recount3 is an online resource consisting of RNA-seq gene, exon, and exon-exon junction counts as well as coverage bigWig files for 8,679 and 10,088 different studies for human and mouse respectively. It is the third generation of the ReCount project and part of recount.bio.
The raw sequencing data were processed with the Monorail
system as described in the recount3
paper which created the coverage bigWig files and the
recount-unified text files. While these raw output files are
available through the Registry of
Open Data on AWS as well as IDIES SciServer, for ease
of statistical analysis, we provide through the recount3
R/Bioconductor package an interface that builds RangedSummarizedExperiment
R objects for gene, exon, and exon-exon junction counts for
each study. Furthermore, snapcount
enables query-based access of the recount3 and
recount2 data. The coverage bigWig files can be
used for annotation-agnostic expression analyses using for
example megadepth,
derfinder
and other tools.
By taking care of several pre-processing steps and
combining many datasets into one easily-accessible website,
we make finding and analyzing RNA-seq data considerably more
straightforward. For more details about
recount3, check the documentation book.
Study explorer
You can open the study explorer independently through shinyapps.io
to explore the data hosted by the recount3
project.
Team members
- Christopher
Wilks (the star behind
recount3!) - Shijie Charles Zheng
- Kevin FY Chen
- Leonardo Collado Torres
- Kasper Daniel Hansen
- Ben Langmead
Teams involved
- Ben Langmead’s lab at JHU Computer Science
- Kasper Daniel Hansen’s lab at JHBSPH Biostatistics Department
- Leonardo Collado-Torres and Andrew E. Jaffe from LIBD
- Abhinav Nellore’s lab at OHSU
- Jeff Leek’s lab at JHBSPH Biostatistics Deparment
- Data hosted by the Registry of Open Data on AWS and SciServer from IDIES at JHU through a load balancer called duffel.