emilio L. Cano. Last updated 2 years ago.

quality-control quality-improvement six-sigma spc

18.8 match 15 stars 7.82 score 169 scripts 1 dependents

bioc

mitch:Multi-Contrast Gene Set Enrichment Analysis

mitch is an R package for multi-contrast enrichment analysis. At it’s heart, it uses a rank-MANOVA based statistical approach to detect sets of genes that exhibit enrichment in the multidimensional space as compared to the background. The rank-MANOVA concept dates to work by Cox and Mann (https://doi.org/10.1186/1471-2105-13-S16-S12). mitch is useful for pathway analysis of profiling studies with one, two or more contrasts, or in studies with multiple omics profiling, for example proteomic, transcriptomic, epigenomic analysis of the same samples. mitch is perfectly suited for pathway level differential analysis of scRNA-seq data. We have an established routine for pathway enrichment of Infinium Methylation Array data (see vignette). The main strengths of mitch are that it can import datasets easily from many upstream tools and has advanced plotting features to visualise these enrichments.

Maintained by Mark Ziemann. Last updated 4 months ago.

geneexpression genesetenrichment singlecell transcriptomics epigenetics proteomics differentialexpression reactome dnamethylation methylationarray gene-regulation gene-seq-analysis pathway-analysis

20.7 match 16 stars 7.06 score 15 scripts

bbolker

bbmle:Tools for General Maximum Likelihood Estimation

Methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.

Maintained by Ben Bolker. Last updated 1 months ago.

10.9 match 25 stars 13.36 score 1.4k scripts 117 dependents

ai4ci

ggoutbreak:Estimate Incidence, Proportions and Exponential Growth Rates

Simple statistical models and visualisations for calculating the incidence, proportion, exponential growth rate, and reproduction number of infectious disease case time series. This toolkit was largely developed during the COVID-19 pandemic.

Maintained by Robert Challen. Last updated 1 months ago.

33.7 match 1 stars 4.30 score

ausclimateservice

TCHazaRds:Tropical Cyclone (Hurricane, Typhoon) Spatial Hazard Modelling

Methods for generating modelled parametric Tropical Cyclone (TC) spatial hazard fields and time series output at point locations from TC tracks. R's compatibility to simply use fast 'cpp' code via the 'Rcpp' package and the wide range spatial analysis tools via the 'terra' package makes it an attractive open source environment to study 'TCs'. This package estimates TC vortex wind and pressure fields using parametric equations originally coded up in 'python' by 'TCRM' <https://github.com/GeoscienceAustralia/tcrm> and then coded up in 'Cuda' 'cpp' by 'TCwindgen' <https://github.com/CyprienBosserelle/TCwindgen>.

Maintained by Julian OGrady. Last updated 2 months ago.

natural-hazards rspatial tropical-cyclone cpp

28.6 match 4 stars 5.00 score

insightsengineering

teal.modules.clinical:'teal' Modules for Standard Clinical Outputs

Provides user-friendly tools for creating and customizing clinical trial reports. By leveraging the 'teal' framework, this package provides 'teal' modules to easily create an interactive panel that allows for seamless adjustments to data presentation, thereby streamlining the creation of detailed and accurate reports.

Maintained by Dawid Kaledkowski. Last updated 17 days ago.

clinical-trials modules nest outputs shiny

13.9 match 34 stars 10.25 score 149 scripts

modeloriented

DALEX:moDel Agnostic Language for Exploration and eXplanation

Any unverified black box model is the path to failure. Opaqueness leads to distrust. Distrust leads to ignoration. Ignoration leads to rejection. DALEX package xrays any model and helps to explore and explain its behaviour. Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance. But such black-box models usually lack direct interpretability. DALEX package contains various methods that help to understand the link between input variables and model output. Implemented methods help to explore the model on the level of a single instance as well as a level of the whole dataset. All model explainers are model agnostic and can be compared across different models. DALEX package is the cornerstone for 'DrWhy.AI' universe of packages for visual model exploration. Find more details in (Biecek 2018) <https://jmlr.org/papers/v19/18-416.html>.

Maintained by Przemyslaw Biecek. Last updated 1 months ago.

black-box dalex data-science explainable-ai explainable-artificial-intelligence explainable-ml explanations explanatory-model-analysis fairness iml interpretability interpretable-machine-learning machine-learning model-visualization predictive-modeling responsible-ai responsible-ml xai

10.5 match 1.4k stars 13.40 score 876 scripts 21 dependents

krajnc

densitr:Analysing Density Profiles from Resistance Drilling of Trees

Provides various tools for analysing density profiles obtained by resistance drilling. It can load individual or multiple files and trim the starting and ending part of each density profile. Tools are also provided to trim profiles manually, to remove the trend from measurements using several methods, to plot the profiles and to detect tree rings automatically. Written with a focus on forestry use of resistance drilling in standing trees.

Maintained by Luka Krajnc. Last updated 3 years ago.

35.9 match 2 stars 3.90 score 9 scripts

data-edu

tidyLPA:Easily Carry Out Latent Profile Analysis (LPA) Using Open-Source or Commercial Software

Easily carry out latent profile analysis ("LPA"), determine the correct number of classes based on best practices, and tabulate and plot the results. Provides functionality to estimate commonly-specified models with free means, variances, and covariances for each profile. Follows a tidy approach, in that output is in the form of a data frame that can subsequently be computed on. Models can be estimated using the free open source 'R' packages 'Mclust' and 'OpenMx', or using the commercial program 'MPlus', via the 'MplusAutomation' package.

Maintained by Joshua M Rosenberg. Last updated 1 years ago.

15.7 match 57 stars 8.71 score 121 scripts

carlos-alberto-silva

rGEDI:NASA's Global Ecosystem Dynamics Investigation (GEDI) Data Visualization and Processing

Set of tools for downloading, reading, visualizing and processing GEDI Level1B, Level2A and Level2B data.

Maintained by Caio Hamamura. Last updated 5 months ago.

21.9 match 169 stars 6.11 score 85 scripts 1 dependents

ltierney

proftools:Profile Output Processing Tools for R

Tools for examining Rprof profile output.

Maintained by Luke Tierney. Last updated 5 years ago.

29.0 match 4.58 score 128 scripts 1 dependents

argocanada

argoFloats:Analysis of Oceanographic Argo Floats

Supports the analysis of oceanographic data recorded by Argo autonomous drifting profiling floats. Functions are provided to (a) download and cache data files, (b) subset data in various ways, (c) handle quality-control flags and (d) plot the results according to oceanographic conventions. A shiny app is provided for easy exploration of datasets. The package is designed to work well with the 'oce' package, providing a wide range of processing capabilities that are particular to oceanographic analysis. See Kelley, Harbin, and Richards (2021) <doi:10.3389/fmars.2021.635922> for more on the scientific context and applications.

Maintained by Dan Kelley. Last updated 1 months ago.

17.2 match 17 stars 7.32 score 203 scripts

r-lib

profvis:Interactive Visualizations for Profiling R Code

Interactive visualizations for profiling R code.

Maintained by Hadley Wickham. Last updated 6 months ago.

7.9 match 310 stars 15.63 score 1.3k scripts 152 dependents

annechao

iNEXT.3D:Interpolation and Extrapolation for Three Dimensions of Biodiversity

Biodiversity is a multifaceted concept covering different levels of organization from genes to ecosystems. 'iNEXT.3D' extends 'iNEXT' to include three dimensions (3D) of biodiversity, i.e., taxonomic diversity (TD), phylogenetic diversity (PD) and functional diversity (FD). This package provides functions to compute standardized 3D diversity estimates with a common sample size or sample coverage. A unified framework based on Hill numbers and their generalizations (Hill-Chao numbers) are used to quantify 3D. All 3D estimates are in the same units of species/lineage equivalents and can be meaningfully compared. The package features size- and coverage-based rarefaction and extrapolation sampling curves to facilitate rigorous comparison of 3D diversity across individual assemblages. Asymptotic 3D diversity estimates are also provided. See Chao et al. (2021) <doi:10.1111/2041-210X.13682> for more details.

Maintained by Anne Chao. Last updated 27 days ago.

cpp

18.3 match 6.74 score 26 scripts 2 dependents

shaunpwilkinson

aphid:Analysis with Profile Hidden Markov Models

Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).

Maintained by Shaun Wilkinson. Last updated 8 months ago.

cpp

18.3 match 22 stars 6.58 score 38 scripts 3 dependents

fragla

eq5d:Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index Scores

EQ-5D is a popular health related quality of life instrument used in the clinical and economic evaluation of health care. Developed by the EuroQol group <https://euroqol.org/>, the instrument consists of two components: health state description and evaluation. For the description component a subject self-rates their health in terms of five dimensions; mobility, self-care, usual activities, pain/discomfort, and anxiety/depression using either a three-level (EQ-5D-3L, <https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-3l/>) or a five-level (EQ-5D-5L, <https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-5l/>) scale. Frequently the scores on these five dimensions are converted to a single utility index using country specific value sets, which can be used in the clinical and economic evaluation of health care as well as in population health surveys. The eq5d package provides methods to calculate index scores from a subject's dimension scores. 32 TTO and 11 VAS EQ-5D-3L value sets including those for countries in Szende et al (2007) <doi:10.1007/1-4020-5511-0> and Szende et al (2014) <doi:10.1007/978-94-007-7596-1>, 47 EQ-5D-5L EQ-VT value sets, the EQ-5D-5L crosswalk value sets developed by van Hout et al. (2012) <doi:10.1016/j.jval.2012.02.008>, the crosswalk value sets for Bermuda, Jordan and Russia and the reverse crosswalk value sets. 10 EQ-5D-Y value sets are also included as are the NICE 'DSU' age-sex based EQ-5D-3L to EQ-5D-5L and EQ-5D-5L to EQ-5D-3L mappings. Methods are also included for the analysis of EQ-5D profiles, including those from the book "Methods for Analyzing and Reporting EQ-5D data" by Devlin et al. (2020) <doi:10.1007/978-3-030-47622-9>. Additionally a shiny web tool is included to enable the calculation, visualisation and automated statistical analysis of EQ-5D data via a web browser using EQ-5D dimension scores stored in CSV or Excel files.

Maintained by Fraser Morton. Last updated 15 days ago.

14.2 match 22 stars 8.19 score 37 scripts

dazzimonti

profExtrema:Compute and Visualize Profile Extrema Functions

Computes profile extrema functions for arbitrary functions. If the function is expensive-to-evaluate it computes profile extrema by emulating the function with a Gaussian process (using package 'DiceKriging'). In this case uncertainty quantification on the profile extrema can also be computed. The different plotting functions for profile extrema give the user a tool to better locate excursion sets.

Maintained by Dario Azzimonti. Last updated 4 months ago.

42.9 match 2.70 score 10 scripts

bioc

fgsea:Fast Gene Set Enrichment Analysis

The package implements an algorithm for fast gene set enrichment analysis. Using the fast algorithm allows to make more permutations and get more fine grained p-values, which allows to use accurate stantard approaches to multiple hypothesis correction.

Maintained by Alexey Sergushichev. Last updated 3 months ago.

geneexpression differentialexpression genesetenrichment pathways cpp

7.1 match 387 stars 16.25 score 3.9k scripts 101 dependents

baddstats

scuba:Diving Calculations and Decompression Models

Code for describing and manipulating scuba diving profiles (depth-time curves) and decompression models, for calculating the predictions of decompression models, for calculating maximum no-decompression time and decompression tables, and for performing mixed gas calculations.

Maintained by Adrian Baddeley. Last updated 2 years ago.

34.6 match 5 stars 3.32 score 42 scripts

ikosmidis

brglm:Bias Reduction in Binomial-Response Generalized Linear Models

Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.

Maintained by Ioannis Kosmidis. Last updated 4 years ago.

