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

Software open-source, cloud-optimized pipeline developed in collaboration with members of the BRAIN Initiative (BICCN and BICAN Sequencing Working Group) and SCORCH. It supports the processing of 10x single-nucleus data generated with 10x Multiome ATAC-seq (Assay for Transposase-Accessible Chromatin), a technique used in molecular biology to assess genome-wide chromatin accessibility.

Proper citation: ATAC Pipeline (RRID:SCR_024656) Copy   

•   Source: SciCrunch Registry
  

https://bioinformaticshome.com/tools/rna-seq/descriptions/LIGER.html

Software R package for integrating and analyzing multiple single-cell datasets. It relies on integrative non-negative matrix factorization to identify shared and dataset-specific factors. Used for analysis of multiple scRNA-seq data sets.

Proper citation: LIGER (RRID:SCR_018100) Copy   

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http://lincscloud.org/

A catalog of gene-expression data collected from human cells treated with chemical compounds and genetic reagents. Computational methods to reduce the number of necessary genomic measurements along with streamlined methodologies enable the current effort to significantly increase the size of the CMap database and along with it, our potential to connect human diseases with the genes that underlie them and the drugs that treat them. The NIH has funded a large expansion of the Connectivity Map dataset through the Library of Integrated Network-based Cellular Signatures (LINCS). The Broad Institute's LINCS center aims to create a first installment of data generation and analysis for the LINCS program. Through these data LINCS intends to accelerate the discovery process by systematically revealing connections between genes/compounds discovered in screens and molecular pathways that underlie disease states.

Proper citation: LINCS Connectivity Map (RRID:SCR_002639) Copy   

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

A tool for annotating human genomic point mutations and indels with data relevant to cancer researchers. Genomic Annotations, Protein Annotations, and Cancer Annotations are aggregated from many resources. A standalone version of Oncotator is being developed.

Proper citation: Oncotator (RRID:SCR_005183) Copy   

•   Source: SciCrunch Registry
  

http://cellprofiler.org

Software tool to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically. It counts cells and also measures the size, shape, intensity and texture of every cell (and every labeled subcellular compartment) in every image. It was designed for high throughput screening but can perform automated image analysis for images from time-lapse movies and low-throughput experiments. CellProfiler has an increasing number of algorithms to identify and measure properties of neuronal cell types.

Proper citation: CellProfiler Image Analysis Software (RRID:SCR_007358) Copy   

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

A tool for visualizing and manually annotating whole genomes that can be run as Applet or Webstart application as well as standalone application.

Proper citation: Argo Genome Browser (RRID:SCR_011763) Copy   

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https://www.hmpdacc.org/ihmp/

Provides human microbiome datasets and minimum reporting standards established by DCC, from both initial HMP-1 phase and iHMP. Offers to query and retrieve metagenomic, metatranscriptomic, human genetic, microbial culture, and many other data types from each project. Provides integrated longitudinal datasets from both microbiome and host from different cohort studies of microbiome associated conditions.

Proper citation: Integrative Human Microbiome Project (RRID:SCR_015586) Copy   

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http://tbdb.org

Database providing integrated access to genome sequence, expression data and literature curation for Tuberculosis (TB) that houses genome assemblies for numerous strains of Mycobacterium tuberculosis (MTB) as well assemblies for over 20 strains related to MTB and useful for comparative analysis. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives, including over 3000 MTB microarrays, 95 RT-PCR datasets, 2700 microarrays for human and mouse TB related experiments, and 260 arrays for Streptomyces coelicolor. (July 2010) To enable wide use of these data, TBDB provides a suite of tools for searching, browsing, analyzing, and downloading the data.

Proper citation: Tuberculosis Database (RRID:SCR_006619) Copy   

•   Source: SciCrunch Registry
  

http://bard.nih.gov/

Database that allows scientists without specialized training to effectively utilize Molecular Libraries Program (MLP) data. It allows the research community to utilize and develop new chemical probes to explore biological functions by building a central, permanently accessible link to all aspects of chemical biology data and analyses. The project is split into two basic segments, the first segment delivering functionality for a data dictionary, as well as assay protocol and data entry tools. The second builds a data warehouse for analysis and visualization, accessible through a public RESTful API. They will initially deploy two clients that will use this API - a web-based interface and a desktop application. Advanced access to data and the platforms will also be available to support plug-in development and the repackaging of data by others. Initially the project will focus on small molecule assays. Features: * allow scientists to annotate assay data using a common, shared language * provide facile access to data, integrating existing chemical biology and computational resources * enable meaningful analysis and interpretation of discovery data by the research community * support hypothesis generation for iterative probe- and drug-discovery projects * inform the entire small molecule discovery and development process, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BARD (RRID:SCR_006283) Copy   

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http://www.broadinstitute.org/mammals/haploreg/haploreg.php

HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.

