An open API service indexing awesome lists of open source software.

https://github.com/dzhang32/dasper

Detecting Aberrant Splicing Events from RNA-sequencing data
https://github.com/dzhang32/dasper

diagnostics rare-disease rna-seq-analysis splicing

Last synced: 4 months ago
JSON representation

Detecting Aberrant Splicing Events from RNA-sequencing data

Awesome Lists containing this project

README

          

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```

# dasper

[![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#maturing)
[![R build status](https://github.com/dzhang32/dasper/actions/workflows/check-bioc.yml/badge.svg)](https://github.com/dzhang32/dasper/actions/workflows/check-bioc.yml)
[![Codecov test coverage](https://codecov.io/gh/dzhang32/dasper/branch/master/graph/badge.svg)](https://codecov.io/gh/dzhang32/dasper?branch=master)
[![BioC status](http://www.bioconductor.org/shields/build/release/bioc/dasper.svg)](https://bioconductor.org/checkResults/release/bioc-LATEST/dasper)
[![DOI](https://zenodo.org/badge/245168125.svg)](https://zenodo.org/badge/latestdoi/245168125)

The aim of `dasper` is to **d**etect **a**berrant **sp**licing **e**vents from **R**NA-seq data. By comparing patient RNA-seq data to a set of controls, `dasper` will score each splicing event in the patient representing the degree to which that splicing event looks abnormal. For a detailed guide on the usage of `dasper`, check out the vignette [here](https://dzhang32.github.io/dasper/articles/dasper.html).

## Installation instructions

Get the latest stable `R` release from [CRAN](http://cran.r-project.org/). Then install `dasper` from [Bioconductor](http://bioconductor.org/) using the following code:

```{r 'install', eval = FALSE}
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}

BiocManager::install("dasper")
```

And the development version from [GitHub](https://github.com/) with:

```{r 'install_dev', eval = FALSE}
BiocManager::install("dzhang32/dasper")
```

## Citation

Below is the citation output from using `citation('dasper')` in R. Please
run this yourself to check for any updates on how to cite __dasper__.

```{r 'citation', eval = requireNamespace('dasper')}
print(citation("dasper"), bibtex = TRUE)
```

Please note that the `dasper` 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.

## Code of Conduct

Please note that the `dasper` project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

## Development tools

* Continuous code testing is possible thanks to [GitHub actions](https://www.tidyverse.org/blog/2020/04/usethis-1-6-0/) through `r BiocStyle::CRANpkg('usethis')`, `r BiocStyle::CRANpkg('remotes')`, `r BiocStyle::Githubpkg('r-hub/sysreqs')` and `r BiocStyle::CRANpkg('rcmdcheck')` customized to use [Bioconductor's docker containers](https://www.bioconductor.org/help/docker/) and `r BiocStyle::Biocpkg('BiocCheck')`.
* Code coverage assessment is possible thanks to [codecov](https://codecov.io/gh) and `r BiocStyle::CRANpkg('covr')`.
* The [documentation website](http://dzhang32.github.io/dasper) is automatically updated thanks to `r BiocStyle::CRANpkg('pkgdown')`.
* The code is styled automatically thanks to `r BiocStyle::CRANpkg('styler')`.
* The documentation is formatted thanks to `r BiocStyle::CRANpkg('devtools')` and `r BiocStyle::CRANpkg('roxygen2')`.

For more details, check the `dev` directory.

In particular, I am very grateful to [Leo](http://lcolladotor.github.io/) for his time and advice throughout the development of `dasper`. The transition of `dasper` Bioconductor-friendly package was made possible thanks to his `r BiocStyle::Biocpkg('biocthis')` package.