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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   

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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   

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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   

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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   

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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   

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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   

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https://github.com/broadinstitute/Drop-seq

Software Java tools for analyzing Drop-seq data. Used to analyze gene expression from thousands of individual cells simultaneously. Analyzes mRNA transcripts while remembering origin cell transcript.

Proper citation: Drop-seq tools (RRID:SCR_018142) Copy   

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https://jump-cellpainting.broadinstitute.org

Consortium is creating new data driven approach to drug discovery based on cellular imaging, image analysis, and high dimensional data analytics. Creates public data set to validate and scale up this image based drug discovery strategy. By coordinating assay procedures across partners, future created data will be well matched. Aims to make cell images as computable as genomes and transcriptomes.

Proper citation: JUMP Cell Painting Consortium (RRID:SCR_021868) Copy   

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https://singlecell.broadinstitute.org/single_cell

Portal specializes in visualizing and disseminating single cell data. Allows you to use natural language and faceted search to discover other scientists’ research and share your own findings. Each study includes information on cell types, singular or multiple gene expression, and spatial transcriptomics. Interactive visualizations allow to explore cell clusters and search for related genes.

Proper citation: Single Cell Portal (RRID:SCR_014816) Copy   

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https://broadinstitute.github.io/warp/docs/Pipelines/Smart-seq2_Single_Nucleus_Multi_Sample_Pipeline/README

Software pipeline for single-nucleus RNAseq data generated by Smart-seq2 assays. Developed in collaboration with the BRAIN Initiative Cell Census Network (BICCN) to process single-nucleus RNAseq (snRNAseq) data generated by Smart-seq2 assays. Used to simultaneously process multiple libraries of single nuclei Smart-seq2 and Smart-seq4 data. For each library (nucleus), the pipeline trims paired FASTQ files, aligns trimmed reads to the genome, counts intronic and exonic reads, and calculates quality control metrics. Counts and metrics for all libraries are combined into merged Loom formatted count matrix.

Proper citation: Smart-seq2 Multi-Sample Pipeline (RRID:SCR_018920) Copy   

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https://github.com/broadinstitute/warp/blob/master/pipelines/skylab/smartseq2_single_sample/SmartSeq2SingleSample.wdl

Software tool designed by Data Coordination Platform of Human Cell Atlas to process single-cell RNAseq data generated by Smart-seq2 assays.Processes stranded or unstranded, paired- or single-end, scRNA-seq data from an individual cell.

Proper citation: Smart-seq2 Single Sample Pipeline (RRID:SCR_021228) Copy   

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https://software.broadinstitute.org/morpheus/

Software tool for versatile matrix visualization and analysis. Program to generate heatmaps from input data. JavaScript matrix visualization and analysis.

Proper citation: Morpheus by Broad Institute (RRID:SCR_017386) Copy   

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https://software.broadinstitute.org/cancer/cga/polysolver

Software tool for HLA typing based on whole exome sequencing data and infers alleles for three major MHC class I genes. Enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using inferred alleles as reference.

Proper citation: Polysolver (RRID:SCR_022278) Copy   

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https://broadinstitute.github.io/warp/docs/Pipelines/SlideSeq_Pipeline/README/

Software pipeline developed in collaboration with BRAIN Initiative Cell Census Network and BRAIN Initiative Cell Atlas Network. Supports processing of spatial transcriptomic data generated with Slide-seq commercialized as Curio Seeker assay.

Proper citation: Slide-seq Pipeline (RRID:SCR_023379) Copy   

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https://portals.broadinstitute.org/cmap/

Collection of genome-wide transcriptional expression data from cultured human cells treated with bioactive small molecules and simple pattern-matching algorithms. camp aims to enable the discovery of functional connections between drugs, genes and diseases through the transitory feature of common gene-expression changes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Connectivity Map 02 (RRID:SCR_015674) Copy   

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https://cumulus.readthedocs.io/en/stable

Software tool as cloud based single cell genomics and spatial transcriptomics data analysis framework that is scalable to massive amounts of data and able to process variety of data types. Consists of cloud analysis workflow, Python analysis package and visualization application. Supports analysis of single-cell RNA-seq, CITE-seq, Perturb-seq, single-cell ATAC-seq, single-cell immune repertoire and spatial transcriptomics data.

Proper citation: Cumulus (RRID:SCR_021644) Copy   

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https://zlab.bio/guide-design-resources

Laboratory portal about research including new approaches for precision gene editing, delivery of molecular and genetic cargo, discovery of novel programmable systems, and engineering of immune system to develop next generation of therapeutics. Provides collection of tools for guide design.CRISPR.MIT.EDU of Guide Design Tools is no longer available, documented on August 28,2020.

Proper citation: Guide Design Resources (RRID:SCR_018982) Copy   

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http://www.broad.mit.edu/annotation/fungi/fgi/

Produces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.

Proper citation: Fungal Genome Initiative (RRID:SCR_003169) Copy   

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http://www.broadinstitute.org/software/syzygy/

A targeted sequencing post processing analysis software tool that allows: 1. SNP and indel detection; 2. Allele frequency estimation; 3. Single-marker association test; 4. Group-wise marker test association; 5. Experimental QC summary (%dbSNP, Ts/Tv, Ns/S); 6. Power to detect variant. (entry from Genetic Analysis Software)

Proper citation: SYZYGY (RRID:SCR_002157) Copy   

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http://exac.broadinstitute.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. An aggregated data platform for genome sequencing data created by a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on this website spans 61,486 unrelated individuals sequenced as part of various disease-specific and population genetic studies. They have removed individuals affected by severe pediatric disease, so this data set should serve as a useful reference set of allele frequencies for severe disease studies. All of the raw data from these projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects. They ask that you not publish global (genome-wide) analyses of these data until after the ExAC flagship paper has been published, estimated to be in early 2015. If you''re uncertain which category your analyses fall into, please email them. The aggregation and release of summary data from the exomes collected by the Exome Aggregation Consortium has been approved by the Partners IRB (protocol 2013P001477, Genomic approaches to gene discovery in rare neuromuscular diseases).

Proper citation: ExAc (RRID:SCR_004068) Copy   

•   Source: SciCrunch Registry