RAPToR
R packageRAPToR
(Real Age Prediction from Transcriptome staging on Reference) is a tool to accurately predict the developmental age of individual samples from their gene expression profiles.
We stage samples on high-resolution references built from existing developmental profiling time-series. Inferred age can then be used in multiple ways to precisely estimate perturbations effects on developmental timing, increase power in differential expression analyses, estimate differential expression due to uncontrolled development and most importantly, to recover perturbation specific effects on gene expression even in the extreme scenario when the perturbation is completely confounded by development.
Please cite our paper if you use RAPToR in your research:
To install the latest version of RAPToR, run the following in your R console :
if (!requireNamespace("remotes", quietly = TRUE))
install.packages("remotes")
remotes::install_github("LBMC/RAPToR", build_vignettes = T)
When dependencies are met, installation should take under 20 seconds.
Users can choose to install the RAPToR package dependencies manually from an R console:
# CRAN packages
install.packages(c("ica", "mgcv", "parallel", "data.table", "pryr", "beeswarm", "Rdpack", "R.rsp"))
# Bioconductor packages
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("limma")
We also recommend to install the following packages used in RAPToR vignettes to download demo data:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(c("GEOquery", "biomaRt"))
We have verified RAPToR works with R v3.6.3, v4.1.1, and v4.1.2 on Unix (Ubuntu 18.04/20.04/22.04 LTS), Windows 10, and macOS (10.14) systems.
Standard datasets can easily run with 4Gb of RAM and 2 CPU cores.
For reference, the GSE80157 (dsaeschimann2017
) dataset used for demo in the main vignette (43 samples by ~19500 genes)
can be both downloaded and staged with RAPToR in under 30 seconds, using less than 2Gb of RAM.
You can access the package's main vignette from your R console with
library(RAPToR)
vignette("RAPToR")
# or
vignette("RAPToR-pdf")
RAPToR is a 2-step process:
The RAPToR
package allows you to estimate the developmental age of individual samples from their gene expression profiles.
This means that any method outputting information on gene expression on a large scale is appropriate : RNA-seq (preferably TPM), MicroArray...
Data must not be gene-centered, as this destroys the relationship between gene levels within a sample.
We recommend you get our data-packages with pre-built references of common organisms for quick & easy usage.
wormRef
Nematode references (C. elegans embryo, larval and young-adult development)drosoRef
Drosophila references (D. melanogaster embryo development)zebraRef
Zebrafish references (D. rerio embryo and larval development)mouseRef
Mouse references (M. musculus embryo development)
Please also update reference data-packages to their latest version to work with this version of RAPToR
ref
) object and corresponding make_ref()
and print functions. ref
objects togeim
object,ae(samp, ref)
),ae
object printing to include reference metadata when available.ae
plotting function toae
plotting graphics bug (larger first plot with overlayed and missing elements) when displaying multiple plots side by side.geim
printing to include reference metadata when available.ref_compare()
gets matching reference time points to the samples and compares logFCs between given sample groups, and between matching reference time points (giving an estimate of development logFCs between groups).get_logFC()
extracts sample and reference logFCs between specified groups from the output of ref_compare()
.plot_cor.ae()
to plot_cor()
.df_CV
vignette("RAPToR-DEcorrection")
-pdf
, e.g. vignette("RAPToR-pdf")
)DESCRIPTION
to automatically install bioconductor dependencies (thanks @helenmiller16).Prior updates can be found in the NEWS file.
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