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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

Ricopili is a tool for visualizing regions of interest in select GWAS data sets. How it works Choose a data set and enter a genomic location or a gene name in the form below. A .pdf plot will be generated, as well as a text file with single SNP results. You can also specify the following options: * Clumping: Independent regions will be colored differently, to highlight LD. If you request more than one clump, be sure to have at least one SNP passing the specified p-value-threshold (for performance reasons.) * SNP: SNPs in the region are colored by LD to this index SNP. * Anonymity: Frequency information is from HapMap to protect anonymity. * NHGRI results: Results from the NHGRI GWAS catalog will be included in the plot. Finally, please note that this tool is in development (it was released on September 19th, 2011) and should be considered beta. In particular, our development server is not equipped for high traffic. If the server fails to respond to your request, please try again at a later time.

Proper citation: Ricopili (RRID:SCR_004496) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/broadinstitute/ichorCNA

Software tool that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. Used to simultaneously segment genome, predict large scale copy number alterations, and estimate tumor fraction of ultra low pass whole genome sequencing sample.

Proper citation: ichorCNA (RRID:SCR_024768) Copy   

•   Source: SciCrunch Registry

http://firebrowse.org/

Portal provides access to cancer genomic data from variety of analyses: clinical, copy number, miR, miRseq, mRNA, mRNAseq, mutation and pathway analyses. Provides comprehensive suite of interdependent analyses of those data, including: correlations, clustering, and GISTIC and MutSigCV. Companion portal to the Broad Institute GDAC Firehose analysis pipeline, and was developed to cull and analyze data generated by The Cancer Genome Atlas (TCGA), which characterizes and identifies genomic patterns in human cancer models.

Proper citation: FireBrowse (RRID:SCR_026320) Copy   

•   Source: SciCrunch Registry

https://github.com/broadinstitute/multiVIB

Software tool as comprehensive framework for integration of single-cell omics data with probabilistic contrastive learning.

Proper citation: multiVIB (RRID:SCR_027589) Copy   

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https://www.broadinstitute.org/genomics

Facility that generates, analyzes, and interprets high-throughput genomic data to understand the genetic basis of disease. Genomics Platform has played leadership role in the design, data generation, and methods development in support of major genomic resource projects.Through the Broad Clinical Labs (BCL), formerly known as the Clinical Research Sequencing Platform (CRSP), it supports clinical trials, diagnostic testing, and major initiatives, including COVID-19 testing. Offers services including Nucleic Acid Extractions, Single Cell Sequencing (using 10x Genomics products), and GWAS Arrays.

Proper citation: Broad Institute Genomics Platform (RRID:SCR_027987) Copy   

•   Source: SciCrunch Registry

https://gatk.broadinstitute.org/hc/en-us/articles/360036350452-VariantFiltration

Software command-line tool designed for hard-filtering variant callsets (VCF files) by applying user-defined criteria to annotate, rather than remove, low-quality variants. It marks fails in the FILTER field (e.g., using JEXL expressions to filter by DP, QD, or FS), making it essential for filtering small datasets, non-model organisms, or whenever Variant Quality Score Recalibration (VQSR) is not feasible

Proper citation: GATK VariantFiltration (RRID:SCR_028441) Copy   

•   Source: SciCrunch Registry

https://software.broadinstitute.org/gatk/

A software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)

Proper citation: GATK (RRID:SCR_001876) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/rat/public/index_main.html

Data set of pictures representing genetic linkage maps of the rat resulting from the integration of two F2 intercrosses (SHRSP x BN and FHH x ACI). Markers in common between the two crosses are connected by a line to define integration points. There are a total of 4,786 markers on these maps; 4375 WIBR/MIT CGR markers; 223 markers from the previously released Mit/Mgh rat maps and 188 markers from the National Institute of Arthritis and Musculoskeletal and Skin Diseases Arb rat maps. Pictures are drawn to a scale of 5cm (Kosombi) per inch. The changes in color of the backbone of the chromosome for each cross represents the space between any two framework loci. Markers in blue type are framework loci. Markers in green type are unique placement loci. Markers in black type are bouncy placement loci.

Proper citation: Genetic Maps of the Rat Genome (RRID:SCR_002266) Copy   

•   Source: SciCrunch Registry

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

A computer program and web-based service for the rapid retrieval of linkage disequilibrium proxy single nucleotide polymorphism (SNP) results given input of one or more query SNPs and based on empirical observations from the International HapMap Project and the 1000 Genomes Project. A series of filters allow users to optionally retrieve results that are limited to specific combinations of genotyping platforms, above specified pairwise r2 thresholds, or up to a maximum distance between query and proxy SNPs. SNAP can also generate linkage disequilibrium plots

Proper citation: SNAP - SNP Annotation and Proxy Search (RRID:SCR_002127) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/

Independent, coeducational, privately endowed university, organized into five schools: architecture and planning; engineering; humanities, arts, and social sciences; management; and science.

Proper citation: Massachusetts Institute of Technology; Massachusetts; USA; (RRID:SCR_000977) Copy   

•   Source: SciCrunch Registry

http://jbrowse.org/

A high-performance visualization tool for interactive exploration of large, integrated genomic datasets written primarily in JavaScript. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.

Proper citation: JBrowse (RRID:SCR_001004) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/science/programs/genome-biology/computational-rd/somaticcall-manual

Software program that finds single-base differences (substitutions) between sequence data from tumor and matched normal samples. It is designed to be highly stringent, so as to achieve a low false positive rate. It takes as input a BAM file for each sample, and produces as output a list of differences (somatic mutations). Note: This software package is no longer supported and information on this page is provided for archival purposes only.

Proper citation: SomaticCall (RRID:SCR_001196) Copy   

•   Source: SciCrunch Registry

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

Software for the reliable and accurate identification of somatic point mutations in next generation sequencing data of cancer genomes.

Proper citation: MuTect (RRID:SCR_000559) Copy   

•   Source: SciCrunch Registry

http://www.cs.utah.edu/~miriah/pathline/Overview.html

Software visualization tool for comparative functional genomics that supports analysis of three types of biological data at once: functional data such as gene activity measurements; pathway data that presents a series of reactions within a cellular process; and phylogenetic data describing ancestral relationships between species. The design of Pathline includes two new visual encoding techniques. The first is an encoding of a linearized metabolic pathway representation that provides appropriate topological information and supports the comparison of quantitative data along the pathway. The second is a curvemap, a matrix layout of temporal expression data for enhanced perception of trends in gene and cell activity levels across multiple species.

Proper citation: Pathline (RRID:SCR_000635) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/node/305

The Connectivity Map aims to generate a detailed map that links gene patterns associated with disease to corresponding patterns produced by drug candidates and a variety of genetic manipulations. The Connectivity Map is the most comprehensive effort yet for using genomics in a drug-discovery framework. It allows researchers to screen compounds against genome-wide disease signatures, rather than a pre-selected set of target genes. Drugs are paired with diseases using sophisticated pattern-matching methods with a high level of resolution and specificity. To build a Connectivity Map, the Broad Institute brings together molecular biologists, genomics specialists, computational scientists, pharmacologists, chemists and chemical biologists, as well as expertise from across the breadth and depth of medicine.Connectivity map is a large public database of signatures of drugs and genes, and pattern-matching tools to detect similarities among these signatures.The parent site for the Broad Institute at MIT has a software library of software applications developed for use in genetic analysis.

Proper citation: National Institute of Mental Health (NIMH) Human Genetics Initiative (RRID:SCR_007436) Copy   

•   Source: SciCrunch Registry