16.1 match 6 stars 7.14 score 86 scripts 11 dependents

gleon

rLakeAnalyzer:Lake Physics Tools

Standardized methods for calculating common important derived physical features of lakes including water density based based on temperature, thermal layers, thermocline depth, lake number, Wedderburn number, Schmidt stability and others.

Maintained by Luke Winslow. Last updated 4 years ago.

12.7 match 45 stars 9.05 score 280 scripts 1 dependents

ms609

TreeSearch:Phylogenetic Analysis with Discrete Character Data

Reconstruct phylogenetic trees from discrete data. Inapplicable character states are handled using the algorithm of Brazeau, Guillerme and Smith (2019) <doi:10.1093/sysbio/syy083> with the "Morphy" library, under equal or implied step weights. Contains a "shiny" user interface for interactive tree search and exploration of results, including character visualization, rogue taxon detection, tree space mapping, and cluster consensus trees (Smith 2022a, b) <doi:10.1093/sysbio/syab099>, <doi:10.1093/sysbio/syab100>. Profile Parsimony (Faith and Trueman, 2001) <doi:10.1080/10635150118627>, Successive Approximations (Farris, 1969) <doi:10.2307/2412182> and custom optimality criteria are implemented.

Maintained by Martin R. Smith. Last updated 4 days ago.

bioinformatics morphological-analysis phylogenetics research-tool tree-search cpp

14.4 match 7 stars 7.89 score 51 scripts

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

11.5 match 173 stars 9.65 score 203 scripts 2 dependents

dmurdoch

ellipse:Functions for Drawing Ellipses and Ellipse-Like Confidence Regions

Contains various routines for drawing ellipses and ellipse-like confidence regions, implementing the plots described in Murdoch and Chow (1996, <doi:10.2307/2684435>). There are also routines implementing the profile plots described in Bates and Watts (1988, <doi:10.1002/9780470316757>).

Maintained by Duncan Murdoch. Last updated 2 years ago.

9.9 match 4 stars 11.13 score 1.2k scripts 256 dependents

bioc

canceR:A Graphical User Interface for accessing and modeling the Cancer Genomics Data of MSKCC

The package is user friendly interface based on the cgdsr and other modeling packages to explore, compare, and analyse all available Cancer Data (Clinical data, Gene Mutation, Gene Methylation, Gene Expression, Protein Phosphorylation, Copy Number Alteration) hosted by the Computational Biology Center at Memorial-Sloan-Kettering Cancer Center (MSKCC).

Maintained by Karim Mezhoud. Last updated 5 months ago.

gui geneexpression clustering go genesetenrichment kegg multiplecomparison cancer cancer-data gene gene-expression gene-methylation gene-mutation gene-sets methylation mskcc mutations tcltk

20.9 match 7 stars 5.25 score 17 scripts

r4ss

r4ss:R Code for Stock Synthesis

A collection of R functions for use with Stock Synthesis, a fisheries stock assessment modeling platform written in ADMB by Dr. Richard D. Methot at the NOAA Northwest Fisheries Science Center. The functions include tools for summarizing and plotting results, manipulating files, visualizing model parameterizations, and various other common stock assessment tasks. This version of '{r4ss}' is compatible with Stock Synthesis versions 3.24 through 3.30 (specifically version 3.30.23.1, from December 2024). Support for 3.24 models is only through the core functions for reading output and plotting.

Maintained by Ian G. Taylor. Last updated 5 days ago.

fisheries fisheries-stock-assessment stock-synthesis

9.6 match 43 stars 11.38 score 1.0k scripts 2 dependents

stan-dev

cmdstanr:R Interface to 'CmdStan'

A lightweight interface to 'Stan' <https://mc-stan.org>. The 'CmdStanR' interface is an alternative to 'RStan' that calls the command line interface for compilation and running algorithms instead of interfacing with C++ via 'Rcpp'. This has many benefits including always being compatible with the latest version of Stan, fewer installation errors, fewer unexpected crashes in RStudio, and a more permissive license.

Maintained by Andrew Johnson. Last updated 9 months ago.

bayes bayesian markov-chain-monte-carlo maximum-likelihood mcmc stan variational-inference

8.8 match 145 stars 12.27 score 5.2k scripts 9 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 6 days ago.

distance openstreetmap router shortest-paths street-networks cpp

9.3 match 129 stars 11.53 score 229 scripts 4 dependents

constantamateur

SoupX:Single Cell mRNA Soup eXterminator

Quantify, profile and remove ambient mRNA contamination (the "soup") from droplet based single cell RNA-seq experiments. Implements the method described in Young et al. (2018) <doi:10.1101/303727>.

Maintained by Matthew Daniel Young. Last updated 2 years ago.

10.6 match 264 stars 10.09 score 594 scripts 1 dependents

georgheinze

logistf:Firth's Bias-Reduced Logistic Regression

Fit a logistic regression model using Firth's bias reduction method, equivalent to penalization of the log-likelihood by the Jeffreys prior. Confidence intervals for regression coefficients can be computed by penalized profile likelihood. Firth's method was proposed as ideal solution to the problem of separation in logistic regression, see Heinze and Schemper (2002) <doi:10.1002/sim.1047>. If needed, the bias reduction can be turned off such that ordinary maximum likelihood logistic regression is obtained. Two new modifications of Firth's method, FLIC and FLAC, lead to unbiased predictions and are now available in the package as well, see Puhr et al (2017) <doi:10.1002/sim.7273>.

Maintained by Georg Heinze. Last updated 2 years ago.

11.5 match 12 stars 9.23 score 346 scripts 16 dependents

matrix-profile-foundation

matrixprofiler:Matrix Profile for R

This is the core functions needed by the 'tsmp' package. The low level and carefully checked mathematical functions are here. These are implementations of the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.

Maintained by Francisco Bischoff. Last updated 3 years ago.

algorithm matrix-profile rcpp time-series cpp

28.7 match 10 stars 3.70 score 2 scripts

bioc

RnBeads:RnBeads

RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.

Maintained by Fabian Mueller. Last updated 1 months ago.

dnamethylation methylationarray methylseq epigenetics qualitycontrol preprocessing batcheffect differentialmethylation sequencing cpgisland immunooncology twochannel dataimport

15.2 match 6.85 score 169 scripts 1 dependents

oskarhansson

strvalidator:Process Control and Validation of Forensic STR Kits

An open source platform for validation and process control. Tools to analyze data from internal validation of forensic short tandem repeat (STR) kits are provided. The tools are developed to provide the necessary data to conform with guidelines for internal validation issued by the European Network of Forensic Science Institutes (ENFSI) DNA Working Group, and the Scientific Working Group on DNA Analysis Methods (SWGDAM). A front-end graphical user interface is provided. More information about each function can be found in the respective help documentation.

Maintained by Oskar Hansson. Last updated 2 months ago.

22.5 match 5 stars 4.29 score 13 scripts

bioc

seqsetvis:Set Based Visualizations for Next-Gen Sequencing Data

seqsetvis enables the visualization and analysis of sets of genomic sites in next gen sequencing data. Although seqsetvis was designed for the comparison of mulitple ChIP-seq samples, this package is domain-agnostic and allows the processing of multiple genomic coordinate files (bed-like files) and signal files (bigwig files pileups from bam file). seqsetvis has multiple functions for fetching data from regions into a tidy format for analysis in data.table or tidyverse and visualization via ggplot2.

Maintained by Joseph R Boyd. Last updated 3 months ago.

software chipseq multiplecomparison sequencing visualization

16.5 match 5.82 score 82 scripts

ebmtnprof

rties:Modeling Interpersonal Dynamics

The name of this package grew out of our research on temporal interpersonal emotion systems (TIES), hence 'rties'. It provides tools for using a set of models to investigate temporal processes in bivariate (e.g., dyadic) systems. The general approach is to model, one dyad at a time, the dynamics of a variable that is assessed repeatedly from both partners, extract the parameter estimates for each dyad, and then use those parameter estimates as input to a latent profile analysis to extract groups of dyads with qualitatively distinct dynamics. Finally, the profile memberships can be used to either predict, or be predicted by, another variable of interest. Currently, 2 models are supported: 1) inertia-coordination, and 2) a coupled-oscillator. Extended documentation is provided in vignettes. Theoretical background can be found in Butler (2011) <doi:10.1177/1088868311411164> and Butler & Barnard (2019) <doi:10.1097/PSY.0000000000000703>.

Maintained by Emily Butler. Last updated 3 years ago.

24.0 match 11 stars 3.94 score 16 scripts

bioc

SpatialDecon:Deconvolution of mixed cells from spatial and/or bulk gene expression data

Using spatial or bulk gene expression data, estimates abundance of mixed cell types within each observation. Based on "Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data", Danaher (2022). Designed for use with the NanoString GeoMx platform, but applicable to any gene expression data.

Maintained by Maddy Griswold. Last updated 5 months ago.

immunooncology featureextraction geneexpression transcriptomics spatial

12.8 match 36 stars 7.40 score 58 scripts

8-bit-sheep

googleAnalyticsR:Google Analytics API into R

Interact with the Google Analytics APIs <https://developers.google.com/analytics/>, including the Core Reporting API (v3 and v4), Management API, User Activity API GA4's Data API and Admin API and Multi-Channel Funnel API.

Maintained by Erik Grönroos. Last updated 6 months ago.

analytics api google googleanalyticsr googleauthr

9.2 match 262 stars 10.11 score 680 scripts 1 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.

microscopy profiling

13.5 match 50 stars 6.89 score 44 scripts

rstudio

renv:Project Environments

A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.

Maintained by Kevin Ushey. Last updated 4 days ago.

5.0 match 1.0k stars 18.55 score 1.5k scripts 113 dependents

dexter-psychometrics

dexter:Data Management and Analysis of Tests

A system for the management, assessment, and psychometric analysis of data from educational and psychological tests.

Maintained by Jesse Koops. Last updated 6 days ago.

openblas cpp openmp

10.3 match 8 stars 8.97 score 135 scripts 2 dependents

mayer79

flashlight:Shed Light on Black Box Machine Learning Models

Shed light on black box machine learning models by the help of model performance, variable importance, global surrogate models, ICE profiles, partial dependence (Friedman J. H. (2001) <doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W. (2016) <arXiv:1612.08468>), further effects plots, interaction strength, and variable contribution breakdown (Gosiewska and Biecek (2019) <arxiv:1903.11420>). All tools are implemented to work with case weights and allow for stratified analysis. Furthermore, multiple flashlights can be combined and analyzed together.

Maintained by Michael Mayer. Last updated 8 months ago.

interpretability interpretable-machine-learning machine-learning xai

14.5 match 22 stars 6.25 score 54 scripts 1 dependents

atmoschem

vein:Vehicular Emissions Inventories

Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.

Maintained by Sergio Ibarra-Espinosa. Last updated 2 hours ago.

atmoschem atmospheric-chemistry atmospheric-science atmospheric-sciences emissions emissions-model vehicular-emissions-inventories vein fortran openmp

10.4 match 46 stars 8.69 score 137 scripts

phaegeli

sarp.snowprofile:Snow Profile Analysis for Snowpack and Avalanche Research

Analysis and plotting tools for snow profile data produced from manual snowpack observations and physical snowpack models. The functions in this package support snowpack and avalanche research by reading various formats of data (including CAAML, SMET, generic csv, and outputs from the snow cover model SNOWPACK), manipulate the data, and produce graphics such as stratigraphy and time series profiles. Package developed by the Simon Fraser University Avalanche Research Program <http://www.avalancheresearch.ca>. Graphics apply visualization concepts from Horton, Nowak, and Haegeli (2020, <doi:10.5194/nhess-20-1557-2020>).

Maintained by Pascal Haegeli. Last updated 2 years ago.

