Packages — R (Page 1 of 15)
r 3.6.0 — Environment for statistical computing and graphics
This is a GNU package.
R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.
r-a3 1.0.0 — Error metrics for predictive models
This package supplies tools for tabulating and analyzing the results of predictive models. The methods employed are applicable to virtually any predictive model and make comparisons between different methodologies straightforward.
r-a4 1.32.0 — Automated Affymetrix array analysis umbrella package
This package provides a software suite for the automated analysis of Affymetrix arrays.
r-a4base 1.32.0 — Automated Affymetrix array analysis base package
This package provides basic features for the automated analysis of Affymetrix arrays.
r-a4classif 1.32.0 — Automated Affymetrix array analysis classification package
This is the classification package for the automated analysis of Affymetrix arrays.
r-a4core 1.32.0 — Automated Affymetrix array analysis core package
This is the core package for the automated analysis of Affymetrix arrays.
r-a4preproc 1.32.0 — Automated Affymetrix array analysis preprocessing package
This is a package for the automated analysis of Affymetrix arrays. It is used for preprocessing the arrays.
r-a4reporting 1.32.0 — Automated Affymetrix array analysis reporting package
This is a package for the automated analysis of Affymetrix arrays. It provides reporting features.
r-abadata 1.12.0 — Gene expression in human brain regions from Allen Brain Atlas
This package provides the data for the gene expression enrichment analysis conducted in the package ABAEnrichment. The package includes three datasets which are derived from the Allen Brain Atlas:
Gene expression data from Human Brain (adults) averaged across donors,
Gene expression data from the Developing Human Brain pooled into five age categories and averaged across donors, and
a developmental effect score based on the Developing Human Brain expression data.
All datasets are restricted to protein coding genes.
r-abaenrichment 1.14.0 — Gene expression enrichment in human brain regions
The package ABAEnrichment is designed to test for enrichment of user defined candidate genes in the set of expressed genes in different human brain regions. The core function
aba_enrich integrates the expression of the candidate gene set (averaged across donors) and the structural information of the brain using an ontology, both provided by the Allen Brain Atlas project.
r-abbyyr 0.5.5 — Access to Abbyy Optical Character Recognition (OCR) API
This package provides tools to get text from images of text using Abbyy Cloud Optical Character Recognition (OCR) API. With abbyyyR, one can easily OCR images, barcodes, forms, documents with machine readable zones, e.g. passports and get the results in a variety of formats including plain text and XML. To learn more about the Abbyy OCR API, see http://ocrsdk.com/.
r-abc 2.1 — Tools for Approximate Bayesian Computation (ABC)
This package implements several Approximate Bayesian Computation (ABC) algorithms for performing parameter estimation, model selection, and goodness-of-fit. Cross-validation tools are also available for measuring the accuracy of ABC estimates, and to calculate the misclassification probabilities of different models.
r-abc-data 1.0 — Data for Approximate Bayesian Computation (ABC) package
This package contains data which are used by functions of the abc package which implements several Approximate Bayesian Computation (ABC) algorithms for performing parameter estimation, model selection, and goodness-of-fit.
r-abcanalysis 1.2.1 — Computed ABC Analysis
Multivariate data sets often differ in several factors or derived statistical parameters, which have to be selected for a valid interpretation. Basing this selection on traditional statistical limits leads occasionally to the perception of losing information from a data set. This package provides tools to calculate these limits on the basis of the mathematical properties of the distribution of the analyzed items.
r-abcoptim 0.15.0 — Optimization of Artificial Bee Colony algorithm
Artificial Bee Colony (ABC) is one of the most recently defined algorithms by Dervis Karaboga in 2005, motivated by the intelligent behavior of honey bees. It is as simple as Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms, and uses only common control parameters such as colony size and maximum cycle number. The
r-abcoptim implements the Artificial bee colony optimization algorithm http://mf.erciyes.edu.tr/abc/pub/tr06_2005.pdf. This version is a work-in-progress and is written in R code.
r-abcp2 1.2 — Approximate Bayesian Computational Model for Estimating P2
This package tests the goodness of fit of a distribution of offspring to the Normal, Poisson, and Gamma distribution and estimates the proportional paternity of the second male (P2) based on the best fit distribution.
r-abcrf 1.8 — Approximate bayesian computation via random forests
This package performs approximate bayesian computation (ABC) model choice and parameter inference via random forests. This machine learning tool named random forests (RF) can conduct selection among the highly complex models covered by ABC algorithms.
