Tools   Select Another Resource Report Type

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Software package for computing correlated mutations based on selection pressure. Three methods are provided for detecting correlated mutations, including conditional selection pressure, mutual information and Jaccard index. The computation consists of two steps: First, the positive selection sites are detected; second, the mutation correlations are computed among the positive selection sites. Note that the first step is optional. Meanwhile, CorMut facilitates the comparison of the correlated mutations between two conditions by the means of correlated mutation network.

Proper citation: CorMut (RRID:SCR_000053) Copy   

•   Source: SciCrunch Registry

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

Software package for meta-analysis of RNA-Seq count data in multiple studies. The probabilities by one-sided NOISeq are combined by Fisher's method or Stouffer's method.

Proper citation: metaSeq (RRID:SCR_000056) Copy   

•   Source: SciCrunch Registry

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

Software package that provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions can be used to evaluate tests of contrast of biological interest and perform single outlier detection.

Proper citation: factDesign (RRID:SCR_001330) Copy   

•   Source: SciCrunch Registry

https://rdrr.io/bioc/spotSegmentation/

Model-based software package for processing microarray images so as to estimate foreground and background intensities. The method starts with a very simple but effective automatic gridding method, and then proceeds in two steps. The first step applies model-based clustering to the distribution of pixel intensities, using the Bayesian Information Criterion (BIC) to choose the number of groups up to a maximum of three. The second step is spatial, finding the large spatially connected components in each cluster of pixels. The method thus combines the strengths of the histogram-based and spatial approaches. It deals effectively with inner holes in spots and with artifacts. It also provides a formal inferential basis for deciding when the spot is blank, namely when the BIC favors one group over two or three.

Proper citation: spotSegmentation (RRID:SCR_001298) Copy   

•   Source: SciCrunch Registry

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

Software for adaptive Gene Picking for Microarray Expression Data Analysis.

Proper citation: pickgene (RRID:SCR_001331) Copy   

•   Source: SciCrunch Registry

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

Software package providing a collection of meta-analysis tools for analysing high throughput experimental data.

Proper citation: GeneMeta (RRID:SCR_001201) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software R package for the analysis of ChIP-chip data and Affymetrix tiling arrays. It provides functions for data import, quality assessment, and data visualization. The software provides tools for the efficient mapping of genomic sequences.

Proper citation: Starr (RRID:SCR_001071) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software tools for meta-analysis in the presence of hierarchical (and/or sampling) dependence, including with gene expression studies.

Proper citation: metahdep (RRID:SCR_001225) Copy   

•   Source: SciCrunch Registry

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

An easy to use software tool for dual color microarray data. Its GUI-Tk based environment lets any non-experienced user perform a basic, but not simple, data analysis just following a wizard. In addition it provides some tools for the developer.

Proper citation: genArise (RRID:SCR_001346) Copy   

•   Source: SciCrunch Registry

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

A software package for meta-analysis of high-throughput experiments using feature annotations. It calculates significant annotations (categories) in each of two (or more) feature (i.e. gene) lists, determines the overlap between the annotations, and returns graphical and tabular data about the significant annotations and which combinations of feature lists the annotations were found to be significant. Interactive exploration is facilitated through the use of RCytoscape (heavily suggested).

Proper citation: categoryCompare (RRID:SCR_001223) Copy   

•   Source: SciCrunch Registry

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

R software package that uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments.

Proper citation: BAC (RRID:SCR_001067) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/data/annotation/html/targetscan.Hs.eg.db.html

R software that predicts biological targets of miRNAs by searching for the presence of conserved 8mer and 7mer sites that match the seed region of each miRNA.

Proper citation: targetscan.Hs.eg.db (RRID:SCR_001068) Copy   

•   Source: SciCrunch Registry

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

A software package that tests groups of covariates (or features) for association with a response variable. The package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.

Proper citation: globaltest (RRID:SCR_001256) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.12/bioc/html/rGADEM.html

R package with tools for de novo motif discovery in large-scale genomic sequence data.

Proper citation: rGADEM (RRID:SCR_001091) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.14/bioc/html/MinimumDistance.html

Software package for analysis of de novo copy number variants in trios from high-dimensional genotyping platforms.

Proper citation: MinimumDistance (RRID:SCR_001260) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages/release/bioc/html/GSVA.html

Open source software R package for assaying variation of gene set enrichment over sample population.Used for microarray and RNA-seq data analysis. Gene set enrichment method that estimates variation of pathway activity over sample population in unsupervised manner.

Proper citation: GSVA (RRID:SCR_021058) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/ReactomePA/

Software R package provides functions for pathway analysis based on REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization.

Proper citation: ReactomePA (RRID:SCR_019316) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/MSnbase/

Software R package provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data. Used for isobaric tagged mass spectrometry data visualization, processing and quantitation.

Proper citation: MSnbase (RRID:SCR_019317) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/PhenStat.html

Software R package for statistical analysis of phenotypic data.Tool kit for standardized analysis of high throughput phenotypic data.

Proper citation: PhenStat (RRID:SCR_021317) Copy   

•   Source: SciCrunch Registry

https://github.com/PapenfussLab/svaNUMT

Software R package for Nuclear Mitochondrial integration events NUMT detection using structural variant calls.

Proper citation: svaNUMT (RRID:SCR_021381) Copy   

•   Source: SciCrunch Registry