25.9 match 3.48 score 4 scripts 2 dependents

moosa-r

rbioapi:User-Friendly R Interface to Biologic Web Services' API

Currently fully supports Enrichr, JASPAR, miEAA, PANTHER, Reactome, STRING, and UniProt! The goal of rbioapi is to provide a user-friendly and consistent interface to biological databases and services. In a way that insulates the user from the technicalities of using web services API and creates a unified and easy-to-use interface to biological and medical web services. This is an ongoing project; New databases and services will be added periodically. Feel free to suggest any databases or services you often use.

Maintained by Moosa Rezwani. Last updated 1 months ago.

api-client bioinformatics biology enrichment enrichment-analysis enrichr jaspar mieaa over-representation-analysis panther reactome string uniprot

11.8 match 20 stars 7.60 score 55 scripts

bioc

bioCancer:Interactive Multi-Omics Cancers Data Visualization and Analysis

This package is a Shiny App to visualize and analyse interactively Multi-Assays of Cancer Genomic Data.

Maintained by Karim Mezhoud. Last updated 5 months ago.

gui datarepresentation network multiplecomparison pathways reactome visualization geneexpression genetarget analysis biocancer-interface cancer cancer-studies rmarkdown

15.1 match 20 stars 5.95 score 7 scripts

cvasi-tktd

cvasi:Calibration, Validation, and Simulation of TKTD Models

Eases the use of ecotoxicological effect models. Can simulate common toxicokinetic-toxicodynamic (TK/TD) models such as General Unified Threshold models of Survival (GUTS) and Lemna. It can derive effects and effect profiles (EPx) from scenarios. It supports the use of 'tidyr' workflows employing the pipe symbol. Time-consuming tasks can be parallelized.

Maintained by Nils Kehrein. Last updated 5 days ago.

ecotoxicology modeling simulation

14.2 match 2 stars 6.26 score 12 scripts

tyee001

VGAM:Vector Generalized Linear and Additive Models

An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (100+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.

Maintained by Thomas Yee. Last updated 1 months ago.

fortran

8.3 match 10 stars 10.67 score 3.6k scripts 169 dependents

modeloriented

survex:Explainable Machine Learning in Survival Analysis

Survival analysis models are commonly used in medicine and other areas. Many of them are too complex to be interpreted by human. Exploration and explanation is needed, but standard methods do not give a broad enough picture. 'survex' provides easy-to-apply methods for explaining survival models, both complex black-boxes and simpler statistical models. They include methods specific to survival analysis such as SurvSHAP(t) introduced in Krzyzinski et al., (2023) <doi:10.1016/j.knosys.2022.110234>, SurvLIME described in Kovalev et al., (2020) <doi:10.1016/j.knosys.2020.106164> as well as extensions of existing ones described in Biecek et al., (2021) <doi:10.1201/9780429027192>.

Maintained by Mikołaj Spytek. Last updated 9 months ago.

biostatistics brier-scores censored-data cox-model cox-regression explainable-ai explainable-machine-learning explainable-ml explanatory-model-analysis interpretable-machine-learning interpretable-ml machine-learning probabilistic-machine-learning shap survival-analysis time-to-event variable-importance xai

10.4 match 110 stars 8.40 score 114 scripts

paws-r

paws:Amazon Web Services Software Development Kit

Interface to Amazon Web Services <https://aws.amazon.com>, including storage, database, and compute services, such as 'Simple Storage Service' ('S3'), 'DynamoDB' 'NoSQL' database, and 'Lambda' functions-as-a-service.

Maintained by Dyfan Jones. Last updated 4 days ago.

aws aws-sdk

7.8 match 332 stars 11.25 score 177 scripts 12 dependents

hadley

profr:An Alternative Display for Profiling Information

An alternative data structure and visual rendering for the profiling information generated by Rprof.

Maintained by Hadley Wickham. Last updated 6 years ago.

16.8 match 30 stars 5.12 score 87 scripts

r-prof

proffer:Profile R Code and Visualize with 'Pprof'

Like similar profiling tools, the 'proffer' package automatically detects sources of slowness in R code. The distinguishing feature of 'proffer' is its utilization of 'pprof', which supplies interactive visualizations that are efficient and easy to interpret. Behind the scenes, the 'profile' package converts native Rprof() data to a protocol buffer that 'pprof' understands. For the documentation of 'proffer', visit <https://r-prof.github.io/proffer/>. To learn about the implementations and methodologies of 'pprof', 'profile', and protocol buffers, visit <https://github.com/google/pprof>. <https://protobuf.dev>, and <https://github.com/r-prof/profile>, respectively.

Maintained by William Michael Landau. Last updated 4 months ago.

13.0 match 88 stars 6.40 score 48 scripts

sfcheung

semlbci:Likelihood-Based Confidence Interval in Structural Equation Models

Forms likelihood-based confidence intervals (LBCIs) for parameters in structural equation modeling, introduced in Cheung and Pesigan (2023) <doi:10.1080/10705511.2023.2183860>. Currently implements the algorithm illustrated by Pek and Wu (2018) <doi:10.1037/met0000163>, and supports the robust LBCI proposed by Falk (2018) <doi:10.1080/10705511.2017.1367254>.

Maintained by Shu Fai Cheung. Last updated 2 months ago.

confidence-intervals lavaan likelihood-based profile-likelihood structural-equation-modeling

13.8 match 1 stars 5.93 score 188 scripts

cran

raws.profile:Managing Profiles on Amazon Web Service

This is an R wrapper from the AWS Command Line Interface that provides methods to manage the user configuration on Amazon Web Service. You can create as many profiles as you want, manage them, and delete them. The profiles created with this tool work with all AWS products such as S3, Glacier, and EC2. It also provides a function to automatically install AWS CLI, but you can download it and install it manually if you prefer.

Maintained by Samuel Macedo. Last updated 6 years ago.

47.5 match 1.70 score

ropensci

RSelenium:R Bindings for 'Selenium WebDriver'

Provides a set of R bindings for the 'Selenium 2.0 WebDriver' (see <https://www.selenium.dev/documentation/> for more information) using the 'JsonWireProtocol' (see <https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol> for more information). 'Selenium 2.0 WebDriver' allows driving a web browser natively as a user would either locally or on a remote machine using the Selenium server it marks a leap forward in terms of web browser automation. Selenium automates web browsers (commonly referred to as browsers). Using RSelenium you can automate browsers locally or remotely.

Maintained by Jonathan Völkle. Last updated 2 years ago.

rselenium selenium webdriver

6.0 match 344 stars 13.38 score 1.9k scripts 12 dependents

nanxstats

protr:Generating Various Numerical Representation Schemes for Protein Sequences

Comprehensive toolkit for generating various numerical features of protein sequences described in Xiao et al. (2015) <DOI:10.1093/bioinformatics/btv042>. For full functionality, the software 'ncbi-blast+' is needed, see <https://blast.ncbi.nlm.nih.gov/doc/blast-help/downloadblastdata.html> for more information.

Maintained by Nan Xiao. Last updated 6 months ago.

bioinformatics feature-engineering feature-extraction machine-learning peptides protein-sequences sequence-analysis

7.9 match 52 stars 10.02 score 173 scripts 3 dependents

rstudio

pointblank:Data Validation and Organization of Metadata for Local and Remote Tables

Validate data in data frames, 'tibble' objects, 'Spark' 'DataFrames', and database tables. Validation pipelines can be made using easily-readable, consecutive validation steps. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions. Many other workflows are available including an information management workflow, where the aim is to record, collect, and generate useful information on data tables.

Maintained by Richard Iannone. Last updated 10 days ago.

data-assertions data-checker data-dictionaries data-frames data-inference data-management data-profiler data-quality data-validation data-verification database-tables easy-to-understand reporting-tool schema-validation testing-tools yaml-configuration

7.5 match 932 stars 10.59 score 284 scripts

irinagain

iglu:Interpreting Glucose Data from Continuous Glucose Monitors

Implements a wide range of metrics for measuring glucose control and glucose variability based on continuous glucose monitoring data. The list of implemented metrics is summarized in Rodbard (2009) <doi:10.1089/dia.2009.0015>. Additional visualization tools include time-series plots, lasagna plots and ambulatory glucose profile report.

Maintained by Irina Gaynanova. Last updated 11 days ago.

8.8 match 26 stars 9.00 score 39 scripts

bioc

mia:Microbiome analysis

mia implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.

Maintained by Tuomas Borman. Last updated 3 days ago.

microbiome software dataimport analysis bioconductor

6.8 match 52 stars 11.50 score 316 scripts 5 dependents

rinterface

shinydashboardPlus:Add More 'AdminLTE2' Components to 'shinydashboard'

Extend 'shinydashboard' with 'AdminLTE2' components. 'AdminLTE2' is a free 'Bootstrap 3' dashboard template available at <https://adminlte.io>. Customize boxes, add timelines and a lot more.

Maintained by David Granjon. Last updated 8 months ago.

dashboard hacktoberfest2022 shiny shiny-apps shinydashboard

5.7 match 459 stars 13.79 score 1.1k scripts 28 dependents

mrc-ide

malariasimulation:An individual based model for malaria

Specifies the latest and greatest malaria model.

Maintained by Giovanni Charles. Last updated 28 days ago.

cpp

9.6 match 16 stars 8.17 score 146 scripts

bioc

DTA:Dynamic Transcriptome Analysis

Dynamic Transcriptome Analysis (DTA) can monitor the cellular response to perturbations with higher sensitivity and temporal resolution than standard transcriptomics. The package implements the underlying kinetic modeling approach capable of the precise determination of synthesis- and decay rates from individual microarray or RNAseq measurements.

Maintained by Bjoern Schwalb. Last updated 5 months ago.

microarray differentialexpression geneexpression transcription

16.3 match 4.78 score 5 scripts 1 dependents

yiluheihei

RevEcoR:Reverse Ecology Analysis on Microbiome

An implementation of the reverse ecology framework. Reverse ecology refers to the use of genomics to study ecology with no a priori assumptions about the organism(s) under consideration, linking organisms to their environment. It allows researchers to reconstruct the metabolic networks and study the ecology of poorly characterized microbial species from their genomic information, and has substantial potentials for microbial community ecological analysis.

Maintained by Yang Cao. Last updated 6 years ago.

13.4 match 6 stars 5.77 score 22 scripts 1 dependents

rkillick

changepoint:Methods for Changepoint Detection

Implements various mainstream and specialised changepoint methods for finding single and multiple changepoints within data. Many popular non-parametric and frequentist methods are included. The cpt.mean(), cpt.var(), cpt.meanvar() functions should be your first point of call.

Maintained by Rebecca Killick. Last updated 3 months ago.

changepoint segmentation

7.0 match 133 stars 11.05 score 736 scripts 40 dependents

lme4

lme4:Linear Mixed-Effects Models using 'Eigen' and S4

Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Maintained by Ben Bolker. Last updated 3 days ago.

cpp

3.6 match 647 stars 20.69 score 35k scripts 1.5k dependents

bioc

MSstatsPTM:Statistical Characterization of Post-translational Modifications

MSstatsPTM provides general statistical methods for quantitative characterization of post-translational modifications (PTMs). Supports DDA, DIA, SRM, and tandem mass tag (TMT) labeling. Typically, the analysis involves the quantification of PTM sites (i.e., modified residues) and their corresponding proteins, as well as the integration of the quantification results. MSstatsPTM provides functions for summarization, estimation of PTM site abundance, and detection of changes in PTMs across experimental conditions.