r-abctools 1.1.3 — Tools for ABC analyses
r-abctools package provides tools for approximate Bayesian computation including summary statistic selection and assessing coverage. This includes recent dimension reduction algorithms to tune the choice of summary statistics, and coverage methods to tune the choice of threshold.
r-abd 0.2-8 — Analysis of biological data
r-abd package contains data sets and sample code for the Analysis of biological data by Michael Whitlock and Dolph Schluter.
r-abe 3.0.1 — Augmented backward elimination
This package performs augmented backward elimination and checks the stability of the obtained model. Augmented backward elimination combines significance or information based criteria with the change in estimate to either select the optimal model for prediction purposes or to serve as a tool to obtain a practically sound, highly interpretable model.
r-abf2 0.7-1 — Load gap-free axon
This package loads electrophysiology data from ABF2 files, as created by Axon Instruments/Molecular Devices software. Only files recorded in gap-free mode are currently supported.
r-abhgenotyper 1.0.1 — Visualize and manipulate ABH genotypes
r-abhgenotyper package provides simple imputation, error-correction and plotting capacities for genotype data. The package is supposed to serve as an intermediate but independent analysis tool between the TASSEL GBS pipeline and the
r-qtl package. It provides functionalities not found in either TASSEL or
r-qtl in addition to visualization of genotypes as "graphical genotypes".
r-abind 1.4-5 — Combine multidimensional arrays
This package provides tools to combine multidimensional arrays into a single array. This is a generalization of
rbind. It works with vectors, matrices, and higher-dimensional arrays. It also provides the functions
afill for manipulating, extracting and replacing data in arrays.
r-abjutils 0.2.3 — Collection of tools for jurimetrical analysis
This package implements general purpose tools, such as functions for sampling and basic manipulation of Brazilian lawsuits identification number. It also implements functions for text cleaning, such as accentuation removal.
r-abn 1.3 — Modelling multivariate data with additive bayesian networks
Bayesian network analysis is a form of probabilistic graphical models which derives from empirical data a directed acyclic graph, DAG, describing the dependency structure between random variables. An additive Bayesian network model consists of a form of a DAG where each node comprises a generalized linear model (GLM). Additive Bayesian network models are equivalent to Bayesian multivariate regression using graphical modelling, they generalises the usual multivariable regression, GLM, to multiple dependent variables. This package provides routines to help determine optimal Bayesian network models for a given data set, where these models are used to identify statistical dependencies in messy, complex data.
r-abnormality 0.1.0 — Measure a subject's abnormality with respect to a reference population
This package contains functions to implement the methodology and considerations laid out by Marks et al. in the article "Measuring abnormality in high dimensional spaces: applications in biomechanical gait analysis". Using high-dimensional datasets to measure a subject's overall level of abnormality as compared to a reference population is often needed in outcomes research.
r-abodoutlier 0.1 — Angle-based outlier detection
This package performs angle-based outlier detection on a given data frame. It offers three methods to process data:
full but slow implementation using all the data that has cubic complexity;
a fully randomized method;
a method using k-nearest neighbours.
These algorithms are well suited for high dimensional data outlier detection.
r-abps 0.3 — Abnormal blood profile score to detect blood doping
This package offers an implementation of the Abnormal blood profile score (ABPS). The ABPS is a part of the Athlete biological passport program of the World anti-doping agency, which combines several blood parameters into a single score in order to detect blood doping. The package also contains functions to calculate other scores used in anti-doping programs, such as the ratio of hemoglobin to reticulocytes (OFF-score), as well as example data.
r-abseqr 1.2.0 — Reporting and data analysis for Rep-Seq datasets of antibody libraries
AbSeq is a comprehensive bioinformatic pipeline for the analysis of sequencing datasets generated from antibody libraries and abseqR is one of its packages. AbseqR empowers the users of abseqPy with plotting and reporting capabilities and allows them to generate interactive HTML reports for the convenience of viewing and sharing with other researchers. Additionally, abseqR extends abseqPy to compare multiple repertoire analyses and perform further downstream analysis on its output.
r-absfiltergsea 1.5.1 — Improved false positive control of gene-permuting with absolute filtering
This package provides a function that performs gene-permuting of a gene-set enrichment analysis (GSEA) calculation with or without the absolute filtering. Without filtering, users can perform (original) two-tailed or one-tailed absolute GSEA.
