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

Software for profile maximum likelihood estimation of parameters for flow cytometry data transformations.

Proper citation: flowTrans (RRID:SCR_002093) Copy   

•   Source: SciCrunch Registry

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

Software package that quantifies the similarity of cell populations across multiple flow cytometry samples using a nonparametric multivariate statistical test. The algorithm allows the users to specify a reference sample for comparison or to construct a reference sample from the available data. The output of the algorithm is a set of text files where the cell population labels are replaced by a metaset of population labels, generated from the matching process.

Proper citation: flowMap (RRID:SCR_002269) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.6/bioc/html/DEGseq.html

R package to identify differentially expressed genes from RNA-Seq data.

Proper citation: DEGseq (RRID:SCR_008480) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.11/bioc/html/easyRNASeq.html

Software that calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as ''RPKM'' or by the ''DESeq'' or ''edgeR'' package.

Proper citation: easyRNASeq (RRID:SCR_012020) Copy   

•   Source: SciCrunch Registry

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

Software tools for quality control, visualization and processing for High-Throughput Sequencing data. These include MDS plots (analogues to PCA), detecting inefficient immuno-precipitation or over-amplification artifacts, tools to identify and test for genomic regions with large accumulation of reads, and visualization of coverage profiles.

Proper citation: htSeqTools (RRID:SCR_006614) Copy   

•   Source: SciCrunch Registry

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

An R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.

Proper citation: DeconRNASeq (RRID:SCR_006713) Copy   

•   Source: SciCrunch Registry

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

Software package that allows the visualization of DNA methylation data after bisulfite sequencing.

Proper citation: methVisual (RRID:SCR_006705) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/2.12/bioc/html/seqbias.html

Software package that implements a model of per-position sequencing bias in high-throughput sequencing data using a simple Bayesian network, the structure and parameters of which are trained on a set of aligned reads and a reference genome sequence.

Proper citation: seqbias (RRID:SCR_006832) Copy   

•   Source: SciCrunch Registry

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

Software functions for reading aCGH data from image analysis output files and clone information files, creation of aCGH S3 objects for storing these data. Basic methods for accessing/replacing, subsetting, printing and plotting aCGH objects.

Proper citation: aCGH (RRID:SCR_013232) 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

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.fhcrc.org/

Fred Hutchinson Cancer Research Center and Seattle Cancer Care Alliance (SCCA) have merged to form Fred Hutchinson Cancer Center, unified adult cancer research and care center. Independent, nonprofit organization is clinically integrated part of UW Medicine and is UW Medicine’s cancer program.

Proper citation: Fred Hutchinson Cancer Center (RRID:SCR_004984) 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

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

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

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

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

Software package that provides utility functions to manage and analyse MS2/MS3 fragmentation data from ion trap mass spectrometry. It was designed for high throughput metabolomics data with many biological samples and a large numer of ion trees collected. Tests have been done with data from low-resolution mass spectrometry but could be readily extended to precursor ion based fragmentation data from high resoultion mass spectrometry.

Proper citation: iontree (RRID:SCR_002813) 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/biomaRt/

Software package that integrates BioMart data resources with data analysis software in Bioconductor. Can annotate range of gene or gene product identifiers including Entrez Gene and Affymetrix probe identifiers with information such as gene symbol, chromosomal coordinates, Gene Ontology and OMIM annotation. Enables retrieval of genomic sequences and single nucleotide polymorphism information, which can be used in data analysis.

Proper citation: biomaRt (RRID:SCR_019214) 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