Proper citation: HaploReg (RRID:SCR_006796) Copy   

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https://data.broadinstitute.org/chembank/assay

ChemBank is a public, web-based informatics environment that includes freely available data derived from small molecules and small-molecule screens, and resources for studying the data so that biological and medical insights can be gained. ChemBank is intended to guide chemists synthesizing novel compounds or libraries, to assist biologists searching for small molecules that perturb specific biological pathways, and to catalyze the process by which drug hunters discover new and effective medicines. ChemBank stores an increasingly varied set of cell measurements derived from, among other biological objects, cell lines treated with small molecules. Analysis tools are available and are being developed that allow the relationships between cell states, cell measurements and small molecules to be determined. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the ICG in collaborations involving biomedical researchers worldwide. These scientists have agreed to perform their experiments in an open data-sharing environment. The goals of ChemBank are to provide life scientists unfettered access to biomedically relevant data and tools heretofore available almost exclusively in the private sector. We intend for ChemBank to be a planning and discovery tool for chemists, biologists, and drug hunters anywhere, with the only necessities being a computer, access to the Internet, and a desire to extract knowledge from public experiments whose greatest value is likely to reside in their collective sum.

Proper citation: ChemBank (RRID:SCR_007592) Copy   

•   Source: SciCrunch Registry
  

http://harvard.eagle-i.net/i/0000012e-6e00-af62-55da-381e80000000

Core facility that provides the following services: DNA analysis - Affymetrix GeneChip arrays service, DNA analysis - Illumina infinium whole genome genotyping service, DNA analysis - custom content genotyping service, RNA Analysis - Affymetrix gene expression service, RNA Analysis - Illumina Gene Expression service, RNA Analysis - Illumina whole-genome DASL service. The Genetic Analysis Platform collaborates with scientists at the Broad and across the world to identify and characterize patterns of genetic variation and gene expression. These patterns can yield a deeper understanding of how genetic factors influence disease risk and treatment outcomes in a wide range of human diseases, including type 2 diabetes, Crohn''s disease, schizophrenia, and cancer, among many others. Over the past several years, the platform has been a leading contributor to major projects such as the International Haplotype Map Project, The Cancer Genome Atlas, the 1,000 Genomes Project, the Genes and Environment Initiative, and served as a national genotyping center under a NIH/NCRR program. Genetic Analysis Platform (GAP) scientists are experts in a wide range of genomic technologies and technology platforms, including genotyping, gene expression and directed resequencing, and routinely apply these technologies to studies of both human and non-human samples. In addition, teams of platform researchers work to test out emerging genetic technologies, develop informatics tools and infrastructure to enhance scientific research, and coordinate large-scale projects involving collaborators both within and beyond the Broad.

Proper citation: Broad Genetic Analysis Platform (RRID:SCR_009690) Copy   

•   Source: SciCrunch Registry
  

http://www.broad.mit.edu/mpr/lung

Data set of a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, researchers analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct sub-classes of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.

Proper citation: Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Sub-classes (RRID:SCR_003010) Copy   

•   Source: SciCrunch Registry
  

Ratings or validation data are available for this resource

http://broadinstitute.github.io/picard/

Java toolset for working with next generation sequencing data in the BAM format.

Proper citation: Picard (RRID:SCR_006525) Copy   

•   Source: SciCrunch Registry
  

http://gnomad.broadinstitute.org/

Database that aggregates exome and genome sequencing data from large-scale sequencing projects. The gnomAD data set contains individuals sequenced using multiple exome capture methods and sequencing chemistries. Raw data from the projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects.

Proper citation: Genome Aggregation Database (RRID:SCR_014964) Copy   

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http://software.broadinstitute.org/gsea/msigdb/index.jsp

Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.

Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy   

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http://www.broadinstitute.org/blog_roll

A blog that serves as a forum for disseminating the science, culture, and life of the Broad Institute. Broad Minded provides content that comes from the collaboration of the Broad community.

Proper citation: Broad Minded (RRID:SCR_000934) Copy   

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http://www.broadinstitute.org/mpg/birdsuite/birdseed.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022.SNP genotyping algorithm that runs on the Affymetrix 500K, SNP5.0, and SNP6.0 platforms. This software runs a clustering algorithm and generally should be run on a sample at least 50 times. It utilizes an Expectation-Maximization (EM) algorithm to produce genotypes and confidence scores for every individual at every SNP.

Proper citation: Birdseed (RRID:SCR_001122) Copy   

•   Source: SciCrunch Registry
  

https://www.broadinstitute.org/birdsuite/birdsuite

Open-source set of tools to detect and report SNP genotypes, common Copy-Number Polymorphisms (CNPs), and novel, rare, or de novo CNVs in samples processed with the Affymetrix platform. While most of the components of the suite can be run individually (for instance, to only do SNP genotyping), the Birdsuite is especially intended for integrated analysis of SNPs and CNVs.

Proper citation: BIRDSUITE (RRID:SCR_001794) Copy   

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https://data.broadinstitute.org/alkesgroup/Eagle/

Software package for statistical estimation of haplotype phase either within a genotyped cohort or using a phased reference panel in large scale sequencing. The package includes Eagle1 (to harness identity-by-descent among distant relatives to rapidly call phase using a fast scoring approach) and Eagle2 (to analyze a full probabilistic model similar to the diploid Li-Stephens model used by previous HMM-based methods.

Proper citation: Eagle (RRID:SCR_015991) Copy   

•   Source: SciCrunch Registry