- License: GPL 2.
- Website: https://cran.r-project.org/web/packages/AbsFilterGSEA/.
- Package source: bioinformatics.scm.
- Patches: None.
- Lint issues: No.
- Builds: x86_64-linux, i686-linux.
r-absim 0.2.6 — Time resolved simulations of antibody repertoires
This package provides simulation methods for the evolution of antibody repertoires. The heavy and light chain variable region of both human and C57BL/6 mice can be simulated in a time-dependent fashion. Both single lineages using one set of V-, D-, and J-genes or full repertoires can be simulated. The algorithm begins with an initial V-D-J recombination event, starting the first phylogenetic tree. Upon completion, the main loop of the algorithm begins, with each iteration representing one simulated time step. Various mutation events are possible at each time step, contributing to a diverse final repertoire.
r-abundant 1.1 — Abundant regression and high-dimensional principal fitted components
This package provides tools to fit and predict with the high-dimensional principal fitted components model. This model is described by Cook, Forzani, and Rothman (2012) doi:10.1214/11-AOS962.
r-ac3net 1.2.2 — Inferring directional conservative causal core gene networks
This package infers directional Conservative causal core (gene) networks (C3NET). This is a version of the algorithm C3NET with directional network.
r-aca 1.1 — Abrupt change-point or aberration detection in point series
This package offers an interactive function for the detection of breakpoints in series.
r-acc 1.3.3 — Exploring accelerometer data
This package processes accelerometer data from uni-axial and tri-axial devices and generates data summaries. Also, includes functions to plot, analyze, and simulate accelerometer data.
r-accelerometry 3.1.2 — Functions for processing accelerometer data
This package provides a collection of functions that perform operations on time-series accelerometer data, such as identify the non-wear time, flag minutes that are part of an activity bout, and find the maximum 10-minute average count value. The functions are generally very flexible, allowing for a variety of algorithms to be implemented.
r-accelmissing 1.4 — Missing value imputation for accelerometer data
This package provides a statistical method to impute the missing values in accelerometer data. The methodology includes both parametric and semi-parametric multiple imputations under the zero-inflated Poisson lognormal model. It also provides multiple functions to preprocess the accelerometer data previous to the missing data imputation. These include detecting the wearing and the non-wearing time, selecting valid days and subjects, and creating plots.
r-acceptancesampling 1.0-6 — Creation and evaluation of acceptance sampling plans
r-acceptancesampling provides functionality for creating and evaluating acceptance sampling plans. Acceptance sampling is a methodology commonly used in quality control and improvement. International standards of acceptance sampling provide sampling plans for specific circumstances. The aim of this package is to provide an easy-to-use interface to visualize single, double or multiple sampling plans. In addition, methods have been provided to enable the user to assess sampling plans against pre-specified levels of performance, as measured by the probability of acceptance for a given level of quality in the lot.
r-acclma 1.0 — ACC & LMA graph plotting
This package contains a function that imports data from a CSV file, or uses manually entered data from the format (x, y, weight) and plots the appropriate ACC vs LOI graph and LMA graph. The main function is
plotLMA (source file, header) that takes a data set and plots the appropriate LMA and ACC graphs. If no source file (a string) was passed, a manual data entry window is opened. The header parameter indicates by TRUE/FALSE (false by default) if the source CSV file has a header row or not. The dataset should contain only one independent variable (x) and one dependent variable (y) and can contain a weight for each observation.
r-acd 1.5.3 — Categorical data analysis with complete or missing responses
This package provides tools for categorical data analysis with complete or missing responses.
r-acdm 1.0.4 — Tools for Autoregressive Conditional Duration Models
ACDm is a package for Autoregressive Conditional Duration (ACD, Engle and Russell, 1998) models. It creates trade, price or volume durations from transactions (tic) data, performs diurnal adjustments, fits various ACD models and tests them.
r-acepack 1.4.1 — Functions for regression transformations
This package provides ACE and AVAS methods for choosing regression transformations.
r-acsnminer 0.16.8.25 — Gene enrichment analysis
This package provides tools to compute and represent gene set enrichment or depletion from your data based on pre-saved maps from the Atlas of Cancer Signalling Networks (ACSN) or user imported maps. The gene set enrichment can be run with hypergeometric test or Fisher exact test, and can use multiple corrections. Visualization of data can be done either by barplots or heatmaps.
r-activity 1.2 — Animal activity statistics
This package provides functions to fit kernel density functions to animal activity time data; plot activity distributions; quantify overall levels of activity; statistically compare activity metrics through bootstrapping; and evaluate variation in linear variables with time (or other circular variables).
r-adaptivesparsity 1.6 — Adaptive sparsity models
This package implements the Figueiredo machine learning algorithm for adaptive sparsity and the Wong algorithm for adaptively sparse gaussian geometric models.
