| title | description | published | date | tags | editor |
|---|---|---|---|---|---|
ARCHS4 |
Massive Mining of Publicly Available RNA-seq Data from Human and Mouse |
true |
2020-08-27 17:21:03 UTC |
aggregator, annotation, genes, proteins, functional association, specialized search, text-mining, database, data visualization, gene expression, model organism, organism-specific |
markdown |
ARCHS4 provides access to gene counts from HiSeq 2000, HiSeq 2500 and NextSeq 500 platforms for human and mouse experiments from GEO and SRA. The website enables downloading of the data in H5 format for programmatic access as well as a 3-dimensional view of the sample and gene spaces. Search features allow browsing of the data by meta data annotation, ability to submit your own up and down gene sets, and explore matching samples enriched for annotated gene sets. Selected sample sets can be downloaded into a tab separated text file through auto-generated R scripts for further analysis. Reads are aligned with Kallisto using a custom cloud computing platform. Human samples are aligned against the GRCh38 human reference genome, and mouse samples against the GRCm38 mouse reference genome. {.is-info}
- ARCHS4 Home Page {.links-list}
- Best if used comparably when working on proteins/genes conserved in bacteria and eukaryotes (specifically, mice and/or humans)
- Tools allow for exceptional mining of publicly available information that may promote corroboration of functional associations or lack, thereof
- Straight-forward, easy to use
- Users may benefit from prior knowledge or familiarity with gene/protein identifiers/accessions, annotation and naming conventions
- Help includes guides, tutorials & examples {.links-list}
- A. Lachmann et al., Massive mining of publicly available RNA-seq data from human and mouse Nature Communications volume 9, Article number: 1366 (2018) {.grid-list}