knitr::opts_chunk$set( collapse = TRUE, comment = "#>", crop = NULL ## Related to https://stat.ethz.ch/pipermail/bioc-devel/2020-April/016656.html )
## Track time spent on making the vignette startTime <- Sys.time() ## Bib setup library("RefManageR") ## Write bibliography information bib <- c( R = citation(), BiocStyle = citation("BiocStyle")[1], knitr = citation("knitr")[1], RefManageR = citation("RefManageR")[1], rmarkdown = citation("rmarkdown")[1], sessioninfo = citation("sessioninfo")[1], testthat = citation("testthat")[1], KinaseTauScore = citation("KinaseTauScore")[1] )
KinaseTauScore
R
is an open-source statistical environment which can be easily modified to enhance its functionality via packages. r Biocpkg("KinaseTauScore")
is a R
package available via the Bioconductor repository for packages. R
can be installed on any operating system from CRAN after which you can install r Biocpkg("KinaseTauScore")
by using the following commands in your R
session:
if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("KinaseTauScore") ## Check that you have a valid Bioconductor installation BiocManager::valid()
r Biocpkg("KinaseTauScore")
is based on many other packages and in particular in those that have implemented the infrastructure needed for dealing with RNA-seq data (EDIT!). That is, packages like r Biocpkg("SummarizedExperiment")
(EDIT!).
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: remember to use the KinaseTauScore
tag and check the older posts. Other alternatives are available such as creating GitHub issues and tweeting. 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.
KinaseTauScore
We hope that r Biocpkg("KinaseTauScore")
will be useful for your research. Please use the following information to cite the package and the overall approach. Thank you!
## Citation info citation("KinaseTauScore")
KinaseTauScore
library("KinaseTauScore")
Edit this as you see fit =)
Here is an example of you can cite your package inside the vignette:
r Biocpkg("KinaseTauScore")
r Citep(bib[["KinaseTauScore"]])
The r Biocpkg("KinaseTauScore")
package r Citep(bib[["KinaseTauScore"]])
was made possible thanks to:
r Citep(bib[["R"]])
r Biocpkg("BiocStyle")
r Citep(bib[["BiocStyle"]])
r CRANpkg("knitr")
r Citep(bib[["knitr"]])
r CRANpkg("RefManageR")
r Citep(bib[["RefManageR"]])
r CRANpkg("rmarkdown")
r Citep(bib[["rmarkdown"]])
r CRANpkg("sessioninfo")
r Citep(bib[["sessioninfo"]])
r CRANpkg("testthat")
r Citep(bib[["testthat"]])
This package was developed using r BiocStyle::Biocpkg("biocthis")
.
Code for creating the vignette
## Create the vignette library("rmarkdown") system.time(render("KinaseTauScore.Rmd", "BiocStyle::html_document")) ## Extract the R code library("knitr") knit("KinaseTauScore.Rmd", tangle = TRUE)
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()
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("RefManageR")
r Citep(bib[["RefManageR"]])
.
## Print bibliography PrintBibliography(bib, .opts = list(hyperlink = "to.doc", style = "html"))
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