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https://github.com/bvieth/powsimR
Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.
https://github.com/bvieth/powsimR
experimental-design gene-expression power power-analysis r rna-seq simulation simulation-framework single-cell
Last synced: 27 days ago
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Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.
- Host: GitHub
- URL: https://github.com/bvieth/powsimR
- Owner: bvieth
- License: artistic-2.0
- Created: 2017-04-16T16:22:12.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2023-08-01T09:59:42.000Z (over 1 year ago)
- Last Synced: 2024-02-24T14:30:53.341Z (10 months ago)
- Topics: experimental-design, gene-expression, power, power-analysis, r, rna-seq, simulation, simulation-framework, single-cell
- Language: HTML
- Homepage: https://bvieth.github.io/powsimR/
- Size: 72.5 MB
- Stars: 102
- Watchers: 9
- Forks: 24
- Open Issues: 5
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE.md
Awesome Lists containing this project
- Awesome-Bioinformatics-Benchmarks - Github - seq-pipelines) to reproduce their analyses. (Single Cell / scRNA Analysis Pipelines)
README
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
# `powsimR`
Power analysis for bulk and
single cell RNA-seq experiments 
Please also consult my Github Page of [powsimR](https://bvieth.github.io/powsimR/) made with [pkgdown](http://pkgdown.r-lib.org/index.html)!
## :arrow_double_down: Installation Guide
For the installation, the R package `devtools` is needed.
```{r, echo=T, eval=F, tidy=T}
install.packages('devtools')
library(devtools)
```
I recommend to install first the dependencies manually and then powsimR. If you plan to use MAGIC for imputation, then please follow their [instruction](https://github.com/KrishnaswamyLab/MAGIC) to install the python implementation before installing powsimR.
```{r, echo=T, eval=F, tidy=T}
ipak <- function(pkg, repository=c('CRAN', 'Bioconductor', 'github')){
new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
# new.pkg <- pkg
if (length(new.pkg)) {
if(repository=='CRAN') {
install.packages(new.pkg, dependencies = TRUE)
}
if(repository=='Bioconductor') {
if(strsplit(version[['version.string']], ' ')[[1]][3] > "4.0.0"){
if (!requireNamespace("BiocManager")){
install.packages("BiocManager")
}
BiocManager::install(new.pkg, dependencies=TRUE, ask=FALSE)
}
if(strsplit(version[['version.string']], ' ')[[1]][3] < "3.6.0"){
stop(message("powsimR depends on packages and functions that are only available in R 4.0.0 and higher."))
}
}
if(repository=='github') {
devtools::install_github(new.pkg, build_vignettes = FALSE, force = FALSE, dependencies=TRUE)
}
}
}
# CRAN PACKAGES
cranpackages <- c("broom", "cobs", "cowplot",
"data.table", "doParallel", "dplyr", "DrImpute",
"fastICA", "fitdistrplus", "foreach", "future",
"gamlss.dist", "ggplot2", "ggpubr", "ggstance", "grDevices",
"grid", "Hmisc", "kernlab", "MASS", "magrittr", "MBESS", "Matrix",
"matrixStats", "mclust", "methods", "minpack.lm", "moments", "msir",
"NBPSeq", "nonnest2", "parallel", "penalized", "plyr", "pscl",
"reshape2", "Rmagic", "rsvd", "Rtsne", "scales", "Seurat", "snow", "sctransform",
"stats", "tibble", "tidyr", "truncnorm", "VGAM", "ZIM", "zoo")
ipak(cranpackages, repository='CRAN')
# BIOCONDUCTOR
biocpackages <- c("bayNorm", "baySeq", "BiocGenerics", "BiocParallel",
"DESeq2", "EBSeq", "edgeR", "IHW", "iCOBRA",
"limma", "Linnorm", "MAST", "monocle", "NOISeq", "qvalue", "ROTS", "RUVSeq",
"S4Vectors", "scater", "scDD", "scde", "scone", "scran", "SCnorm",
"SingleCellExperiment", "SummarizedExperiment", "zinbwave")
ipak(biocpackages, repository='Bioconductor')
# GITHUB
githubpackages <- c('cz-ye/DECENT', 'nghiavtr/BPSC',
'mohuangx/SAVER', 'statOmics/zingeR',
'Vivianstats/scImpute')
ipak(githubpackages, repository = 'github')
```
To check whether all dependencies are installed, you can run the following lines:
```{r depcheck, echo = TRUE, eval = FALSE, tidy = FALSE}
powsimRdeps <- data.frame(Package = c(cranpackages,
biocpackages,
sapply(strsplit(githubpackages, "/"), "[[", 2)),
stringsAsFactors = F)
ip <- as.data.frame(installed.packages()[,c(1,3:4)], stringsAsFactors = F)
ip.check <- cbind(powsimRdeps,
Version = ip[match(powsimRdeps$Package, rownames(ip)),"Version"])
table(is.na(ip.check$Version)) # all should be FALSE
```
After installing the dependencies, powsimR can be installed by using devtools as well.