- License: LGPL 3+.
- Website: https://cran.r-project.org/web/packages/AdaptiveSparsity.
- Package source: machine-learning.scm.
- Patches: None.
- Lint issues: No.
- Builds: x86_64-linux, i686-linux.
r-ade4 1.7-13 — Multivariate data analysis and graphical display
The ade4 package contains data analysis functions to analyze ecological and environmental data in the framework of Euclidean exploratory methods.
r-adegenet 2.1.1 — Exploratory analysis of genetic and genomic data
This package provides a toolset for the exploration of genetic and genomic data. Adegenet provides formal (S4) classes for storing and handling various genetic data, including genetic markers with varying ploidy and hierarchical population structure (
genind class), alleles counts by populations (
genpop), and genome-wide SNP data (
genlight). It also implements original multivariate methods (DAPC, sPCA), graphics, statistical tests, simulation tools, distance and similarity measures, and several spatial methods. A range of both empirical and simulated datasets is also provided to illustrate various methods.
r-adgoftest 0.3 — Anderson-Darling GoF test
This package provides an implementation of the Anderson-Darling GoF test with p-value calculation based on Marsaglia's 2004 paper "Evaluating the Anderson-Darling Distribution".
r-afex 0.23-0 — Analysis of factorial experiments
This package provides convenience functions for analyzing factorial experiments using ANOVA or mixed models.
r-affy 1.62.0 — Methods for affymetrix oligonucleotide arrays
This package contains functions for exploratory oligonucleotide array analysis.
r-affyio 1.54.0 — Tools for parsing Affymetrix data files
This package provides routines for parsing Affymetrix data files based upon file format information. The primary focus is on accessing the CEL and CDF file formats.
r-aggregation 1.0.1 — Methods for p-value aggregation
This package contains functionality for performing the following methods of p-value aggregation: Fisher's method, the Lancaster method (weighted Fisher's method), and Sidak correction.
r-algdesign 1.1-7.3 — Algorithmic experimental design
This package provides tools to calculate exact and approximate theory experimental designs for D, A, and I criteria. Very large designs may be created. Experimental designs may be blocked or blocked designs created from a candidate list, using several criteria. The blocking can be done when whole and within plot factors interact.
r-allelicimbalance 1.22.0 — Investigate allele-specific expression
This package provides a framework for allele-specific expression investigation using RNA-seq data.
r-als 0.0.6 — Multivariate curve resolution alternating least squares
Alternating least squares is often used to resolve components contributing to data with a bilinear structure; the basic technique may be extended to alternating constrained least squares. This package provides an implementation of multivariate curve resolution alternating least squares (MCR-ALS).
Commonly applied constraints include unimodality, non-negativity, and normalization of components. Several data matrices may be decomposed simultaneously by assuming that one of the two matrices in the bilinear decomposition is shared between datasets.
r-amap 0.8-17 — Another multidimensional analysis package
This package provides tools for clustering and principal component analysis (with robust methods, and parallelized functions).
r-analytics 3.0 — Collection of data analysis tools
This package is a collection of data analysis tools. It includes tools for regression outlier detection in a fitted linear model, stationary bootstrap using a truncated geometric distribution, a comprehensive test for weak stationarity, column means by group, weighted biplots, and a heuristic to obtain a better initial configuration in non-metric MDS.
r-annaffy 1.56.0 — Annotation tools for Affymetrix biological metadata
This package provides functions for handling data from Bioconductor Affymetrix annotation data packages. It produces compact HTML and text reports including experimental data and URL links to many online databases. It allows searching of biological metadata using various criteria.
r-annotate 1.62.0 — Annotation for microarrays
This package provides R environments for the annotation of microarrays.
r-annotationdbi 1.46.0 — Annotation database interface
This package provides user interface and database connection code for annotation data packages using SQLite data storage.
