vignettes/jaffelab-quickstart.Rmd
jaffelab-quickstart.RmdR is an open-source statistical environment which can be
easily modified to enhance its functionality via packages. jaffelab is
a R package available via GitHub. R can be
installed on any operating system from CRAN after which you can install
jaffelab by
using the following commands in your R session:
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
remotes::install_github("LieberInstitute/jaffelab")If you are asking yourself the question “Where do I start using Bioconductor?” you might be interested in this blog post.
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
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.
We hope that 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")## To cite package 'jaffelab' in publications use:
##
## Collado-Torres L, Jaffe AE, Burke EE (2024). _jaffelab: Commonly used
## functions by the Jaffe lab_. R package version 0.99.34,
## <https://github.com/LieberInstitute/jaffelab>.
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
## title = {jaffelab: Commonly used functions by the Jaffe lab},
## author = {Leonardo Collado-Torres and Andrew E. Jaffe and Emily E. Burke},
## year = {2024},
## note = {R package version 0.99.34},
## url = {https://github.com/LieberInstitute/jaffelab},
## }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.
The jaffelab package (Collado-Torres, Jaffe, and Burke, 2024) was made possible thanks to:
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")## [1] TRUEDate the vignette was generated.
## [1] "2024-03-27 13:29:08 UTC"Wallclock time spent generating the vignette.
## Time difference of 0.871 secsR session information.
## ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────
## setting value
## version R version 4.3.2 (2023-10-31)
## os Ubuntu 22.04.3 LTS
## system x86_64, linux-gnu
## ui X11
## language en
## collate en_US.UTF-8
## ctype en_US.UTF-8
## tz UTC
## date 2024-03-27
## pandoc 3.1.1 @ /usr/local/bin/ (via rmarkdown)
##
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##
## ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────This vignette was generated using BiocStyle (Oleś, 2023) with knitr (Xie, 2014) and rmarkdown (Allaire, Xie, Dervieux, McPherson et al., 2024) running behind the scenes.
Citations made with knitcitations (Boettiger, 2021).
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