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http://www.broadinstitute.org/

Biomedical and genomic research center located in Cambridge, Massachusetts, United States. Nonprofit research organization under the name Broad Institute Inc., and is partners with Massachusetts Institute of Technology, Harvard University, and the five Harvard teaching hospitals. Dedicated to advance understanding of biology and treatment of human disease to improve human health.

Proper citation: Broad Institute (RRID:SCR_007073) Copy   

•   Source: SciCrunch Registry

http://lincs.hms.harvard.edu/db/

Database that contains all publicly available HMS LINCS datasets and information for each dataset about experimental reagents and experimental and data analysis protocols. Experimental reagents include small molecule perturbagens, cells, antibodies, and proteins.

Proper citation: HMS LINCS Database (RRID:SCR_006454) Copy   

•   Source: SciCrunch Registry

https://www.broadinstitute.org/ccle/

A collaborative project between the Broad Institute and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation, with the goal of conducting a detailed genetic and pharmacologic characterization of a large panel of human cancer models. The CCLE also works to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.

Proper citation: Cancer Cell Line Encyclopedia (RRID:SCR_013836) Copy   

•   Source: SciCrunch Registry

http://life.ccs.miami.edu/life/

LIFE search engine contains data generated from LINCS Pilot Phase, to integrate LINCS content leveraging semantic knowledge model and common LINCS metadata standards. LIFE makes LINCS content discoverable and includes aggregate results linked to Harvard Medical School and Broad Institute and other LINCS centers, who provide more information including experimental conditions and raw data. Please visit LINCS Data Portal.

Proper citation: LINCS Information Framework (RRID:SCR_003937) Copy   

•   Source: SciCrunch Registry

https://cellarium.ai

Software platform to annotate cell types.

Proper citation: Cellarium (RRID:SCR_025438) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics.org/go2msig/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 24, 2020. Software tool as automated Gene Ontology based multi species gene set generator for gene set enrichment analysis. Used to generate gene sets required for Gene Set Enrichment Analysis for almost any organism for which GO term association data exists.
Gene set collections can be automatically created for wide variety of species.

Proper citation: GO2MSIG (RRID:SCR_018359) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_sting_gatk_walkers_genotyper_UnifiedGenotyper.html

A multiple-sample, technology-aware SNP and indel caller.

Proper citation: UnifiedGenotyper (RRID:SCR_004710) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/igv/

A high-performance visualization tool for interactive exploration of large, integrated genomic datasets.

Proper citation: Integrative Genomics Viewer (RRID:SCR_011793) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/software/genepattern

A powerful genomic analysis platform that provides access to hundreds of tools for gene expression analysis, proteomics, SNP analysis, flow cytometry, RNA-seq analysis, and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.

Proper citation: GenePattern (RRID:SCR_003201) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/mpg/magenta/

A computational tool that tests for enrichment of genetic associations in predefined biological processes or sets of functionally related genes, using genome-wide genetic data as input.

Proper citation: MAGENTA (RRID:SCR_003422) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/mpg/grail/

A tool to examine relationships between genes in different disease associated loci. Given several genomic regions or SNPs associated with a particular phenotype or disease, GRAIL looks for similarities in the published scientific text among the associated genes. As input, users can upload either (1) SNPs that have emerged from a genome-wide association study or (2) genomic regions that have emerged from a linkage scan or are associated common or rare copy number variants. SNPs should be listed according to their rs#''s and must be listed in HapMap. Genomic Regions are specified by a user-defined identifier, the chromosome that it is located on, and the start and end base-pair positions for the region. Grail can take two sets of inputs - Query regions and Seed regions. Seed regions are definitely associated SNPs or genomic regions, and Query regions are those regions that the user is attempting to evaluate agains them. In many applications the two sets are identical. Based on textual relationships between genes, GRAIL assigns a p-value to each region suggesting its degree of functional connectivity, and picks the best candidate gene. GRAIL is developed by Soumya Raychaudhuri in the labs of David Altshuler and Mark Daly at the Center for Human Genetic Research of Massachusetts General Hospital and Harvard Medical School, and the Broad Institute. GRAIL is described in manuscript, currently in preparation.

Proper citation: Gene Relationships Across Implicated Loci (RRID:SCR_008537) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/scientific-community/science/programs/cancer/ultrasome

An efficient methodology for detecting and delineating gains and losses of chromosomal material in DNA copy-number data.

Proper citation: Ultrasome (RRID:SCR_008465) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/invex/

A permutation-based method (written in Python) for ascertaining genes with a somatic mutation distribution showing evidence of positive selection for non-silent mutations.

Proper citation: InVEx (RRID:SCR_008734) Copy   

•   Source: SciCrunch Registry

http://trinityrnaseq.sourceforge.net/

Software for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data.

Proper citation: Trinity (RRID:SCR_013048) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/annotation/medea/

THIS RESOURCE IS NO LONGER IN SERVCE, documented June, 2019.Comparative Genomic Visualization with Adobe Flash.

Proper citation: MEDEA (RRID:SCR_013356) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/mutsig

Software that analyzes lists of mutations discovered in DNA sequencing, to identify genes that were mutated more often than expected by chance given background mutation processes.

Proper citation: MutSig (RRID:SCR_010779) Copy   

•   Source: SciCrunch Registry

https://www.broadinstitute.org/scientific-community/science/programs/genome-sequencing-and-analysis/computational-rd/computational-

Software tool as whole genome shotgun assembler that can generate high quality genome assemblies using short reads (~100bp) such as those produced by the new generation of sequencers.

Proper citation: ALLPATHS-LG (RRID:SCR_010742) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/annotation/genome/magnaporthe_comparative/MultiHome.html

The Magnaporthe comparative genomics database provides accesses to multiple fungal genomes from the Magnaporthaceae family to facilitate the comparative analysis. As part of the Broad Fungal Genome Initiative, the Magnaporthe comparative project includes the finished M. oryzae (formerly M. grisea) genome, as well as the draft assemblies of Gaeumannomyces graminis var. tritici and M. poae. It provides users the tools to BLAST search, browse genome regions (to retrieve DNA, find clones, and graphically view sequence regions), and provides gene indexes and genome statistics. We were funded to attempt 7x sequence coverage comprising paired end reads from plasmids, Fosmids and BACs. Our strategy involves Whole Genome Shotgun (WGS) sequencing, in which sequence from the entire genome is generated and reassembled. Our specific aims are as follows: 1. Generate and assemble sequence reads yielding 7X coverage of the Magnaporthe oryzae genome through whole genome shotgun sequencing. 2. Generate and incorporate BAC and Fosmid end sequences into the genome assembly to provide a paired-end of average every 2 kb. 3. Integrate the genome sequence with existing physical and genetic map information. 4. Perform automated annotation of the sequence assembly. 5. Distribute the sequence assembly and results of our annotation and analysis through a freely accessible, public web server and by deposition of the sequence assembly in GenBank.

Proper citation: Magnaporthe comparative Database (RRID:SCR_003079) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/genome_bio/siphy/

Software that implements rigorous statistical tests to detect bases under selection from a multiple alignment data. It takes full advantage of deeply sequenced phylogenies to estimate both unlikely substitution patterns as well as slowdowns or accelerations in mutation rates. It can be applied as an Hidden Markov Model (HMM), in sliding windows, or to specific regions.

Proper citation: SiPhy (RRID:SCR_000564) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/contest

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 8,2025. A software tool (and method) for estimating the amount of cross-sample contamination in next generation sequencing data.

Proper citation: ContEst (RRID:SCR_000595) Copy   

•   Source: SciCrunch Registry