Maintained by Devon Kohler. Last updated 4 months ago.

immunooncology massspectrometry proteomics software differentialexpression onechannel twochannel normalization qualitycontrol post-translational-modification cpp

9.2 match 10 stars 7.98 score 36 scripts 2 dependents

diegommcc

SpatialDDLS:Deconvolution of Spatial Transcriptomics Data Based on Neural Networks

Deconvolution of spatial transcriptomics data based on neural networks and single-cell RNA-seq data. SpatialDDLS implements a workflow to create neural network models able to make accurate estimates of cell composition of spots from spatial transcriptomics data using deep learning and the meaningful information provided by single-cell RNA-seq data. See Torroja and Sanchez-Cabo (2019) <doi:10.3389/fgene.2019.00978> and Mañanes et al. (2024) <doi:10.1093/bioinformatics/btae072> to get an overview of the method and see some examples of its performance.

Maintained by Diego Mañanes. Last updated 5 months ago.

deconvolution deep-learning neural-network spatial-transcriptomics

14.7 match 5 stars 5.00 score 1 scripts

lbelzile

mev:Modelling of Extreme Values

Various tools for the analysis of univariate, multivariate and functional extremes. Exact simulation from max-stable processes [Dombry, Engelke and Oesting (2016) <doi:10.1093/biomet/asw008>, R-Pareto processes for various parametric models, including Brown-Resnick (Wadsworth and Tawn, 2014, <doi:10.1093/biomet/ast042>) and Extremal Student (Thibaud and Opitz, 2015, <doi:10.1093/biomet/asv045>). Threshold selection methods, including Wadsworth (2016) <doi:10.1080/00401706.2014.998345>, and Northrop and Coleman (2014) <doi:10.1007/s10687-014-0183-z>. Multivariate extreme diagnostics. Estimation and likelihoods for univariate extremes, e.g., Coles (2001) <doi:10.1007/978-1-4471-3675-0>.

Maintained by Leo Belzile. Last updated 5 months ago.

extreme-value-statistics likelihood-functions max-stable simulation threshold-selection openblas cpp openmp

8.9 match 13 stars 8.23 score 94 scripts 4 dependents

cpanse

protViz:Visualizing and Analyzing Mass Spectrometry Related Data in Proteomics

Helps with quality checks, visualizations and analysis of mass spectrometry data, coming from proteomics experiments. The package is developed, tested and used at the Functional Genomics Center Zurich <https://fgcz.ch>. We use this package mainly for prototyping, teaching, and having fun with proteomics data. But it can also be used to do data analysis for small scale data sets.

Maintained by Christian Panse. Last updated 1 years ago.

fun mass-spectrometry peptide-identification proteomics quantification visualization cpp

9.2 match 11 stars 7.88 score 72 scripts 2 dependents

bioc

TargetSearch:A package for the analysis of GC-MS metabolite profiling data

This packages provides a flexible, fast and accurate method for targeted pre-processing of GC-MS data. The user provides a (often very large) set of GC chromatograms and a metabolite library of targets. The package will automatically search those targets in the chromatograms resulting in a data matrix that can be used for further data analysis.

Maintained by Alvaro Cuadros-Inostroza. Last updated 4 months ago.

massspectrometry preprocessing decisiontree immunooncology bioc bioconductor gc-ms mass-spectrometry

9.7 match 4 stars 7.42 score 3 scripts

bioc

kebabs:Kernel-Based Analysis of Biological Sequences

The package provides functionality for kernel-based analysis of DNA, RNA, and amino acid sequences via SVM-based methods. As core functionality, kebabs implements following sequence kernels: spectrum kernel, mismatch kernel, gappy pair kernel, and motif kernel. Apart from an efficient implementation of standard position-independent functionality, the kernels are extended in a novel way to take the position of patterns into account for the similarity measure. Because of the flexibility of the kernel formulation, other kernels like the weighted degree kernel or the shifted weighted degree kernel with constant weighting of positions are included as special cases. An annotation-specific variant of the kernels uses annotation information placed along the sequence together with the patterns in the sequence. The package allows for the generation of a kernel matrix or an explicit feature representation in dense or sparse format for all available kernels which can be used with methods implemented in other R packages. With focus on SVM-based methods, kebabs provides a framework which simplifies the usage of existing SVM implementations in kernlab, e1071, and LiblineaR. Binary and multi-class classification as well as regression tasks can be used in a unified way without having to deal with the different functions, parameters, and formats of the selected SVM. As support for choosing hyperparameters, the package provides cross validation - including grouped cross validation, grid search and model selection functions. For easier biological interpretation of the results, the package computes feature weights for all SVMs and prediction profiles which show the contribution of individual sequence positions to the prediction result and indicate the relevance of sequence sections for the learning result and the underlying biological functions.

Maintained by Ulrich Bodenhofer. Last updated 5 months ago.

supportvectormachine classification clustering regression cpp

10.9 match 6.58 score 47 scripts 3 dependents

bioc

PrInCE:Predicting Interactomes from Co-Elution

PrInCE (Predicting Interactomes from Co-Elution) uses a naive Bayes classifier trained on dataset-derived features to recover protein-protein interactions from co-elution chromatogram profiles. This package contains the R implementation of PrInCE.

Maintained by Michael Skinnider. Last updated 5 months ago.

proteomics systemsbiology networkinference

11.3 match 8 stars 6.38 score 25 scripts

refunders

refund:Regression with Functional Data

Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.

Maintained by Julia Wrobel. Last updated 6 months ago.

6.9 match 41 stars 10.25 score 472 scripts 16 dependents

dsstoffer

astsa:Applied Statistical Time Series Analysis

Contains data sets and scripts for analyzing time series in both the frequency and time domains including state space modeling as well as supporting the texts Time Series Analysis and Its Applications: With R Examples (5th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2025, <https://link.springer.com/book/9783031705830>, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, <DOI:10.1201/9780429273285>.

Maintained by David Stoffer. Last updated 2 months ago.

9.0 match 7 stars 7.86 score 2.2k scripts 8 dependents

cran

evd:Functions for Extreme Value Distributions

Extends simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models.

Maintained by Alec Stephenson. Last updated 6 months ago.

7.4 match 2 stars 9.46 score 748 scripts 82 dependents

bioc

ChIPanalyser:ChIPanalyser: Predicting Transcription Factor Binding Sites

ChIPanalyser is a package to predict and understand TF binding by utilizing a statistical thermodynamic model. The model incorporates 4 main factors thought to drive TF binding: Chromatin State, Binding energy, Number of bound molecules and a scaling factor modulating TF binding affinity. Taken together, ChIPanalyser produces ChIP-like profiles that closely mimic the patterns seens in real ChIP-seq data.

Maintained by Patrick C.N. Martin. Last updated 5 months ago.

software biologicalquestion workflowstep transcription sequencing chiponchip coverage alignment chipseq sequencematching dataimport peakdetection

16.0 match 4.38 score 12 scripts

pablo14

funModeling:Exploratory Data Analysis and Data Preparation Tool-Box

Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book Data Science Live Book (<https://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.

Maintained by Pablo Casas. Last updated 2 years ago.

8.1 match 100 stars 8.57 score 654 scripts

choileena

ProfileLikelihood:Profile Likelihood for a Parameter in Commonly Used Statistical Models

Provides profile likelihoods for a parameter of interest in commonly used statistical models. The models include linear models, generalized linear models, proportional odds models, linear mixed-effects models, and linear models for longitudinal responses fitted by generalized least squares. The package also provides plots for normalized profile likelihoods as well as the maximum profile likelihood estimates and the kth likelihood support intervals.

Maintained by Leena Choi. Last updated 2 years ago.

24.9 match 2.80 score 21 scripts 1 dependents

kharchenkolab

numbat:Haplotype-Aware CNV Analysis from scRNA-Seq

A computational method that infers copy number variations (CNVs) in cancer scRNA-seq data and reconstructs the tumor phylogeny. 'numbat' integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. 'numbat' can be used to: 1. detect allele-specific copy number variations from single-cells; 2. differentiate tumor versus normal cells in the tumor microenvironment; 3. infer the clonal architecture and evolutionary history of profiled tumors. 'numbat' does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). Additional examples and documentations are available at <https://kharchenkolab.github.io/numbat/>. For details on the method please see Gao et al. Nature Biotechnology (2022) <doi:10.1038/s41587-022-01468-y>.

Maintained by Teng Gao. Last updated 17 days ago.

cancer-genomics cnv-detection lineage-tracing phylogeny single-cell single-cell-analysis single-cell-rna-seq spatial-transcriptomics cpp

9.2 match 179 stars 7.41 score 120 scripts

r-spatial

spatialreg:Spatial Regression Analysis

A collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in 'spdep'. These model fitting functions include maximum likelihood methods for cross-sectional models proposed by 'Cliff' and 'Ord' (1973, ISBN:0850860369) and (1981, ISBN:0850860814), fitting methods initially described by 'Ord' (1975) <doi:10.1080/01621459.1975.10480272>. The models are further described by 'Anselin' (1988) <doi:10.1007/978-94-015-7799-1>. Spatial two stage least squares and spatial general method of moment models initially proposed by 'Kelejian' and 'Prucha' (1998) <doi:10.1023/A:1007707430416> and (1999) <doi:10.1111/1468-2354.00027> are provided. Impact methods and MCMC fitting methods proposed by 'LeSage' and 'Pace' (2009) <doi:10.1201/9781420064254> are implemented for the family of cross-sectional spatial regression models. Methods for fitting the log determinant term in maximum likelihood and MCMC fitting are compared by 'Bivand et al.' (2013) <doi:10.1111/gean.12008>, and model fitting methods by 'Bivand' and 'Piras' (2015) <doi:10.18637/jss.v063.i18>; both of these articles include extensive lists of references. A recent review is provided by 'Bivand', 'Millo' and 'Piras' (2021) <doi:10.3390/math9111276>. 'spatialreg' >= 1.1-* corresponded to 'spdep' >= 1.1-1, in which the model fitting functions were deprecated and passed through to 'spatialreg', but masked those in 'spatialreg'. From versions 1.2-*, the functions have been made defunct in 'spdep'. From version 1.3-6, add Anselin-Kelejian (1997) test to `stsls` for residual spatial autocorrelation <doi:10.1177/016001769702000109>.

Maintained by Roger Bivand. Last updated 4 days ago.

bayesian impacts maximum-likelihood spatial-dependence spatial-econometrics spatial-regression openblas

5.3 match 46 stars 12.92 score 916 scripts 24 dependents

bioc

cBioPortalData:Exposes and Makes Available Data from the cBioPortal Web Resources

The cBioPortalData R package accesses study datasets from the cBio Cancer Genomics Portal. It accesses the data either from the pre-packaged zip / tar files or from the API interface that was recently implemented by the cBioPortal Data Team. The package can provide data in either tabular format or with MultiAssayExperiment object that uses familiar Bioconductor data representations.

Maintained by Marcel Ramos. Last updated 10 days ago.

software infrastructure thirdpartyclient bioconductor-package nci-itcr u24ca289073

6.7 match 33 stars 10.15 score 147 scripts 4 dependents

r-lib

gtable:Arrange 'Grobs' in Tables

Tools to make it easier to work with "tables" of 'grobs'. The 'gtable' package defines a 'gtable' grob class that specifies a grid along with a list of grobs and their placement in the grid. Further the package makes it easy to manipulate and combine 'gtable' objects so that complex compositions can be built up sequentially.

Maintained by Thomas Lin Pedersen. Last updated 5 months ago.

3.8 match 91 stars 18.09 score 4.1k scripts 7.6k dependents

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 6 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

5.0 match 13.40 score 17k scripts 255 dependents

ikosmidis

profileModel:Profiling Inference Functions for Various Model Classes

Provides tools that can be used to calculate, evaluate, plot and use for inference the profiles of *arbitrary* inference functions for *arbitrary* 'glm'-like fitted models with linear predictors. More information on the methods that are implemented can be found in Kosmidis (2008) <https://www.r-project.org/doc/Rnews/Rnews_2008-2.pdf>.

Maintained by Ioannis Kosmidis. Last updated 4 years ago.

