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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

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://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

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

Software application for discovering direct or indirect targets of transcription factors (TFs) using ChIP-chip or ChIP-seq, and microarray or RNA-seq gene expression data. Inputting a list of genes of potential targets of one TF from ChIP-chip or ChIP-seq, and the gene expression results, it generates a regulatory network of the TF.

Proper citation: GeneNetworkBuilder (RRID:SCR_006455) Copy   

•   Source: SciCrunch Registry

http://crcview.hegroup.org/

Web-based microarray data analysis and visualization system powered by CRC, or Chinese Restaurant cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. It also incorporates several gene expression analysis programs from Bioconductor, including GOStats, genefilter, and Heatplus. CRCView also installs from the Bioconductor system 78 annotation libraries of microarray chips for human (31), mouse (24), rat (14), zebrafish (1), chicken (1), Drosophila (3), Arabidopsis (2), Caenorhabditis elegans (1), and Xenopus Laevis (1). CRCView allows flexible input data format, automated model-based CRC clustering analysis, rich graphical illustration, and integrated Gene Ontology (GO)-based gene enrichment for efficient annotation and interpretation of clustering results. CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. You need to register for an account in the system to store your data and analyses. The data and results can be visited again anytime you log in.

Proper citation: CRCView (RRID:SCR_007092) 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/release/bioc/html/ReadqPCR.html

A software package that provides functions to read raw RT-qPCR data of different platforms.

Proper citation: ReadqPCR (RRID:SCR_000030) 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

http://bioconductor.org/packages/epialleleR/

Software R package for calling hypermethylated variant epiallele frequencies at level of genomic regions or individual cytosines in next-generation sequencing data using binary alignment map files as input. Used for sensitive allele specific methylation analysis in next generation sequencing data. Used for sensitive detection, quantification and visualisation of mosaic epimutations in methylation sequencing data.

Proper citation: epialleleR (RRID:SCR_023913) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/Orthology.eg.db/

Software R package to provide orthology mappings between species, based on NCBI Gene IDs and NCBI orthology mappings.

Proper citation: Orthology.eg.db (RRID:SCR_024740) Copy   

•   Source: SciCrunch Registry

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

Software R package provides central location where curated data from experiments, publications or training courses can be accessed.

Proper citation: ExperimentHub (RRID:SCR_024820) Copy   

•   Source: SciCrunch Registry

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

Software package which provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.

Proper citation: topGO (RRID:SCR_014798) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/KEGGgraph/

Software R package interface between KEGG pathway and graph object as well as collection of tools to analyze, dissect and visualize these graphs.

Proper citation: KEGGgraph (RRID:SCR_023788) Copy   

•   Source: SciCrunch Registry