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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   

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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   

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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   

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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   

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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   

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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   

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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   

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http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/vicuna

A de novo assembly program targeting populations with high mutation rates.

Proper citation: VICUNA (RRID:SCR_006302) Copy   

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http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

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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   

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http://www.broadinstitute.org/software/cprg/?q=node/39

An algorithm to identify chromosomal breakpoints using massively parallel next generation sequence data.

Proper citation: SegSeq (RRID:SCR_010826) Copy   

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http://www.harvard.edu/

Institution of higher education in the United States. Private Ivy League research university in Cambridge, Massachusetts.

Proper citation: Harvard University; Cambridge; United States (RRID:SCR_011273) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 18th,2023. Software package for genome analysis. Used for analysis of next generation genomic data in cancer.

Proper citation: IndelGenotyper (RRID:SCR_016663) Copy   

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https://software.broadinstitute.org/software/discovar/blog/

Software tool for variant calling with reference and de novo assembly of genomes. The heart of DISCOVAR is a de novo genome assembler which can generate de novo assemblies for both large and small genomes.

Proper citation: Discovar assembler (RRID:SCR_016755) Copy   

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https://depmap.org/portal/

Portal for identifying genetic and pharmacologic dependencies and biomarkers that predicts them by providing access to datasets, visualizations, and analysis tools that are being used by Cancer Dependency Map Project at Broad Institute. Project to systematically identify genes and small molecule dependencies and to determine markers that predict sensitivity. All data generated by DepMap Project are available to public under CC BY 4.0 license on quarterly basis and pre-publication.

Proper citation: Cancer Dependency Map Portal (RRID:SCR_017655) Copy   

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https://terra.bio

Open ecosystem of data repositories hosted by various partner organizations, who work together to ensure that their data can be federated across participating platforms. Open source platform for biomedical researchers to access data, run analysis tools, and collaborate. Terra powers important scientific projects including AnVIL, BioData Catalyst, Human Cell Atlas, BICCN, and many others. Easily access both open and access-controlled datasets hosted in cloud repositories. Explore, analyze, and visualize data using Jupyter Notebooks, RStudio, RShinyApps, and Galaxy.

Proper citation: Terra (RRID:SCR_021648) Copy   

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

Software package for massive single cell data processing. Enables analysis of million scale single cell RNA-seq data and is functionally comparable to Seurat and SCANPY. Command line tool, Python package and base for Cloud based analysis workflows. Supports variety of analysis tasks, such as cell and gene level quality control, highly variable gene selection, dimension reduction, kNN graph building, data integration, clustering, differential expression analysis and putative cell type annotation.

Proper citation: Pegasus (RRID:SCR_021645) Copy   

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https://clue.io

Dataset of cellular signatures that catalogs transcriptional responses of human cells to chemical and genetic perturbation. CMap contains perturbagens, expression signatures, and small molecules from cell lines.

Proper citation: CMap (RRID:SCR_016204) Copy   

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

Web interactive visualization tool for large scale single cell genomics data.Interactive web application for exploring million scale single cell datasets. Can be hosted on Google App Engine application for collaborative use or can be run in standalone mode on personal computer. Consists of client side component implemented in JavaScript and server component implemented in Python. Client uses React to manage state and WebGL to visualize variables on 2D/3D embeddings in performant manner. Server component consists of functions to manage datasets, slice variables from dataset stored in PARQUET, Zarr or H5AD formats.

Proper citation: Cirrocumulus (RRID:SCR_021646) Copy   

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https://braincelldata.org/

Web application that allows users to view and explore brain cell data. Composed of three, interlinked tabs. GeneExp allows users to plot expression of one or two genes in Slide-seq atlas. SingleCell allows users to plot gene expression in snRNA-seq atlas. CellSpatial shows spatial localization of snRNA-seq cell types in Slide-seq dataset. Used to visualize, interact with, and download data.

Proper citation: Brain Cell Data Viewer (RRID:SCR_023321) Copy   

•   Source: SciCrunch Registry