14.4 match 4.69 score 20 scripts 12 dependents

benjaminrich

linpk:Generate Concentration-Time Profiles from Linear PK Systems

Generate concentration-time profiles from linear pharmacokinetic (PK) systems, possibly with first-order absorption or zero-order infusion, possibly with one or more peripheral compartments, and possibly under steady-state conditions. Single or multiple doses may be specified. Secondary (derived) PK parameters (e.g. Cmax, Ctrough, AUC, Tmax, half-life, etc.) are computed.

Maintained by Benjamin Rich. Last updated 11 months ago.

13.5 match 10 stars 4.90 score 16 scripts

kleebaum

geoelectrics:3D-Visualization of Geoelectric Resistivity Measurement Profiles

Visualizes two-dimensional geoelectric resistivity measurement profiles in three dimensions.

Maintained by Anja Kleebaum. Last updated 2 years ago.

15.5 match 13 stars 4.28 score 29 scripts

cjvanlissa

tidySEM:Tidy Structural Equation Modeling

A tidy workflow for generating, estimating, reporting, and plotting structural equation models using 'lavaan', 'OpenMx', or 'Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as 'tidy' data, making them easy to customize. Includes functionality to estimate latent class analyses, and to plot 'dagitty' and 'igraph' objects.

Maintained by Caspar J. van Lissa. Last updated 8 days ago.

6.1 match 58 stars 10.69 score 330 scripts 1 dependents

yufree

enviGCMS:GC/LC-MS Data Analysis for Environmental Science

Gas/Liquid Chromatography-Mass Spectrometer(GC/LC-MS) Data Analysis for Environmental Science. This package covered topics such molecular isotope ratio, matrix effects and Short-Chain Chlorinated Paraffins analysis etc. in environmental analysis.

Maintained by Miao YU. Last updated 2 months ago.

environment mass-spectrometry metabolomics

9.9 match 17 stars 6.49 score 30 scripts 1 dependents

tsmodels

tsdistributions:Location Scale Standardized Distributions

Location-Scale based distributions parameterized in terms of mean, standard deviation, skew and shape parameters and estimation using automatic differentiation. Distributions include the Normal, Student and GED as well as their skewed variants ('Fernandez and Steel'), the 'Johnson SU', and the Generalized Hyperbolic. Also included is the semi-parametric piece wise distribution ('spd') with Pareto tails and kernel interior.

Maintained by Alexios Galanos. Last updated 4 months ago.

distributions finance probability-distribution probability-distributions statistical-distributions timeseries cpp

9.6 match 4 stars 6.66 score 19 scripts 2 dependents

bioc

rCGH:Comprehensive Pipeline for Analyzing and Visualizing Array-Based CGH Data

A comprehensive pipeline for analyzing and interactively visualizing genomic profiles generated through commercial or custom aCGH arrays. As inputs, rCGH supports Agilent dual-color Feature Extraction files (.txt), from 44 to 400K, Affymetrix SNP6.0 and cytoScanHD probeset.txt, cychp.txt, and cnchp.txt files exported from ChAS or Affymetrix Power Tools. rCGH also supports custom arrays, provided data complies with the expected format. This package takes over all the steps required for individual genomic profiles analysis, from reading files to profiles segmentation and gene annotations. This package also provides several visualization functions (static or interactive) which facilitate individual profiles interpretation. Input files can be in compressed format, e.g. .bz2 or .gz.

Maintained by Frederic Commo. Last updated 5 months ago.

acgh copynumbervariation preprocessing featureextraction

12.5 match 4 stars 5.10 score 26 scripts 1 dependents

openanalytics

clinDataReview:Clinical Data Review Tool

Creation of interactive tables, listings and figures ('TLFs') and associated report for exploratory analysis of data in a clinical trial, e.g. for clinical oversight activities. Interactive figures include sunburst, treemap, scatterplot, line plot and barplot of counts data. Interactive tables include table of summary statistics (as counts of adverse events, enrollment table) and listings. Possibility to compare data (summary table or listing) across two data batches/sets. A clinical data review report is created via study-specific configuration files and template 'R Markdown' reports contained in the package.

Maintained by Laure Cougnaud. Last updated 9 months ago.

9.0 match 11 stars 7.10 score 36 scripts

bioc

recoup:An R package for the creation of complex genomic profile plots

recoup calculates and plots signal profiles created from short sequence reads derived from Next Generation Sequencing technologies. The profiles provided are either sumarized curve profiles or heatmap profiles. Currently, recoup supports genomic profile plots for reads derived from ChIP-Seq and RNA-Seq experiments. The package uses ggplot2 and ComplexHeatmap graphics facilities for curve and heatmap coverage profiles respectively.

Maintained by Panagiotis Moulos. Last updated 5 months ago.

immunooncology software geneexpression preprocessing qualitycontrol rnaseq chipseq sequencing coverage atacseq chiponchip alignment dataimport

12.7 match 1 stars 5.02 score 2 scripts

bioc

idpr:Profiling and Analyzing Intrinsically Disordered Proteins in R

‘idpr’ aims to integrate tools for the computational analysis of intrinsically disordered proteins (IDPs) within R. This package is used to identify known characteristics of IDPs for a sequence of interest with easily reported and dynamic results. Additionally, this package includes tools for IDP-based sequence analysis to be used in conjunction with other R packages. Described in McFadden WM & Yanowitz JL (2022). "idpr: A package for profiling and analyzing Intrinsically Disordered Proteins in R." PloS one, 17(4), e0266929. <https://doi.org/10.1371/journal.pone.0266929>.

Maintained by William M. McFadden. Last updated 5 months ago.

structuralprediction proteomics cellbiology

10.1 match 4 stars 6.16 score 20 scripts

bioc

cogena:co-expressed gene-set enrichment analysis

cogena is a workflow for co-expressed gene-set enrichment analysis. It aims to discovery smaller scale, but highly correlated cellular events that may be of great biological relevance. A novel pipeline for drug discovery and drug repositioning based on the cogena workflow is proposed. Particularly, candidate drugs can be predicted based on the gene expression of disease-related data, or other similar drugs can be identified based on the gene expression of drug-related data. Moreover, the drug mode of action can be disclosed by the associated pathway analysis. In summary, cogena is a flexible workflow for various gene set enrichment analysis for co-expressed genes, with a focus on pathway/GO analysis and drug repositioning.

Maintained by Zhilong Jia. Last updated 5 months ago.

clustering genesetenrichment geneexpression visualization pathways kegg go microarray sequencing systemsbiology datarepresentation dataimport bioconductor bioinformatics

8.4 match 12 stars 7.36 score 32 scripts

bioc

Rcpi:Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery

A molecular informatics toolkit with an integration of bioinformatics and chemoinformatics tools for drug discovery.

Maintained by Nan Xiao. Last updated 5 months ago.

software dataimport datarepresentation featureextraction cheminformatics biomedicalinformatics proteomics go systemsbiology bioconductor bioinformatics drug-discovery feature-extraction fingerprint molecular-descriptors protein-sequences

7.8 match 37 stars 7.81 score 29 scripts

bioc

syntenet:Inference And Analysis Of Synteny Networks

syntenet can be used to infer synteny networks from whole-genome protein sequences and analyze them. Anchor pairs are detected with the MCScanX algorithm, which was ported to this package with the Rcpp framework for R and C++ integration. Anchor pairs from synteny analyses are treated as an undirected unweighted graph (i.e., a synteny network), and users can perform: i. network clustering; ii. phylogenomic profiling (by identifying which species contain which clusters) and; iii. microsynteny-based phylogeny reconstruction with maximum likelihood.

Maintained by Fabrício Almeida-Silva. Last updated 3 months ago.

software networkinference functionalgenomics comparativegenomics phylogenetics systemsbiology graphandnetwork wholegenome network comparative-genomics evolutionary-genomics network-science phylogenomics synteny synteny-network cpp

9.1 match 26 stars 6.67 score 12 scripts 1 dependents

bioc

GenomicPlot:Plot profiles of next generation sequencing data in genomic features

Visualization of next generation sequencing (NGS) data is essential for interpreting high-throughput genomics experiment results. 'GenomicPlot' facilitates plotting of NGS data in various formats (bam, bed, wig and bigwig); both coverage and enrichment over input can be computed and displayed with respect to genomic features (such as UTR, CDS, enhancer), and user defined genomic loci or regions. Statistical tests on signal intensity within user defined regions of interest can be performed and represented as boxplots or bar graphs. Parallel processing is used to speed up computation on multicore platforms. In addition to genomic plots which is suitable for displaying of coverage of genomic DNA (such as ChIPseq data), metagenomic (without introns) plots can also be made for RNAseq or CLIPseq data as well.

Maintained by Shuye Pu. Last updated 2 months ago.

alternativesplicing chipseq coverage geneexpression rnaseq sequencing software transcription visualization annotation

10.8 match 3 stars 5.62 score 4 scripts

bioc

DrugVsDisease:Comparison of disease and drug profiles using Gene set Enrichment Analysis

This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format.

Maintained by j. Saez-Rodriguez. Last updated 5 months ago.

microarray geneexpression clustering

18.1 match 3.30 score 8 scripts

bioc

GenomicSuperSignature:Interpretation of RNA-seq experiments through robust, efficient comparison to public databases

This package provides a novel method for interpreting new transcriptomic datasets through near-instantaneous comparison to public archives without high-performance computing requirements. Through the pre-computed index, users can identify public resources associated with their dataset such as gene sets, MeSH term, and publication. Functions to identify interpretable annotations and intuitive visualization options are implemented in this package.

Maintained by Sehyun Oh. Last updated 5 months ago.

transcriptomics systemsbiology principalcomponent rnaseq sequencing pathways clustering bioconductor-package exploratory-data-analysis gsea mesh principal-component-analysis rna-sequencing-profiles transferlearning

8.5 match 16 stars 6.97 score 59 scripts

sammorrissette

SC2API:Blizzard SC2 API Wrapper

A wrapper for Blizzard's Starcraft II (a 2010 real-time strategy game) Application Programming Interface (API). All documented API calls are implemented in an easy-to-use and consistent manner.

Maintained by Samuel Morrissette. Last updated 4 years ago.

15.8 match 1 stars 3.70 score 4 scripts

bioc

DropletUtils:Utilities for Handling Single-Cell Droplet Data

Provides a number of utility functions for handling single-cell (RNA-seq) data from droplet technologies such as 10X Genomics. This includes data loading from count matrices or molecule information files, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.

Maintained by Jonathan Griffiths. Last updated 3 months ago.

immunooncology singlecell sequencing rnaseq geneexpression transcriptomics dataimport coverage zlib cpp

5.8 match 10.08 score 2.7k scripts 9 dependents

dgrun

FateID:Quantification of Fate Bias in Multipotent Progenitors

Application of 'FateID' allows computation and visualization of cell fate bias for multi-lineage single cell transcriptome data. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.

Maintained by Dominic Grün. Last updated 3 years ago.

8.9 match 22 stars 6.50 score 48 scripts 1 dependents

nlmixr2

nlmixr2extra:Nonlinear Mixed Effects Models in Population PK/PD, Extra Support Functions

Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>). This package is for support functions like preconditioned fits <doi:10.1208/s12248-016-9866-5>, boostrap and stepwise covariate selection.

Maintained by Matthew Fidler. Last updated 28 days ago.

openblas cpp

10.0 match 3 stars 5.80 score 11 scripts 5 dependents

ohdsi

EvidenceSynthesis:Synthesizing Causal Evidence in a Distributed Research Network

Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study, without sharing patient-level data. Allows for normal and non-normal approximations of the data-site likelihood of the effect parameter.

