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https://github.com/lieberinstitute/speaqeasyworkshop2020

EuroBioc2020 SPEAQeasy workshop https://eurobioc2020.bioconductor.org by Nick Eagles and Josh Stolz. For more information about SPEAQeasy check http://research.libd.org/SPEAQeasy/. For an example on how to use this RNA-seq processing pipeline and analyze the output files check http://research.libd.org/SPEAQeasy-example/.
https://github.com/lieberinstitute/speaqeasyworkshop2020

bioconductor limma nextflow nextflow-pipelines rnaseq-pipeline rstats speaqeasy

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EuroBioc2020 SPEAQeasy workshop https://eurobioc2020.bioconductor.org by Nick Eagles and Josh Stolz. For more information about SPEAQeasy check http://research.libd.org/SPEAQeasy/. For an example on how to use this RNA-seq processing pipeline and analyze the output files check http://research.libd.org/SPEAQeasy-example/.

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README

          

---
output: github_document
---

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

# SPEAQeasyWorkshop2020

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
[![R build status](https://github.com/LieberInstitute/SPEAQeasyWorkshop2020/actions/workflows/check-bioc.yml/badge.svg)](https://github.com/LieberInstitute/SPEAQeasyWorkshop2020/actions/workflows/check-bioc.yml)

This workshop aims to describe the `SPEAQeasy` RNA-seq processing pipeline, show how to use it, and then illustrate how the results can be analyzed using Bioconductor R packages for differential expression analyses.

SPEAQeasy is a [Nextflow](https://www.nextflow.io/)-based **S**calable RNA-seq processing **P**ipeline for **E**xpression **A**nalysis and **Q**uantification that produces R objects ready for analysis with Bioconductor tools. Partipants will become familiar with SPEAQeasy set-up, execution on real data, and practice configuring some common settings. We will walk through a complete differential expression analysis, utilizing popular packages such as [limma](https://www.bioconductor.org/packages/limma), [edgeR](http://bioconductor.org/packages/edgeR), and [clusterProfiler](https://bioconductor.org/packages/clusterProfiler).

## Citation

Below is the citation output from using `citation('SPEAQeasyWorkshop2020')` in R. Please
run this yourself to check for any updates on how to cite __SPEAQeasyWorkshop2020__.

```{r 'citation', eval = requireNamespace('SPEAQeasyWorkshop2020')}
print(citation("SPEAQeasyWorkshop2020"), bibtex = TRUE)
```

Please note that the `SPEAQeasyWorkshop2020` 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 `SPEAQeasyWorkshop2020` 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')`, 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://LieberInstitute.github.io/SPEAQeasyWorkshop2020) 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.

This package was developed using `r BiocStyle::Biocpkg('biocthis')`.