Cancer Program Tool Resources

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TumorPortal

Genes, Cancers, and DNA Mutations
http://TumorPortal.org

SegSeq

SegSeq is an algorithm to identify chromosomal breakpoints using massively parallel next generation sequence data.

RNA-SeQC

RNA-SeQC is a java program which computes a series of quality control metrics for RNA-seq data.

PathSeq

PathSeq is a computational tool for the identification and analysis of microbial sequences in high-throughput human sequencing data that is designed to work with large numbers of sequencing reads in a scalable manner.

Oncotator

Oncotator is a tool for annotating human genomic point mutations and indels with data relevant to cancer researchers. Annotations are aggregated from genomic annotations, protein annotations, and cancer annotations.

Oncotator

Oncotator is a tool for annotating human genomic point mutations and indels with data relevant to cancer researchers. Annotations are aggregated from genomic annotations, protein annotations, and cancer annotations.

MutSig

MutSig (for "Mutation Significance") is a package of tools for analyzing mutation data.  It operates on a cohort of patients and identifies mutations, genes, and other genomic elements predicted to be driver candidates.

MuTect

MuTect is a method developed at the Broad Institute for the reliable and accurate identification of somatic point mutations in next generation sequencing data of cancer genomes.

Molecular Signatures DB (MSigDB)

The Molecular Signatures Database (MSigDB) is a collection of annotated gene sets for use with GSEA software.

JuncBASE

JuncBASE (Junction-Based Analysis of Splicing Events) is used to identify and classify alternative splicing events from RNA-Seq data. Alternative splicing events are identified from splice junction reads from RNA-Seq read alignments allowing for analysis of unannoated or aberrant alternative splicing. JuncBASE also uses read counts to quantify the relative expression of each isoform and identifies splice events that are significantly differentially expressed across two or more samples. 

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