r-annotationfilter 1.8.0 — Facilities for filtering Bioconductor annotation resources
This package provides classes and other infrastructure to implement filters for manipulating Bioconductor annotation resources. The filters are used by
Organism.dplyr, and other packages.
r-annotationforge 1.26.0 — Code for building annotation database packages
This package provides code for generating Annotation packages and their databases. Packages produced are intended to be used with AnnotationDbi.
r-annotationfuncs 1.34.0 — Annotation translation functions
This package provides functions for handling translating between different identifieres using the Biocore Data Team data-packages (e.g.
r-annotationhub 2.16.0 — Client to access AnnotationHub resources
This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g. VCF, bed, wig) and other resources from standard locations (e.g. UCSC, Ensembl) can be discovered. The resource includes metadata about each resource, e.g., a textual description, tags, and date of modification. The client creates and manages a local cache of files retrieved by the user, helping with quick and reproducible access.
r-annotationtools 1.58.0 — Annotate microarrays and perform gene expression analyses
This package provides functions to annotate microarrays, find orthologs, and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file database (plain text files).
r-annotatr 1.10.0 — Annotation of genomic regions to genomic annotations
Given a set of genomic sites/regions (e.g. ChIP-seq peaks, CpGs, differentially methylated CpGs or regions, SNPs, etc.) it is often of interest to investigate the intersecting genomic annotations. Such annotations include those relating to gene models (promoters, 5'UTRs, exons, introns, and 3'UTRs), CpGs (CpG islands, CpG shores, CpG shelves), or regulatory sequences such as enhancers. The annotatr package provides an easy way to summarize and visualize the intersection of genomic sites/regions with genomic annotations.
r-anota 1.32.0 — Analysis of translational activity
Genome wide studies of translational control is emerging as a tool to study various biological conditions. The output from such analysis is both the mRNA level (e.g. cytosolic mRNA level) and the levl of mRNA actively involved in translation (the actively translating mRNA level) for each mRNA. The standard analysis of such data strives towards identifying differential translational between two or more sample classes - i.e. differences in actively translated mRNA levels that are independent of underlying differences in cytosolic mRNA levels. This package allows for such analysis using partial variances and the random variance model. As 10s of thousands of mRNAs are analyzed in parallel the library performs a number of tests to assure that the data set is suitable for such analysis.
r-apcluster 1.4.7 — Affinity propagation clustering
This package implements affinity propagation clustering introduced by Frey and Dueck (2007). The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation. Various plotting functions are available for analyzing clustering results.
r-ape 5.3 — Analyses of phylogenetics and evolution
This package provides functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, and several other tools.
r-argparse 2.0.1 — Command line optional and positional argument parser
This package provides a command line parser to be used with Rscript to write shebang scripts that gracefully accept positional and optional arguments and automatically generate usage notices.
r-argparser 0.4 — Command-line argument parser
This package provides a cross-platform command-line argument parser written purely in R with no external dependencies. It is useful with the Rscript front-end and facilitates turning an R script into an executable script.
r-arm 1.10-1 — Data analysis using regression and multilevel/hierarchical models
This package provides functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.
r-aroma-light 3.14.0 — Methods for normalization and visualization of microarray data
This package provides methods for microarray analysis that take basic data types such as matrices and lists of vectors. These methods can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.
r-arrmdata 1.18.0 — Example dataset for normalization of Illumina 450k methylation data
This package provides raw beta values from 36 samples across 3 groups from Illumina 450k methylation arrays.
r-arrmnormalization 1.24.0 — Adaptive robust regression normalization for methylation data
This is a package to perform the Adaptive Robust Regression method (ARRm) for the normalization of methylation data from the Illumina Infinium HumanMethylation 450k assay.
r-arules 1.6-3 — Mining association rules and frequent itemsets
This package provides an infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). It also provides C implementations of the association mining algorithms Apriori and Eclat.
r-askpass 1.1 — Safe password entry for R
This package provides cross-platform utilities for prompting the user for credentials or a passphrase, for example to authenticate with a server or read a protected key.
r-aspi 0.2.0 — Analysis of symmetry of parasitic infections
This package provides tools for the analysis and visualization of bilateral asymmetry in parasitic infections.
r-assertive 0.3-5 — Readable check functions to ensure code integrity
This package provides lots of predicates (
is_* functions) to check the state of your variables, and assertions (
assert_* functions) to throw errors if they aren't in the right form.
