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http://bioconductor.org/packages/GenomicFeatures/

Software R package for making and manipulating transcript centric annotations. Used to download the genomic locations of the transcripts, exons and cds of a given organism, from either the UCSC Genome Browser or a BioMart database.

Proper citation: GenomicFeatures (RRID:SCR_016960) Copy   

•   Source: SciCrunch Registry

https://github.com/SofieVG/FlowSOM

Software tool to analyze Flow or mass cytometry data using a Self-Organizing Map. Used to obtain an overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise.

Proper citation: FlowSOM (RRID:SCR_016899) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/GenomicRanges/

Software R package for computing and annotating genomic ranges. Used for storing and manipulating genomic intervals and variables defined along genome.

Proper citation: Genomic Ranges (RRID:SCR_017051) Copy   

•   Source: SciCrunch Registry

https://scfind.sanger.ac.uk/

Software R package as search tool for single cell RNA-seq data by gene lists. Builds index from scRNA-seq datasets which organizes information in suitable and compact manner so that datasets can be very efficiently searched for either cells or cell types in which given list of genes is expressed.

Proper citation: Scfind (RRID:SCR_017339) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/EGAD/

Software package implements series of highly efficient tools to calculate functional properties of networks based on guilt by association methods. Ultra fast functional analysis of gene networks.

Proper citation: Extending Guilt by Association by Degree (RRID:SCR_018427) Copy   

•   Source: SciCrunch Registry

http://master.bioconductor.org/packages/2.13/bioc/html/BHC.html

Software package that performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture) to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. This avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric. This implementation accepts multinomial (i.e. discrete, with 2+ categories) or time-series data and also includes a randomised algorithm which is more efficient for larger data sets.

Proper citation: BHC (RRID:SCR_006399) Copy   

•   Source: SciCrunch Registry

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

R package with tools that use probabilistic inference of ChIP-Seq. It follows an empirical Bayes mixture model approach.

Proper citation: PICS (RRID:SCR_001093) Copy   

•   Source: SciCrunch Registry

https://visrsoftware.github.io/

Software as an R-based visual framework for analysis of sequencing datasets. Provides a framework for integrative and interactive analyses.

Proper citation: VisR (RRID:SCR_016658) 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/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://bioconductor.org/packages/SimFFPE/

Software R package to simulate artifact chimeric reads specifically generated in next generation sequencing process of formalin fixed paraffin embedded tissue. Simulates normal reads as well as artifact chimeric reads that are enriched in FFPE samples. These artifact chimeric reads can lead to large amounts of false positive structural variant calls.

Proper citation: SimFFPE (RRID:SCR_021085) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/DESeq2.html

Software package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.

Proper citation: DESeq2 (RRID:SCR_015687) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/AUCell/

Software R package to identify cells with active gene sets in single cell RNA-seq data. Used for analysis of gene set activity in single cell RNA-seq data.Used to calculate whether critical subset of input gene set is enriched within expressed genes for each cell.

Proper citation: AUCell (RRID:SCR_021327) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/StructuralVariantAnnotation/

Software R package for structural variant analysis. Contains helper functions for dealing with structural variants in VCF format. Contains functions for parsing VCFs from number of popular callers as well as functions for dealing with breakpoints involving two separate genomic loci encoded as GRanges objects.

Proper citation: StructuralVariantAnnotation (RRID:SCR_018683) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/EnhancedVolcano/

Software R package to produce publication ready volcano plots with enhanced colouring and labeling. Used to visualise results of differential expression analyses.

Proper citation: EnhancedVolcano (RRID:SCR_018931) 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

http://bios.unc.edu/~weisun/software/asSeq.htm

Software that establishes a statistical framework for future developments of eQTL (expression quantitative trait locus) mapping methods using RNA-seq data (e.g., linkage-based eQTL mapping), and the joint study of multiple genetic markers and/or multiple genes. This R package has been submitted to R/bioconductor. It will be available on bioconductor soon. It is recommended to install this R package from bioconductor. You can also install this R package from the source code by yourself. Since the R package contains C code, a C complier is required for installation. With both R and appropriate c complier installed, this R package can be installed using the following command (in Mac Terminal window or Windows command window) R CMD INSTALL asSeq

Proper citation: asSeq (RRID:SCR_001625) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/resolver/SCR_002250

THIS RESOURCE IS NO LONGER IN SERVICE. Documented Jul 19, 2024. Metadatabase manually curated that provides web accessible tools related to genomics, transcriptomics, proteomics and metabolomics. Used as informative directory for multi-omic data analysis.

Proper citation: OMICtools (RRID:SCR_002250) Copy   

•   Source: SciCrunch Registry

http://bioinfo.cipf.es/noiseq/doku.php?id=start

Software used for the identification of differentially expressed genes from count data or previously normalized count data. It empirically models the noise distribution of count changes by contrasting fold-change differences (M) and absolute expression differences (D) for all the features in samples within the same condition. This reference distribution is then used to assess whether the M-D values computed between two conditions for a given gene is likely to be part of the noise or represent a true differential expression.

Proper citation: NOISeq (RRID:SCR_003002) Copy   

•   Source: SciCrunch Registry