The recount2 resource is composed of over 70,000 uniformly processed
human RNA-seq samples spanning TCGA and SRA, including GTEx. The
processed data can be accessed via the recount2 website and the
recount Bioconductor package. This workflow explains in detail how to
use the recount package and how to integrate it with other
Bioconductor packages for several analyses that can be carried out with
the recount2 resource. In particular, we describe how the coverage count
matrices were computed in recount2 as well as different ways of
obtaining public metadata, which can facilitate downstream analyses.
Step-by-step directions show how to do a gene level differential
expression analysis, visualize base-level genome coverage data, and
perform an analyses at multiple feature levels. This workflow thus
provides further information to understand the data in recount2 and a
compendium of R code to use the data.
The workflow is available on Bioconductor at https://www.bioconductor.org/help/workflows/recountWorkflow/ and F1000Research at https://f1000research.com/articles/6-1558/v1.
For more information about recountWorkflow check the vignettes
through Bioconductor
or at the documentation
website.
Get the latest stable R release from
CRAN. Then install recountWorkflow from
Bioconductor using the following code:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("recountWorkflow")Below is the citation output from using citation('recountWorkflow') in
R. Please run this yourself to check for any updates on how to cite
recountWorkflow.
print(citation("recountWorkflow"), bibtex = TRUE)
#> To cite package 'recountWorkflow' in publications use:
#>
#> Collado-Torres L, Nellore A, Jaffe AE (2017). "recount workflow:
#> Accessing over 70,000 human RNA-seq samples with Bioconductor
#> [version 1; referees: 1 approved, 2 approved with reservations]."
#> _F1000Research_. doi:10.12688/f1000research.12223.1
#> <https://doi.org/10.12688/f1000research.12223.1>,
#> <https://f1000research.com/articles/6-1558/v1>.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Article{,
#> title = {recount workflow: Accessing over 70,000 human RNA-seq samples with Bioconductor [version 1; referees: 1 approved, 2 approved with reservations]},
#> author = {Leonardo Collado-Torres and Abhinav Nellore and Andrew E. Jaffe},
#> year = {2017},
#> journal = {F1000Research},
#> doi = {10.12688/f1000research.12223.1},
#> url = {https://f1000research.com/articles/6-1558/v1},
#> }
#>
#> Collado-Torres L, Nellore A, Jaffe AE (2023). _recount workflow:
#> accessing over 70,000 human RNA-seq samples with Bioconductor_.
#> doi:10.18129/B9.bioc.recountWorkflow
#> <https://doi.org/10.18129/B9.bioc.recountWorkflow>,
#> https://github.com/LieberInstitute/recountWorkflow - R package
#> version 1.25.0,
#> <http://www.bioconductor.org/packages/recountWorkflow>.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {recount workflow: accessing over 70,000 human RNA-seq samples with Bioconductor},
#> author = {Leonardo Collado-Torres and Abhinav Nellore and Andrew E. Jaffe},
#> year = {2023},
#> url = {http://www.bioconductor.org/packages/recountWorkflow},
#> note = {https://github.com/LieberInstitute/recountWorkflow - R package version 1.25.0},
#> doi = {10.18129/B9.bioc.recountWorkflow},
#> }Please note that the recountWorkflow was only made possible thanks to
many other R and bioinformatics software authors, which are cited either
in the vignettes and/or the paper(s) describing this package.
Please note that the recountWorkflow project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
- Continuous code testing is possible thanks to GitHub actions through usethis, remotes, sysreqs and rcmdcheck customized to use Bioconductor’s docker containers and BiocCheck.
- Code coverage assessment is possible thanks to codecov and covr.
- The documentation website is automatically updated thanks to pkgdown.
- The code is styled automatically thanks to styler.
- The documentation is formatted thanks to devtools and roxygen2.
For more details, check the dev directory.