r-assertive-base 0.0-7 — Core of the assertive package
This package provides a minimal set of predicates and assertions used by the assertive package. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-code 0.0-3 — Assertions to check properties of code
This package provides a set of predicates and assertions for checking the properties of code. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-data 0.0-3 — Assertions to check properties of data
This package provides a set of predicates and assertions for checking the properties of (country independent) complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-data-uk 0.0-2 — Assertions to check properties of strings
This package provides a set of predicates and assertions for checking the properties of UK-specific complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-data-us 0.0-2 — Assertions to check properties of strings
This package provides a set of predicates and assertions for checking the properties of US-specific complex data types. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-datetimes 0.0-2 — Assertions to check properties of dates and times
This package provides a set of predicates and assertions for checking the properties of dates and times. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-files 0.0-2 — Assertions to check properties of files
This package provides a set of predicates and assertions for checking the properties of files and connections. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-matrices 0.0-2 — Assertions to check properties of matrices
This package provides a set of predicates and assertions for checking the properties of matrices. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-models 0.0-2 — Assertions to check properties of models
This package provides a set of predicates and assertions for checking the properties of models. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-numbers 0.0-2 — Assertions to check properties of numbers
This package provides a set of predicates and assertions for checking the properties of numbers. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-properties 0.0-4 — Assertions to check properties of variables
This package provides a set of predicates and assertions for checking the properties of variables, such as length, names and attributes. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-reflection 0.0-4 — Assertions for checking the state of R
This package provides a set of predicates and assertions for checking the state and capabilities of R, the operating system it is running on, and the IDE being used. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-sets 0.0-3 — Assertions to check properties of sets
This package provides a set of predicates and assertions for checking the properties of sets. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-strings 0.0-3 — Assertions to check properties of strings
This package provides a set of predicates and assertions for checking the properties of strings. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertive-types 0.0-3 — Assertions to check types of variables
This package provides a set of predicates and assertions for checking the types of variables. This is mainly for use by other package developers who want to include run-time testing features in their own packages.
r-assertthat 0.2.1 — Easy pre and post assertions
Assertthat is an extension to stopifnot() that makes it easy to declare the pre and post conditions that your code should satisfy, while also producing friendly error messages so that your users know what they've done wrong.
r-atacseqqc 1.8.1 — ATAC-seq quality control
ATAC-seq, an assay for Transposase-Accessible Chromatin using sequencing, is a rapid and sensitive method for chromatin accessibility analysis. It was developed as an alternative method to MNase-seq, FAIRE-seq and DNAse-seq. The ATACseqQC package was developed to help users to quickly assess whether their ATAC-seq experiment is successful. It includes diagnostic plots of fragment size distribution, proportion of mitochondria reads, nucleosome positioning pattern, and CTCF or other Transcript Factor footprints.
r-auc 0.3.0 — Compute the area under the curve of selected measures
This package includes functions to compute the area under the curve of selected measures: the area under the sensitivity curve (AUSEC), the area under the specificity curve (AUSPC), the area under the accuracy curve (AUACC), and the area under the receiver operating characteristic curve (AUROC). The curves can also be visualized. Support for partial areas is provided.
r-aucell 1.6.1 — Analysis of gene set activity in single-cell RNA-seq data
AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules, etc) in single-cell RNA-seq data. AUCell uses the Area Under the Curve (AUC) to calculate whether a critical subset of the input gene set is enriched within the expressed genes for each cell. The distribution of AUC scores across all the cells allows exploring the relative expression of the signature. Since the scoring method is ranking-based, AUCell is independent of the gene expression units and the normalization procedure. In addition, since the cells are evaluated individually, it can easily be applied to bigger datasets, subsetting the expression matrix if needed.
r-backports 1.1.4 — Reimplementations of functions introduced since R 3.0.0
Provides implementations of functions which have been introduced in R since version 3.0.0. The backports are conditionally exported which results in R resolving the function names to the version shipped with R (if available) and uses the implemented backports as fallback. This way package developers can make use of the new functions without worrying about the minimum required R version.
r-bacon 1.12.0 — Controlling bias and inflation in association studies
Bacon can be used to remove inflation and bias often observed in epigenome- and transcriptome-wide association studies. To this end bacon constructs an empirical null distribution using a Gibbs Sampling algorithm by fitting a three-component normal mixture on z-scores.