Maintained by Martijn Schuemie. Last updated 6 months ago.

hades openjdk

9.9 match 8 stars 5.87 score 31 scripts

cran

drc:Analysis of Dose-Response Curves

Analysis of dose-response data is made available through a suite of flexible and versatile model fitting and after-fitting functions.

Maintained by Christian Ritz. Last updated 9 years ago.

6.9 match 8 stars 8.39 score 1.4k scripts 28 dependents

revelle

psych:Procedures for Psychological, Psychometric, and Personality Research

A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r/> web page.

Maintained by William Revelle. Last updated 3 months ago.

4.1 match 52 stars 13.94 score 29k scripts 317 dependents

bioc

AlpsNMR:Automated spectraL Processing System for NMR

Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.

Maintained by Sergio Oller Moreno. Last updated 5 months ago.

software preprocessing visualization classification cheminformatics metabolomics dataimport

7.5 match 15 stars 7.59 score 12 scripts 1 dependents

cecileproust-lima

lcmm:Extended Mixed Models Using Latent Classes and Latent Processes

Estimation of various extensions of the mixed models including latent class mixed models, joint latent class mixed models, mixed models for curvilinear outcomes, mixed models for multivariate longitudinal outcomes using a maximum likelihood estimation method (Proust-Lima, Philipps, Liquet (2017) <doi:10.18637/jss.v078.i02>).

Maintained by Cecile Proust-Lima. Last updated 1 months ago.

fortran

5.0 match 62 stars 11.41 score 249 scripts 7 dependents

daniel-gerhard

mcprofile:Testing Generalized Linear Hypotheses for Generalized Linear Model Parameters by Profile Deviance

Calculation of signed root deviance profiles for linear combinations of parameters in a generalized linear model. Multiple tests and simultaneous confidence intervals are provided.

Maintained by Daniel Gerhard. Last updated 4 years ago.

confidence-intervals glm

11.7 match 1 stars 4.88 score 51 scripts 1 dependents

briencj

growthPheno:Functional Analysis of Phenotypic Growth Data to Smooth and Extract Traits

Assists in the plotting and functional smoothing of traits measured over time and the extraction of features from these traits, implementing the SET (Smoothing and Extraction of Traits) method described in Brien et al. (2020) Plant Methods, 16. Smoothing of growth trends for individual plants using natural cubic smoothing splines or P-splines is available for removing transient effects and segmented smoothing is available to deal with discontinuities in growth trends. There are graphical tools for assessing the adequacy of trait smoothing, both when using this and other packages, such as those that fit nonlinear growth models. A range of per-unit (plant, pot, plot) growth traits or features can be extracted from the data, including single time points, interval growth rates and other growth statistics, such as maximum growth or days to maximum growth. The package also has tools adapted to inputting data from high-throughput phenotyping facilities, such from a Lemna-Tec Scananalyzer 3D (see <https://www.youtube.com/watch?v=MRAF_mAEa7E/> for more information). The package 'growthPheno' can also be installed from <http://chris.brien.name/rpackages/>.

Maintained by Chris Brien. Last updated 20 hours ago.

8.5 match 6 stars 6.66 score 42 scripts

arbrazzale

nlreg:Higher Order Inference for Nonlinear Heteroscedastic Models

Likelihood inference based on higher order approximations for nonlinear models with possibly non constant variance.

Maintained by Alessandra R. Brazzale. Last updated 6 years ago.

33.5 match 1.67 score 47 scripts

bioc

antiProfiles:Implementation of gene expression anti-profiles

Implements gene expression anti-profiles as described in Corrada Bravo et al., BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272.

Maintained by Hector Corrada Bravo. Last updated 5 months ago.

geneexpression classification

14.3 match 3.90 score

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

7.0 match 96 stars 7.89 score 268 scripts 1 dependents

kaihsianghu

iNEXT.4steps:Four-Step Biodiversity Analysis Based on 'iNEXT'

Expands 'iNEXT' to include the estimation of sample completeness and evenness. The package provides simple functions to perform the following four-step biodiversity analysis: STEP 1: Assessment of sample completeness profiles. STEP 2a: Analysis of size-based rarefaction and extrapolation sampling curves to determine whether the asymptotic diversity can be accurately estimated. STEP 2b: Comparison of the observed and the estimated asymptotic diversity profiles. STEP 3: Analysis of non-asymptotic coverage-based rarefaction and extrapolation sampling curves. STEP 4: Assessment of evenness profiles. The analyses in STEPs 2a, 2b and STEP 3 are mainly based on the previous 'iNEXT' package. Refer to the 'iNEXT' package for details. This package is mainly focusing on the computation for STEPs 1 and 4. See Chao et al. (2020) <doi:10.1111/1440-1703.12102> for statistical background.

Maintained by Anne Chao. Last updated 9 months ago.

9.1 match 4 stars 6.00 score 8 scripts

giorgilancs

PrevMap:Geostatistical Modelling of Spatially Referenced Prevalence Data

Provides functions for both likelihood-based and Bayesian analysis of spatially referenced prevalence data. For a tutorial on the use of the R package, see Giorgi and Diggle (2017) <doi:10.18637/jss.v078.i08>.

Maintained by Emanuele Giorgi. Last updated 2 years ago.

12.5 match 4.36 score 46 scripts

frictionlessdata

tableschema.r:Table Schema 'Frictionless Data'

Allows to work with 'Table Schema' (<https://specs.frictionlessdata.io/table-schema/>). 'Table Schema' is well suited for use cases around handling and validating tabular data in text formats such as 'csv', but its utility extends well beyond this core usage, towards a range of applications where data benefits from a portable schema format. The 'tableschema.r' package can load and validate any table schema descriptor, allow the creation and modification of descriptors, expose methods for reading and streaming data that conforms to a 'Table Schema' via the 'Tabular Data Resource' abstraction.

Maintained by Kleanthis Koupidis. Last updated 2 years ago.

9.5 match 25 stars 5.70 score 101 scripts

dzmitrygb

Repliscope:Replication Timing Profiling using DNA Copy Number

Create, Plot and Compare Replication Timing Profiles. The method is described in Muller et al., (2014) <doi: 10.1093/nar/gkt878>.

Maintained by Dzmitry G Batrakou. Last updated 3 years ago.

17.3 match 3.13 score 27 scripts

ericmarcon

divent:Entropy Partitioning to Measure Diversity

Measurement and partitioning of diversity, based on Tsallis entropy, following Marcon and Herault (2015) <doi:10.18637/jss.v067.i08>. 'divent' provides functions to estimate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity.

Maintained by Eric Marcon. Last updated 22 days ago.

cpp

11.2 match 1 stars 4.81 score 1 scripts

husson

SensoMineR:Sensory Data Analysis

Statistical Methods to Analyse Sensory Data. SensoMineR: A package for sensory data analysis. S. Le and F. Husson (2008).

Maintained by Francois Husson. Last updated 1 years ago.

9.1 match 5.72 score 108 scripts 3 dependents

bioc

GOexpress:Visualise microarray and RNAseq data using gene ontology annotations

The package contains methods to visualise the expression profile of genes from a microarray or RNA-seq experiment, and offers a supervised clustering approach to identify GO terms containing genes with expression levels that best classify two or more predefined groups of samples. Annotations for the genes present in the expression dataset may be obtained from Ensembl through the biomaRt package, if not provided by the user. The default random forest framework is used to evaluate the capacity of each gene to cluster samples according to the factor of interest. Finally, GO terms are scored by averaging the rank (alternatively, score) of their respective gene sets to cluster the samples. P-values may be computed to assess the significance of GO term ranking. Visualisation function include gene expression profile, gene ontology-based heatmaps, and hierarchical clustering of experimental samples using gene expression data.

Maintained by Kevin Rue-Albrecht. Last updated 5 months ago.

software geneexpression transcription differentialexpression genesetenrichment datarepresentation clustering timecourse microarray sequencing rnaseq annotation multiplecomparison pathways go visualization immunooncology bioconductor bioconductor-package bioconductor-stats geneontology geneset-enrichment

7.7 match 9 stars 6.75 score 31 scripts

cran

sn:The Skew-Normal and Related Distributions Such as the Skew-t and the SUN

Build and manipulate probability distributions of the skew-normal family and some related ones, notably the skew-t and the SUN families. For the skew-normal and the skew-t distributions, statistical methods are provided for data fitting and model diagnostics, in the univariate and the multivariate case.

Maintained by Adelchi Azzalini. Last updated 2 years ago.

7.0 match 3 stars 7.44 score 92 dependents

immunomind

immunarch:Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires

A comprehensive framework for bioinformatics exploratory analysis of bulk and single-cell T-cell receptor and antibody repertoires. It provides seamless data loading, analysis and visualisation for AIRR (Adaptive Immune Receptor Repertoire) data, both bulk immunosequencing (RepSeq) and single-cell sequencing (scRNAseq). Immunarch implements most of the widely used AIRR analysis methods, such as: clonality analysis, estimation of repertoire similarities in distribution of clonotypes and gene segments, repertoire diversity analysis, annotation of clonotypes using external immune receptor databases and clonotype tracking in vaccination and cancer studies. A successor to our previously published 'tcR' immunoinformatics package (Nazarov 2015) <doi:10.1186/s12859-015-0613-1>.

Maintained by Vadim I. Nazarov. Last updated 12 months ago.

airr-analysis b-cell-receptor bcr bcr-repertoire bioinformatics ig ig-repertoire immune-repertoire immune-repertoire-analysis immune-repertoire-data immunoglobulin immunoinformatics immunology rep-seq repertoire-analysis single-cell single-cell-analysis t-cell-receptor tcr tcr-repertoire cpp

5.4 match 315 stars 9.49 score 203 scripts

flrd

standardlastprofile:Data Package for BDEW Standard Load Profiles in Electricity

Data on standard load profiles from the German Association of Energy and Water Industries (BDEW Bundesverband der Energie- und Wasserwirtschaft e.V.) in a tidy format. The data and methodology are described in VDEW (1999), "Repräsentative VDEW-Lastprofile", <https://www.bdew.de/media/documents/1999_Repraesentative-VDEW-Lastprofile.pdf>. The package also offers an interface for generating a standard load profile over a user-defined period. For the algorithm, see VDEW (2000), "Anwendung der Repräsentativen VDEW-Lastprofile step-by-step", <https://www.bdew.de/media/documents/2000131_Anwendung-repraesentativen_Lastprofile-Step-by-step.pdf>.

Maintained by Markus Döring. Last updated 8 months ago.

data electricity germany

13.9 match 1 stars 3.70 score 4 scripts

pbiecek

ceterisParibus:Ceteris Paribus Profiles

Ceteris Paribus Profiles (What-If Plots) are designed to present model responses around selected points in a feature space. For example around a single prediction for an interesting observation. Plots are designed to work in a model-agnostic fashion, they are working for any predictive Machine Learning model and allow for model comparisons. Ceteris Paribus Plots supplement the Break Down Plots from 'breakDown' package.

Maintained by Przemyslaw Biecek. Last updated 5 years ago.

9.4 match 42 stars 5.48 score 36 scripts

r-forge

copula:Multivariate Dependence with Copulas

Classes (S4) of commonly used elliptical, Archimedean, extreme-value and other copula families, as well as their rotations, mixtures and asymmetrizations. Nested Archimedean copulas, related tools and special functions. Methods for density, distribution, random number generation, bivariate dependence measures, Rosenblatt transform, Kendall distribution function, perspective and contour plots. Fitting of copula models with potentially partly fixed parameters, including standard errors. Serial independence tests, copula specification tests (independence, exchangeability, radial symmetry, extreme-value dependence, goodness-of-fit) and model selection based on cross-validation. Empirical copula, smoothed versions, and non-parametric estimators of the Pickands dependence function.

Maintained by Martin Maechler. Last updated 12 days ago.

