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http://cran.r-project.org/web/packages/neuRosim/

Software package that allows users to generate fMRI time series or 4D data. Some high-level functions are created for fast data generation with only a few arguments and a diversity of functions to define activation and noise. For more advanced users it is possible to use the low-level functions and manipulate the arguments.

Proper citation: neuRosim (RRID:SCR_002154) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/flowPlots.html

Software for analysis plots and data class for gated flow cytometry data.

Proper citation: flowPlots (RRID:SCR_002177) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/metaRNASeq/

Software package for meta-analysis of RNA-seq data. This package implements two p-value combination techniques (inverse normal and Fisher methods). It also provides a vignette explaining how to combine data from multiple RNA-seq experiments.

Proper citation: metaRNASeq (RRID:SCR_002174) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/src/contrib/Archive/demi/

R package for estimating differential expression from multiple indicators that capitalizes on the high number of concurrent measurements. It extends to various experimental designs and target categories (transcripts, genes, genomic regions) as well as small sample sizes.

Proper citation: DEMI (RRID:SCR_002291) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/flowCore.html

A Bioconductor software package for high throughput flow cytometry that provides S4 data structures and basic functions.

Proper citation: flowCore (RRID:SCR_002205) Copy   

•   Source: SciCrunch Registry

http://www.statmethods.net/index.html

Training material created for both current R users, and experienced users of other statistical packages (e.g., SAS, SPSS, Stata) who would like to transition to R to help you quickly access this language in your work. The book inspired by this site takes the material here and significantly expands upon it.

Proper citation: Quick-R (RRID:SCR_002417) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/flowBeads.html

Software package for the analysis of flow cytometry bead data. It extends flowCore to provide functionality specific to bead data. One of the goals of this package is to automate analysis of bead data for the purpose of normalization.

Proper citation: flowBeads (RRID:SCR_002440) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/flowCyBar.html

A software package to analyze flow cytometric data using gate information to follow population / community dynamics.

Proper citation: flowCyBar (RRID:SCR_002319) Copy   

•   Source: SciCrunch Registry

http://www.r-tutor.com/

Couple of introductory tutorials on basic R concepts that provides an introduction to the R programming language, and illustrates its use by solving elementary statistics textbook exercises. Beyond the basics, they also cover topics of GPU computing in R. An R Tutorial eBook is also available.

Proper citation: R Tutorial - An R Introduction to Statistics (RRID:SCR_002394) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/MBASED.html

Software package containing functions for allele-specific gene expression (ASE) analysis using meta-analysis based allele-specific expression detection.

Proper citation: MBASED (RRID:SCR_002584) Copy   

•   Source: SciCrunch Registry

http://www.tractor-mri.org.uk/

Software application that includes R packages for reading, writing and visualising magnetic resonance images stored in Analyze, NIfTI and DICOM file formats (DICOM support is read only). It also contains functions specifically designed for working with diffusion MRI and tractography, including a standard implementation of the neighbourhood tractography approach to white matter tract segmentation. A shell script is also provided to run experiments with TractoR without interacting with R.

Proper citation: TractoR: Tractography with R (RRID:SCR_002602) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/sapFinder.html

An R software package, for detection of the variant peptides based on tandem mass spectrometry (MS/MS)-based proteomics data. It automates (1) variation-associated database construction, (2) database searching, (3) post-processing, (4) HTML-based report generation in shotgun proteomics.

Proper citation: sapFinder (RRID:SCR_002685) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/pathview.html

A tool set for pathway-based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.

Proper citation: Pathview (RRID:SCR_002732) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/flowCL.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software for semantic labelling of flow cytometric cell populations.

Proper citation: flowCL (RRID:SCR_000046) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/data/annotation/html/RmiR.Hs.miRNA.html

Software package for various databases of microRNA Targets.

Proper citation: RmiR.Hs.miRNA (RRID:SCR_000101) Copy   

•   Source: SciCrunch Registry

http://neuro.debian.net/

Collection based on a collaborative effort of popular neuroscience research software for the Debian operating system as well as Ubuntu and other derivatives. Popular packages include AFNI, FSL, PyMVPA and many others. It contains both unofficial or prospective packages which are not (yet) available from the main Debian archive, as well as backported or simply rebuilt packages also available elsewhere. A listing of current and planned projects is available if you want to get involved. The main goal of the project is to provide a versatile and convenient environment for neuroscientific research that is based on open-source software. To this end, the project offers a package repository that complements the main Debian (and Ubuntu) archive. NeuroDebian is not yet another Linux distribution, but rather an effort inside the Debian project itself. Software packages are fully integrated into the Debian system and from there will eventually migrate into Ubuntu as well. With NeuroDebian, installing and updating neuroscience software is no different from any other part of the operating system. Maintaining a research software environment becomes as easy as installing an editor. There is also virtual machine to test NeuroDebian on Windows or Mac OS. If you want to see your software packaged for Debian, please drop them a note.

Proper citation: neurodebian (RRID:SCR_004401) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/edgeR/

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

Proper citation: edgeR (RRID:SCR_012802) Copy   

•   Source: SciCrunch Registry

http://www.dkfz.de/en/epidemiologie-krebserkrankungen/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

Proper citation: PIAGE (RRID:SCR_013124) Copy   

•   Source: SciCrunch Registry

https://CRAN.R-project.org/package=NBR

Software tool as implementation of network based statistics toolbox in R. Includes mixed effects models.

Proper citation: Network-Based R-Statistics (RRID:SCR_019114) Copy   

•   Source: SciCrunch Registry

http://folk.uio.no/thoree/FEST/

An R package for simulations and likelihood calculations of pair-wise family relationships using DNA marker data. (entry from Genetic Analysis Software)

Proper citation: R/FEST (RRID:SCR_013347) Copy   

•   Source: SciCrunch Registry