This registry exists to help people discover and share datasets that are available via AWS resources. Learn more about sharing data on AWS.
See all usage examples for datasets listed in this registry tagged with genomic.
You are currently viewing a subset of data tagged with genomic.
If you want to add a dataset or example of how to use a dataset to this registry, please follow the instructions on the Registry of Open Data on AWS GitHub repository.
Unless specifically stated in the applicable dataset documentation, datasets available through the Registry of Open Data on AWS are not provided and maintained by AWS. Datasets are provided and maintained by a variety of third parties under a variety of licenses. Please check dataset licenses and related documentation to determine if a dataset may be used for your application.
The International Cancer Genome Consortium (ICGC) coordinates projects with the common aim of accelerating research into the causes and control of cancer. The PanCancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in whole genomes from ICGC. More than 2,400 consistently analyzed genomes corresponding to over 1,100 unique ICGC donors are now freely available on Amazon S3 to credentialed researchers subject to ICGC data sharing policies.
The Encyclopedia of DNA Elements (ENCODE) Consortium is an international collaboration of research groups funded by the National Human Genome Research Institute (NHGRI). The goal of ENCODE is to build a comprehensive parts list of functional elements in the human genome, including elements that act at the protein and RNA levels, and regulatory elements that control cells and circumstances in which a gene is active. ENCODE investigators employ a variety of assays and methods to identify functional elements. The discovery and annotation of gene elements is accomplished primarily by sequencing a ...
The Sequence Read Archive (SRA) stores raw sequencing data from the next generation of sequencing platforms including Roche 454 GS System®, Illumina Genome Analyzer®, Applied Biosystems SOLiD® System, Helicos Heliscope®, Complete Genomics®, and Pacific Biosciences SMRT®. SRA on AWS hosts a subset of SRA accession codes in two public S3 buckets.
The 1000 Genomes Project is an international collaboration which has established the most detailed catalogue of human genetic variation, including SNPs, structural variants, and their haplotype context. The final phase of the project sequenced more than 2500 individuals from 26 different populations around the world and produced an integrated set of phased haplotypes with more than 80 million variants for these individuals.
Common reference genomes hosted on AWS S3. Can be used when aligning and analysing raw DNA sequencing data.
Broad maintained human genome reference builds hg19/hg38 and decoy references.
The GATK test data resource bundle is a collection of files for resequencing human genomic data with the Broad Institute's Genome Analysis Toolkit (GATK).
QIIME 2 is a powerful, extensible, and decentralized microbiome analysis package with a focus on data and analysis transparency. QIIME 2 enables researchers to start an analysis with raw DNA sequence data and finish with publication-quality figures and statistical results. This dataset contains the user docs (and related datasets) for QIIME 2.
The Cancer Genome Atlas (TCGA) is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI) to accelerate our understanding of the molecular basis of cancer. TCGA-funded researchers across the United States have produced a corpus of raw and processed genomic, transcriptomic, and epigenomic data from thousands of cancer patients.
Tabula Muris is a compendium of single cell transcriptomic data from the model organism Mus musculus comprising more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations, and allow for direct and controlled comparison of gene expression in cell types shared between tissues, such as T-lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3’-end counting, enabled the s...
The 3000 Rice Genome Project is an international effort to sequence the genomes of 3,024 rice varieties from 89 countries.
The Genome Ark hosts genomic information for the Vertebrate Genomes Project (VGP) and other related projects. The VGP is an international collaboration that aims to generate complete and near error-free reference genomes for all extant vertebrate species. These genomes will be used to address fundamental questions in biology and disease, to identify species most genetically at risk for extinction, and to preserve genetic information of life.
Several reference genomes to enable translation of whole human genome sequencing to clinical practice.
This dataset includes sequencing data, assemblies, and analyses for the offspring of ten parent-offspring trios.
This dataset includes the sequencing and assembly of a reference standard human genome (GM12878) using the MinION nanopore sequencing instrument with the R9.4 1D chemistry.
Tabula Muris Senis is a comprehensive compendium of single cell transcriptomic data from the model organism Mus musculus comprising more than 500,000 cells from 18 organs and tissues across the mouse lifespan. We discovered cell-specific changes occurring across multiple cell types and organs, as well as age related changes in the cellular composition of different organs. Using single-cell transcriptomic data we were able to assess cell type specific manifestations of different hallmarks of aging, such as senescence, changes in the activity of metabolic pathways, depletion of stem-cell populat...
The Genome Institute at Washington University has developed a high-throughput, fault-tolerant analysis information management system called the Genome Modeling System (GMS), capable of executing complex, interdependent, and automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. GMS includes a full system image with software and services, expandable from one workstation to a large compute cluster.