4.3 match 11.83 score 1.2k scripts 86 dependents

cysouw

qlcData:Processing Data for Quantitative Language Comparison

Functionality to read, recode, and transcode data as used in quantitative language comparison, specifically to deal with multilingual orthographic variation (Moran & Cysouw (2018) <doi:10.5281/zenodo.1296780>) and with the recoding of nominal data.

Maintained by Michael Cysouw. Last updated 9 months ago.

9.5 match 3 stars 5.38 score 40 scripts

bioc

TBSignatureProfiler:Profile RNA-Seq Data Using TB Pathway Signatures

Gene signatures of TB progression, TB disease, and other TB disease states have been validated and published previously. This package aggregates known signatures and provides computational tools to enlist their usage on other datasets. The TBSignatureProfiler makes it easy to profile RNA-Seq data using these signatures and includes common signature profiling tools including ASSIGN, GSVA, and ssGSEA. Original models for some gene signatures are also available. A shiny app provides some functionality alongside for detailed command line accessibility.

Maintained by Aubrey R. Odom. Last updated 3 months ago.

geneexpression differentialexpression bioconductor-package biomarkers gene-signatures tuberculosis

6.9 match 12 stars 7.25 score 23 scripts

rinterface

bs4Dash:A 'Bootstrap 4' Version of 'shinydashboard'

Make 'Bootstrap 4' Shiny dashboards. Use the full power of 'AdminLTE3', a dashboard template built on top of 'Bootstrap 4' <https://github.com/ColorlibHQ/AdminLTE>.

Maintained by David Granjon. Last updated 6 months ago.

bootstrap4 dashboard-templates hacktoberfest2022 shiny shiny-apps shinydashboard

3.9 match 442 stars 12.87 score 1.2k scripts 15 dependents

bioc

ASSIGN:Adaptive Signature Selection and InteGratioN (ASSIGN)

ASSIGN is a computational tool to evaluate the pathway deregulation/activation status in individual patient samples. ASSIGN employs a flexible Bayesian factor analysis approach that adapts predetermined pathway signatures derived either from knowledge-based literature or from perturbation experiments to the cell-/tissue-specific pathway signatures. The deregulation/activation level of each context-specific pathway is quantified to a score, which represents the extent to which a patient sample encompasses the pathway deregulation/activation signature.

Maintained by Ying Shen. Last updated 5 months ago.

software geneexpression pathways bayesian

6.8 match 2 stars 7.37 score 65 scripts 1 dependents

bioc

TPP2D:Detection of ligand-protein interactions from 2D thermal profiles (DLPTP)

Detection of ligand-protein interactions from 2D thermal profiles (DLPTP), Performs an FDR-controlled analysis of 2D-TPP experiments by functional analysis of dose-response curves across temperatures.

Maintained by Nils Kurzawa. Last updated 5 months ago.

software proteomics dataimport

11.7 match 4.20 score 16 scripts

spiwokv

metadynminer:Tools to Read, Analyze and Visualize Metadynamics HILLS Files from 'Plumed'

Metadynamics is a state of the art biomolecular simulation technique. 'Plumed' Tribello, G.A. et al. (2014) <doi:10.1016/j.cpc.2013.09.018> program makes it possible to perform metadynamics using various simulation codes. The results of metadynamics done in 'Plumed' can be analyzed by 'metadynminer'. The package 'metadynminer' reads 1D and 2D metadynamics hills files from 'Plumed' package. It uses a fast algorithm by Hosek, P. and Spiwok, V. (2016) <doi:10.1016/j.cpc.2015.08.037> to calculate a free energy surface from hills. Minima can be located and plotted on the free energy surface. Transition states can be analyzed by Nudged Elastic Band method by Henkelman, G. and Jonsson, H. (2000) <doi:10.1063/1.1323224>. Free energy surfaces, minima and transition paths can be plotted to produce publication quality images.

Maintained by Vojtech Spiwok. Last updated 1 years ago.

cpp

9.1 match 33 stars 5.35 score 45 scripts 1 dependents

bioc

limma:Linear Models for Microarray and Omics Data

Data analysis, linear models and differential expression for omics data.

Maintained by Gordon Smyth. Last updated 6 days ago.

exonarray geneexpression transcription alternativesplicing differentialexpression differentialsplicing genesetenrichment dataimport bayesian clustering regression timecourse microarray micrornaarray mrnamicroarray onechannel proprietaryplatforms twochannel sequencing rnaseq batcheffect multiplecomparison normalization preprocessing qualitycontrol biomedicalinformatics cellbiology cheminformatics epigenetics functionalgenomics genetics immunooncology metabolomics proteomics systemsbiology transcriptomics

3.5 match 13.81 score 16k scripts 585 dependents

mladenjovanovic

shorts:Short Sprints

Create short sprint acceleration-velocity (AVP) and force-velocity (FVP) profiles and predict kinematic and kinetic variables using the timing-gate split times, laser or radar gun data, tether devices data, as well as the data provided by the GPS and LPS monitoring systems. The modeling method utilized in this package is based on the works of Furusawa K, Hill AV, Parkinson JL (1927) <doi: 10.1098/rspb.1927.0035>, Greene PR. (1986) <doi: 10.1016/0025-5564(86)90063-5>, Chelly SM, Denis C. (2001) <doi: 10.1097/00005768-200102000-00024>, Clark KP, Rieger RH, Bruno RF, Stearne DJ. (2017) <doi: 10.1519/JSC.0000000000002081>, Samozino P. (2018) <doi: 10.1007/978-3-319-05633-3_11>, Samozino P. and Peyrot N., et al (2022) <doi: 10.1111/sms.14097>, Clavel, P., et al (2023) <doi: 10.1016/j.jbiomech.2023.111602>, Jovanovic M. (2023) <doi: 10.1080/10255842.2023.2170713>, Jovanovic M., et al (2024) <doi: 10.3390/s24092894>, and Jovanovic M., et al (2024) <doi: 10.3390/s24196192>.

Maintained by Mladen Jovanović. Last updated 5 months ago.

10.8 match 14 stars 4.45 score 4 scripts

limengbinggz

ddtlcm:Latent Class Analysis with Dirichlet Diffusion Tree Process Prior

Implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis. Reference: Li et al. (2023) <arXiv:2306.04700>.

Maintained by Mengbing Li. Last updated 8 months ago.

8.3 match 6 stars 5.80 score 8 scripts

bioc

DMRcaller:Differentially Methylated Regions caller

Uses Bisulfite sequencing data in two conditions and identifies differentially methylated regions between the conditions in CG and non-CG context. The input is the CX report files produced by Bismark and the output is a list of DMRs stored as GRanges objects.

Maintained by Nicolae Radu Zabet. Last updated 5 months ago.

differentialmethylation dnamethylation software sequencing coverage

11.8 match 4.08 score 8 scripts

shixiangwang

tinyscholar:Get and Show Personal 'Google Scholar' Profile

Provides functions to get personal 'Google Scholar' profile data from web API and show it in table or figure format.

Maintained by Shixiang Wang. Last updated 1 years ago.

google-scholar

10.4 match 8 stars 4.60 score 7 scripts

paulrougieux

FAOSTAT:Download Data from the FAOSTAT Database

Download Data from the FAOSTAT Database of the Food and Agricultural Organization (FAO) of the United Nations. A list of functions to download statistics from FAOSTAT (database of the FAO <https://www.fao.org/faostat/>) and WDI (database of the World Bank <https://data.worldbank.org/>), and to perform some harmonization operations.

Maintained by Paul Rougieux. Last updated 7 months ago.

9.0 match 5.30 score 132 scripts

anthonypileggi

casino:Play Casino Games

Play casino games in the R console, including poker, blackjack, and a slot machine. Try to build your fortune before you succumb to the gambler's ruin!

Maintained by Anthony Pileggi. Last updated 6 years ago.

9.9 match 10 stars 4.81 score 13 scripts

runehaubo

ordinal:Regression Models for Ordinal Data

Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence.

Maintained by Rune Haubo Bojesen Christensen. Last updated 3 months ago.

3.8 match 38 stars 12.41 score 1.3k scripts 178 dependents

bioc

SigsPack:Mutational Signature Estimation for Single Samples

Single sample estimation of exposure to mutational signatures. Exposures to known mutational signatures are estimated for single samples, based on quadratic programming algorithms. Bootstrapping the input mutational catalogues provides estimations on the stability of these exposures. The effect of the sequence composition of mutational context can be taken into account by normalising the catalogues.

Maintained by Franziska Schumann. Last updated 5 months ago.

somaticmutation snp variantannotation biomedicalinformatics dnaseq

10.9 match 2 stars 4.30 score 4 scripts

bioc

dada2:Accurate, high-resolution sample inference from amplicon sequencing data

The dada2 package infers exact amplicon sequence variants (ASVs) from high-throughput amplicon sequencing data, replacing the coarser and less accurate OTU clustering approach. The dada2 pipeline takes as input demultiplexed fastq files, and outputs the sequence variants and their sample-wise abundances after removing substitution and chimera errors. Taxonomic classification is available via a native implementation of the RDP naive Bayesian classifier, and species-level assignment to 16S rRNA gene fragments by exact matching.

Maintained by Benjamin Callahan. Last updated 5 months ago.

immunooncology microbiome sequencing classification metagenomics amplicon bioconductor bioinformatics metabarcoding taxonomy cpp

3.5 match 485 stars 13.17 score 3.0k scripts 4 dependents

bioc

GeneTonic:Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis

This package provides functionality to combine the existing pieces of the transcriptome data and results, making it easier to generate insightful observations and hypothesis. Its usage is made easy with a Shiny application, combining the benefits of interactivity and reproducibility e.g. by capturing the features and gene sets of interest highlighted during the live session, and creating an HTML report as an artifact where text, code, and output coexist. Using the GeneTonicList as a standardized container for all the required components, it is possible to simplify the generation of multiple visualizations and summaries.

Maintained by Federico Marini. Last updated 2 months ago.

gui geneexpression software transcription transcriptomics visualization differentialexpression pathways reportwriting genesetenrichment annotation go shinyapps bioconductor bioconductor-package data-exploration data-visualization functional-enrichment-analysis gene-expression pathway-analysis reproducible-research rna-seq-analysis rna-seq-data shiny transcriptome user-friendly

5.6 match 77 stars 8.28 score 37 scripts 1 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 4 days ago.

arrow polars rust

3.9 match 499 stars 12.01 score 1.0k scripts 2 dependents

cran

gprofiler2:Interface to the 'g:Profiler' Toolset

A toolset for functional enrichment analysis and visualization, gene/protein/SNP identifier conversion and mapping orthologous genes across species via 'g:Profiler' (<https://biit.cs.ut.ee/gprofiler/>). The main tools are: (1) 'g:GOSt' - functional enrichment analysis and visualization of gene lists; (2) 'g:Convert' - gene/protein/transcript identifier conversion across various namespaces; (3) 'g:Orth' - orthology search across species; (4) 'g:SNPense' - mapping SNP rs identifiers to chromosome positions, genes and variant effects. This package is an R interface corresponding to the 2019 update of 'g:Profiler' and provides access to 'g:Profiler' for versions 'e94_eg41_p11' and higher. See the package 'gProfileR' for accessing older versions from the 'g:Profiler' toolset.

Maintained by Liis Kolberg. Last updated 1 years ago.

5.8 match 4 stars 7.97 score 1.5k scripts 16 dependents

pilaboratory

sads:Maximum Likelihood Models for Species Abundance Distributions

Maximum likelihood tools to fit and compare models of species abundance distributions and of species rank-abundance distributions.

Maintained by Paulo I. Prado. Last updated 1 years ago.

5.3 match 23 stars 8.66 score 244 scripts 3 dependents

bupaverse

processmapR:Construct Process Maps Using Event Data

Visualize event logs using directed graphs, i.e. process maps. Part of the 'bupaR' framework.

