In LieberInstitute/jaffelab: Commonly used functions by the Jaffe lab

Quick start to using to `r Githubpkg('LieberInstitute/jaffelab')`

## Track time spent on making the vignette
startTime <- Sys.time()

## Bib setup
library("knitcitations")

## Load knitcitations with a clean bibliography
cleanbib()
cite_options(hyperlink = "to.doc", citation_format = "text", style = "html")
# Note links won't show for now due to the following issue
# https://github.com/cboettig/knitcitations/issues/63

## Write bibliography information
bib <- c(
    BiocStyle = citation("BiocStyle"),
    GenomicRanges = citation("GenomicRanges"),
    googledrive = citation("googledrive"),
    IRanges = citation("IRanges"),
    jaffelab = citation("jaffelab"),
    knitcitations = citation("knitcitations"),
    knitr = citation("knitr")[3],
    limma = citation("limma"),
    parallel = citation("parallel"),
    R = citation(),
    rafalib = citation("rafalib"),
    RColorBrewer = citation("RColorBrewer"),
    remotes = citation("remotes"),
    rmarkdown = citation("rmarkdown")[1],
    sessioninfo = citation("sessioninfo"),
    testthat = citation("testthat")
)

write.bibtex(bib, file = "quickstartRef.bib")

Basics

Install `r Githubpkg('LieberInstitute/jaffelab')`

R is an open-source statistical environment which can be easily modified to enhance its functionality via packages. r Githubpkg('LieberInstitute/jaffelab') is a R package available via GitHub. R can be installed on any operating system from CRAN after which you can install r Githubpkg('LieberInstitute/jaffelab') by using the following commands in your R session:

if (!requireNamespace("remotes", quietly = TRUE)) {
    install.packages("remotes")
}

remotes::install_github("LieberInstitute/jaffelab")

Required knowledge

If you are asking yourself the question "Where do I start using Bioconductor?" you might be interested in this blog post.

Asking for help

As package developers, we try to explain clearly how to use our packages and in which order to use the functions. But R and Bioconductor have a steep learning curve so it is critical to learn where to ask for help. The blog post quoted above mentions some but we would like to highlight the Bioconductor support site as the main resource for getting help for Bioconductor packages. For r Githubpkg('LieberInstitute/jaffelab') please post issues in GitHub. However, please note that if you want to receive help you should adhere to the posting guidelines. It is particularly critical that you provide a small reproducible example and your session information so package developers can track down the source of the error.

Citing `r Githubpkg('LieberInstitute/jaffelab')`

We hope that r Githubpkg('LieberInstitute/jaffelab') will be useful for your research. Please use the following information to cite the package and the overall approach. Thank you!

## Citation info
citation("jaffelab")

Overview

r Githubpkg('LieberInstitute/jaffelab') is based on many other packages and in particular in those that have implemented the infrastructure needed for dealing with RNA-seq data. We use it extensively at the Andrew Jaffe Data Science team from the Lieber Institute for Brain Development (LIBD), including in publications such as BrainSEQ Phase II (DOI 10.1016/j.neuron.2019.05.013). This R package started with a collection of functions Andrew Jaffe used frequently, some authored by Rafael Irizarry and Jeff Leek. It now includes other helper functions that are more specific to our work at LIBD such as agePlotter(). Please check the help files of each function to get an idea on what they do.

Reproducibility

The r Githubpkg('LieberInstitute/jaffelab') package r citep(bib[['jaffelab']]) was made possible thanks to:

R r citep(bib[['R']])
r Biocpkg('BiocStyle') r citep(bib[['BiocStyle']])
r Biocpkg('GenomicRanges') r citep(bib[['GenomicRanges']])
r CRANpkg('googledrive') r citep(bib[['googledrive']])
r Biocpkg('IRanges') r citep(bib[['IRanges']])
r CRANpkg('knitcitations') r citep(bib[['knitcitations']])
r CRANpkg('knitr') r citep(bib[['knitr']])
r Biocpkg('limma') r citep(bib[['limma']])
r CRANpkg('parallel') r citep(bib[['parallel']])
r CRANpkg('rafalib') r citep(bib[['rafalib']])
r CRANpkg('RColorBrewer') r citep(bib[['RColorBrewer']])
r CRANpkg('remotes') r citep(bib[['remotes']])
r CRANpkg('rmarkdown') r citep(bib[['rmarkdown']])
r CRANpkg('sessioninfo') r citep(bib[['sessioninfo']])
r CRANpkg('testthat') r citep(bib[['testthat']])

Code for creating the vignette

## Create the vignette
library("rmarkdown")
system.time(render("jaffelab-quickstart.Rmd", "BiocStyle::html_document"))

## Extract the R code
library("knitr")
knit("jaffelab-quickstart.Rmd", tangle = TRUE)

## Clean up
file.remove("quickstartRef.bib")

Date the vignette was generated.

## Date the vignette was generated
Sys.time()

Wallclock time spent generating the vignette.

## Processing time in seconds
totalTime <- diff(c(startTime, Sys.time()))
round(totalTime, digits = 3)

R session information.

## Session info
library("sessioninfo")
options(width = 120)
session_info()

Bibliography

This vignette was generated using r Biocpkg('BiocStyle') r citep(bib[['BiocStyle']]) with r CRANpkg('knitr') r citep(bib[['knitr']]) and r CRANpkg('rmarkdown') r citep(bib[['rmarkdown']]) running behind the scenes.

Citations made with r CRANpkg('knitcitations') r citep(bib[['knitcitations']]).