The goal of ADARcas is to provide some functions that allow the user
to measure ADARs activity by using previously developed signatures, or
by computing his own signature starting if a dataset with its
reconstructed regulatory network is available. ADARs’ activity will be
represented by a Contextual Activity Score (CAS), that is specific for
human neuronal, mouse neuronal or cancert contexts and can be computed
starting from bulk, single-cell RNA-Seq or spatial transcriptomic data.
The ADARcas package can be installed:
if (!require("remotes", quietly = TRUE))
install.packages("remotes")
remotes::install_github("CaluraLab/ADARcas")
#> ── R CMD build ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> checking for file ‘/tmp/RtmpoDB5vR/remotesca6de748769db/CaluraLab-ADARcas-ea1fd54/DESCRIPTION’ ... ✔ checking for file ‘/tmp/RtmpoDB5vR/remotesca6de748769db/CaluraLab-ADARcas-ea1fd54/DESCRIPTION’
#> ─ preparing ‘ADARcas’:
#> checking DESCRIPTION meta-information ... ✔ checking DESCRIPTION meta-information
#> ─ checking for LF line-endings in source and make files and shell scripts
#> ─ checking for empty or unneeded directories
#> Removed empty directory ‘ADARcas/ADARcas’
#> ─ looking to see if a ‘data/datalist’ file should be added
#> ─ building ‘ADARcas_0.99.0.tar.gz’
#>
#> - Continuous code testing is possible thanks to GitHub actions through usethis, remotes, and rcmdcheck customized to use Bioconductor’s docker containers and BiocCheck.
- Code coverage assessment is possible thanks to codecov and covr.
- The code is styled automatically thanks to styler.
- The documentation is formatted thanks to devtools and roxygen2.
For more details, check the dev directory.
This package was developed using biocthis.