Maintained by Gert Janssenswillen. Last updated 7 months ago.

cpp

6.0 match 9 stars 7.70 score 169 scripts 3 dependents

pboutros

ISOpureR:Deconvolution of Tumour Profiles

Deconvolution of mixed tumour profiles into normal and cancer for each patient, using the ISOpure algorithm in Quon et al. Genome Medicine, 2013 5:29. Deconvolution requires mixed tumour profiles and a set of unmatched "basis" normal profiles.

Maintained by Paul C Boutros. Last updated 6 years ago.

cpp

12.8 match 3 stars 3.61 score 34 scripts

kurthornik

textcat:N-Gram Based Text Categorization

Text categorization based on n-grams.

Maintained by Kurt Hornik. Last updated 4 months ago.

13.0 match 3 stars 3.53 score 170 scripts

bioc

MIRA:Methylation-Based Inference of Regulatory Activity

DNA methylation contains information about the regulatory state of the cell. MIRA aggregates genome-scale DNA methylation data into a DNA methylation profile for a given region set with shared biological annotation. Using this profile, MIRA infers and scores the collective regulatory activity for the region set. MIRA facilitates regulatory analysis in situations where classical regulatory assays would be difficult and allows public sources of region sets to be leveraged for novel insight into the regulatory state of DNA methylation datasets.

Maintained by John Lawson. Last updated 5 months ago.

immunooncology dnamethylation generegulation genomeannotation systemsbiology functionalgenomics chipseq methylseq sequencing epigenetics coverage

6.1 match 11 stars 7.52 score 7 scripts 1 dependents

bioc

ncGTW:Alignment of LC-MS Profiles by Neighbor-wise Compound-specific Graphical Time Warping with Misalignment Detection

The purpose of ncGTW is to help XCMS for LC-MS data alignment. Currently, ncGTW can detect the misaligned feature groups by XCMS, and the user can choose to realign these feature groups by ncGTW or not.

Maintained by Chiung-Ting Wu. Last updated 5 months ago.

software massspectrometry metabolomics alignment cpp

9.4 match 8 stars 4.90 score 3 scripts

mcanigueral

evprof:Electric Vehicle Charging Sessions Profiling and Modelling

Tools for modelling electric vehicle charging sessions into generic groups with similar connection patterns called "user profiles", using Gaussian Mixture Models clustering. The clustering and profiling methodology is described in Cañigueral and Meléndez (2021, ISBN:0142-0615) <doi:10.1016/j.ijepes.2021.107195>.

Maintained by Marc Cañigueral. Last updated 4 days ago.

13.9 match 2 stars 3.30 score 6 scripts

bioc

gcrma:Background Adjustment Using Sequence Information

Background adjustment using sequence information

Maintained by Z. Wu. Last updated 5 months ago.

microarray onechannel preprocessing

6.3 match 7.28 score 164 scripts 11 dependents

bayesiandemography

bage:Bayesian Estimation and Forecasting of Age-Specific Rates

Fast Bayesian estimation and forecasting of age-specific rates, probabilities, and means, based on 'Template Model Builder'.

Maintained by John Bryant. Last updated 2 months ago.

cpp

6.2 match 3 stars 7.30 score 39 scripts

silvialiverani

PReMiuM:Dirichlet Process Bayesian Clustering, Profile Regression

Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection. The main reference for the package is Liverani, Hastie, Azizi, Papathomas and Richardson (2015) <doi:10.18637/jss.v064.i07>.

Maintained by Silvia Liverani. Last updated 1 years ago.

cpp

14.4 match 3.13 score 126 scripts

japal

MALDIrppa:MALDI Mass Spectrometry Data Robust Pre-Processing and Analysis

Provides methods for quality control and robust pre-processing and analysis of MALDI mass spectrometry data (Palarea-Albaladejo et al. (2018) <doi:10.1093/bioinformatics/btx628>).

Maintained by Javier Palarea-Albaladejo. Last updated 1 years ago.

mass-spectrometry pre-processing

7.4 match 2 stars 6.06 score 32 scripts 1 dependents

january3

tmod:Feature Set Enrichment Analysis for Metabolomics and Transcriptomics

Methods and feature set definitions for feature or gene set enrichment analysis in transcriptional and metabolic profiling data. Package includes tests for enrichment based on ranked lists of features, functions for visualisation and multivariate functional analysis. See Zyla et al (2019) <doi:10.1093/bioinformatics/btz447>.

Maintained by January Weiner. Last updated 2 months ago.

6.5 match 3 stars 6.88 score 168 scripts 1 dependents

jmcurran

relSim:Relative Simulator

A set of tools to explore the behaviour statistics used for forensic DNA interpretation when close relatives are involved. The package also offers some useful tools for exploring other forensic DNA situations.

Maintained by James M. Curran. Last updated 1 years ago.

cpp

14.1 match 3.18 score 30 scripts

blue-matter

SAMtool:Stock Assessment Methods Toolkit

Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries. 'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting, model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation.

Maintained by Quang Huynh. Last updated 20 days ago.

cpp

6.9 match 3 stars 6.49 score 36 scripts 1 dependents

bwiernik

configural:Multivariate Profile Analysis

R functions for criterion profile analysis, Davison and Davenport (2002) <doi:10.1037/1082-989X.7.4.468> and meta-analytic criterion profile analysis, Wiernik, Wilmot, Davison, and Ones (2020) <doi:10.1037/met0000305>. Sensitivity analyses to aid in interpreting criterion profile analysis results are also included.

Maintained by Brenton M. Wiernik. Last updated 12 months ago.

11.2 match 4 stars 3.96 score 23 scripts

davidorme

caper:Comparative Analyses of Phylogenetics and Evolution in R

Functions for performing phylogenetic comparative analyses.

Maintained by David Orme. Last updated 1 years ago.

6.0 match 1 stars 7.41 score 928 scripts 5 dependents

openbiox

UCSCXenaShiny:Interactive Analysis of UCSC Xena Data

Provides functions and a Shiny application for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.

Maintained by Shixiang Wang. Last updated 4 months ago.

cancer-dataset shiny-apps ucsc-xena

5.2 match 96 stars 8.54 score 35 scripts

bioc

maSigPro:Significant Gene Expression Profile Differences in Time Course Gene Expression Data

maSigPro is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray and RNA-Seq experiments.

Maintained by Maria Jose Nueda. Last updated 5 months ago.

microarray rna-seq differential expression timecourse

8.5 match 5.18 score 76 scripts

datashield

DSI:'DataSHIELD' Interface

'DataSHIELD' is an infrastructure and series of R packages that enables the remote and 'non-disclosive' analysis of sensitive research data. This package defines the API that is to be implemented by 'DataSHIELD' compliant data repositories.

Maintained by Yannick Marcon. Last updated 4 months ago.

6.3 match 2 stars 7.01 score 106 scripts 4 dependents

mikldk

DNAtools:Tools for Analysing Forensic Genetic DNA Data

Computationally efficient tools for comparing all pairs of profiles in a DNA database. The expectation and covariance of the summary statistic is implemented for fast computing. Routines for estimating proportions of close related individuals are available. The use of wildcards (also called F- designation) is implemented. Dedicated functions ease plotting the results. See Tvedebrink et al. (2012) <doi:10.1016/j.fsigen.2011.08.001>. Compute the distribution of the numbers of alleles in DNA mixtures. See Tvedebrink (2013) <doi:10.1016/j.fsigss.2013.10.142>.

Maintained by Mikkel Meyer Andersen. Last updated 2 years ago.

cpp

7.3 match 6.00 score 28 scripts

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

7.1 match 10 stars 6.16 score 160 scripts 6 dependents

bioc

TCGAbiolinks:TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

Maintained by Tiago Chedraoui Silva. Last updated 27 days ago.

dnamethylation differentialmethylation generegulation geneexpression methylationarray differentialexpression pathways network sequencing survival software bioc bioconductor gdc integrative-analysis tcga tcga-data tcgabiolinks

3.0 match 305 stars 14.45 score 1.6k scripts 6 dependents

boxuancui

DataExplorer:Automate Data Exploration and Treatment

Automated data exploration process for analytic tasks and predictive modeling, so that users could focus on understanding data and extracting insights. The package scans and analyzes each variable, and visualizes them with typical graphical techniques. Common data processing methods are also available to treat and format data.

Maintained by Boxuan Cui. Last updated 1 years ago.

data-analysis data-exploration data-science eda visualization

3.9 match 519 stars 11.16 score 2.2k scripts

bioc

cfdnakit:Fragmen-length analysis package from high-throughput sequencing of cell-free DNA (cfDNA)

This package provides basic functions for analyzing shallow whole-genome sequencing (~0.3X or more) of cell-free DNA (cfDNA). The package basically extracts the length of cfDNA fragments and aids the vistualization of fragment-length information. The package also extract fragment-length information per non-overlapping fixed-sized bins and used it for calculating ctDNA estimation score (CES).

Maintained by Pitithat Puranachot. Last updated 5 months ago.

copynumbervariation sequencing wholegenome

8.3 match 8 stars 5.20 score 8 scripts

pik-piam

remind2:The REMIND R package (2nd generation)

Contains the REMIND-specific routines for data and model output manipulation.

Maintained by Renato Rodrigues. Last updated 7 days ago.

4.8 match 8.88 score 161 scripts 5 dependents

bioc

CGHcall:Calling aberrations for array CGH tumor profiles.

Calls aberrations for array CGH data using a six state mixture model as well as several biological concepts that are ignored by existing algorithms. Visualization of profiles is also provided.

Maintained by Mark van de Wiel. Last updated 5 months ago.

microarray preprocessing visualization

6.9 match 6.18 score 42 scripts 6 dependents

rkbauer

RchivalTag:Analyzing and Interactive Visualization of Archival Tagging Data

A set of functions to generate, access and analyze standard data products from archival tagging data.

Maintained by Robert K. Bauer. Last updated 2 months ago.

data-visuali depth depth-temperature-profiles dygraphs ggpot leaflet minipat pelagic plotly satellite sensor spatial star-oddi temperature time-series tracks wildlife-computers

11.8 match 1 stars 3.59 score 26 scripts

adokter

vol2birdR:Vertical Profiles of Biological Signals in Weather Radar Data

'R' implementation of the 'vol2bird' software for generating vertical profiles of birds and other biological signals in weather radar data. See Dokter et al. (2011) <doi:10.1098/rsif.2010.0116> for a paper describing the methodology.

Maintained by Adriaan M. Dokter. Last updated 10 days ago.

proj hdf5 zlib gsl cpp

6.4 match 6 stars 6.61 score 19 scripts

vwendy

pompom:Person-Oriented Method and Perturbation on the Model

An implementation of a hybrid method of person-oriented method and perturbation on the model. Pompom is the initials of the two methods. The hybrid method will provide a multivariate intraindividual variability metric (iRAM). The person-oriented method used in this package refers to uSEM (unified structural equation modeling, see Kim et al., 2007, Gates et al., 2010 and Gates et al., 2012 for details). Perturbation on the model was conducted according to impulse response analysis introduced in Lutkepohl (2007). Kim, J., Zhu, W., Chang, L., Bentler, P. M., & Ernst, T. (2007) <doi:10.1002/hbm.20259>. Gates, K. M., Molenaar, P. C. M., Hillary, F. G., Ram, N., & Rovine, M. J. (2010) <doi:10.1016/j.neuroimage.2009.12.117>. Gates, K. M., & Molenaar, P. C. M. (2012) <doi:10.1016/j.neuroimage.2012.06.026>. Lutkepohl, H. (2007, ISBN:3540262393).

Maintained by Xiao Yang. Last updated 4 years ago.

13.7 match 3.08 score 24 scripts

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 2 days ago.

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

4.5 match 136 stars 9.33 score 95 scripts