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https://github.com/powellgenomicslab/ascend

Software R package for analysis of single cell RNA-seq expression, normalization and differential expression data. Provides framework to perform cell and gene filtering, quality control, normalization, dimension reduction, clustering, differential expression, and visualization functions.

Proper citation: ascend (RRID:SCR_017257) 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://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/Basic4Cseq.html

An R/Bioconductor package for basic filtering, analysis and subsequent near-cis visualization of 4C-seq data. Virtual fragment libraries can be created for any BSGenome package, and filter functions for both reads and fragments and basic quality controls are included. Fragment data in the vicinity of the experiment's viewpoint can be visualized as a coverage plot based on a running median approach and a multi-scale contact profile.

Proper citation: Basic4Cseq (RRID:SCR_002836) Copy   

•   Source: SciCrunch Registry

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

Software package that provides an interface to simulate metabolic reconstruction from the BiGG database and other metabolic reconstruction databases. The package facilitates flux balance analysis (FBA) and the sampling of feasible flux distributions. Metabolic networks and estimated fluxes can be visualized with hypergraphs.

Proper citation: BiGGR (RRID:SCR_002854) Copy   

•   Source: SciCrunch Registry

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

R package providing functions to assess and to compare the performance of risk prediction (survival) models.

Proper citation: SurvComp (RRID:SCR_003054) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.10/bioc/html/R453Plus1Toolbox.html

R software toolbox of functions for the analysis of data generated by Roche's 454 sequencing platform. Additional functions are included for quality assurance, annotation and visualization of detected variants, complementing the software tools shipped by Roche with their product. A pipeline for the detection of structural variants is provided.

Proper citation: R453Plus1Toolbox (RRID:SCR_001105) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software package for DNA methylation data analysis and visualization. A new class is defined to keep the chromosome location information together with the data. The current version of the package mainly focuses on analyzing the Illumina Infinium methylation array data, but most methods can be generalized to other methylation array or sequencing data.

Proper citation: methyAnalysis (RRID:SCR_001290) Copy   

•   Source: SciCrunch Registry

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

Software package for survival time prediction based on a piecewise baseline hazard Cox regression model. It is meant to help predict survival times in the presence of high-dimensional explanatory covariates.

Proper citation: RCASPAR (RRID:SCR_001253) Copy   

•   Source: SciCrunch Registry

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

Software package for dimension Reduction for Array CGH Data with Minimal Information Loss.

Proper citation: CGHregions (RRID:SCR_001278) Copy   

•   Source: SciCrunch Registry

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

Software package for quantile smoothing and genomic visualization of array data.

Proper citation: quantsmooth (RRID:SCR_001271) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.0/bioc/html/SNPchip.html

Software package that contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor, including the R packages Biobase and oligo. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality.

Proper citation: SNPchip (RRID:SCR_001269) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.1/bioc/html/VanillaICE.html

Software package using Hidden Markov Models for characterizing chromosomal alterations in high throughput SNP arrays.

Proper citation: VanillaICE (RRID:SCR_001268) Copy   

•   Source: SciCrunch Registry

https://rdrr.io/bioc/sRAP/

Software package that provides a pipeline for gene expression analysis (primarily for RNA-Seq data). The normalization function is specific for RNA-Seq analysis, but all other functions (Quality Control Figures, Differential Expression and Visualization, and Functional Enrichment via BD-Func) will work with any type of gene expression data.

Proper citation: sRAP (RRID:SCR_001297) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software package for quality assessment and to identify differentially expressed genes in the Affymetrix gene expression data.

Proper citation: AffyExpress (RRID:SCR_001321) Copy   

•   Source: SciCrunch Registry

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

Software library that contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. It is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions.

Proper citation: MACAT (RRID:SCR_001350) Copy   

•   Source: SciCrunch Registry

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

Software that graphically displays correlation in microarray data that is due to insufficient normalization.

Proper citation: maCorrPlot (RRID:SCR_001348) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/aroma.light.html

Light-weight software package for normalization and visualization of microarray data using only basic R data types. Software can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.

Proper citation: aroma.light (RRID:SCR_001312) Copy   

•   Source: SciCrunch Registry

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

Software functions for normalization of two-color microarrays by optimised local regression and for detection of artifacts in microarray data.

Proper citation: OLIN (RRID:SCR_001304) Copy   

•   Source: SciCrunch Registry