```{r, echo=T, eval=F, tidy=T}
devtools::install_github('bvieth/powsimR',
build_vignettes = TRUE,
dependencies=FALSE)
library("powsimR")
```
Alternative, you can try to install powsimR and its dependencies directly using devtools:
```{r, echo=T, eval=F, tidy=T}
devtools::install_github("bvieth/powsimR")
```
## :book: User Guide
For examples and tips on using the package, please consult the vignette after successful installation by
```{r, echo=T, eval=F, tidy=T}
browseVignettes('powsimR')
```
Some users have experienced issues installing powsimR due to vignette compilation errors or because they are missing the necessary R packages to build the vignette, i.e. knitr and rmdformats. If that is the case, you can either install these dependencies or leave out building the vignette (by setting build_vignettes to FALSE) and read it on my Github Page of [powsimR](https://bvieth.github.io/powsimR/articles/powsimR.html) or download it as a html file [here](https://github.com/bvieth/powsimR/blob/master/vignettes/powsimR.html).
### DLLs and ulimit
Note that the error "maximal number of DLLs reached..." might occur due to the loading of many shared objects by Bioconductor packages. Restarting the R session after installing dependencies / powsimR will help.
Starting with R version 3.4.0, one can set the environmental variable 'R_MAX_NUM_DLLS' to a higher number. See `?Startup()` for more information. I recommend to increase the maximum number of DLLs that can be loaded to 500. The environmental variable R\_MAX\_NUM\_DLLS can be set in R\_HOME/etc/Renviron prior to starting R. For that locate the Renviron file and add the following line: R\_MAX\_NUM\_DLLS=xy where xy is the number of DLLs.
On my Ubuntu machine, the Renviron file is in /usr/lib/R/etc/ and I can set it to 500.
In addition, the user limits for open files (unix: ulimit) might have to be set to a higher number to accomodate the increase in DLLs. Please check out the help pages for [MACs](https://gist.github.com/tombigel/d503800a282fcadbee14b537735d202c) and [Linux](https://glassonionblog.wordpress.com/2013/01/27/increase-ulimit-and-file-descriptors-limit/) for guidance.
## :scroll: Citation
Please use the following entry for citing powsimR.
```{r, echo=T, eval=F, tidy=T}
citation("powsimR")
```
powsimR is published in [Bioinformatics](https://doi.org/10.1093/bioinformatics/btx435).
A preprint paper is also on [bioRxiv](https://doi.org/10.1101/117150).
## :incoming_envelope: Notes
Please send bug reports and feature requests by opening a new issue on
[this page](https://github.com/bvieth/powsimR/issues).
I try to keep up to date with new developments / changes of methods implemented in powsimR, but if you encounter run errors while using a certain tool (e.g. for imputation), then I appreciate if you can post this as an [issue](https://github.com/bvieth/powsimR/issues).
## `R` Session Info
```{r}
library(powsimR)
sessionInfo()
```