The dataset for this recipe will be a test or control RNAseq experiment from Arabidopsis with three replicates each. These are available as a prepared count matrix in datasets/ch1/arabidopsis.RDS in this book's data repository. In this section, we'll use a set of counts in a simple test or control experiment from Arabidopsis thaliana. The matrix has six columns (three mock treatments and three hrcc treatments) and 26,222 rows, each a gene feature. We'll need the dplyr, extRemes, and powsimR packages for this code.
Our package of interest, powsimR, isn't on CRAN; it's hosted as a source on GitHub at https://github.com/bvieth/powsimR. You'll need to use devtools to install it, which can be done using the following code:
install.packages("devtools")
devtools::install_github("bvieth/powsimR")
If you do this, there is a chance that this package will still fail to install. It has a lot of dependencies and you might need to install those manually; there is further information on the package GitHub repository and you should check that for the latest information. At the time of writing, you'll need to do the following two big steps. First, create the ipak function outlined here, then run the three different package installation steps with the ipak function:
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] > "3.5.0") { if (!requireNamespace("BiocManager")) { install.packages("BiocManager") } BiocManager::install(new.pkg, dependencies = TRUE, ask = FALSE) } if (strsplit(version[["version.string"]], " ")[[1]][3] < "3.5.0") { source("https://bioconductor.org/biocLite.R") biocLite(new.pkg, dependencies = TRUE, ask = FALSE) } } if (repository == "github") { devtools::install_github(new.pkg, build_vignettes = FALSE, force = FALSE, dependencies = TRUE) } } }
# CRAN PACKAGES cranpackages <- c("broom", "cobs", "cowplot", "data.table", "devtools", "doParallel", "dplyr", "drc", "DrImpute", "fastICA", "fitdistrplus", "foreach", "gamlss.dist", "ggExtra", "ggplot2", "ggthemes", "grDevices", "glmnet", "grid", "gtools", "Hmisc", "kernlab", "MASS", "MBESS", "matrixStats", "mclust", "methods", "minpack.lm", "moments", "msir", "NBPSeq", "nonnest2", "parallel", "penalized", "plyr", "pscl", "reshape2", "Rmagic", "rsvd", "Rtsne", "scales", "Seurat", "snow", "stats", "tibble", "tidyr", "VGAM", "ZIM")
ipak(cranpackages, repository = "CRAN") # BIOCONDUCTOR biocpackages <- c("AnnotationDbi", "bayNorm", "baySeq", "Biobase", "BiocGenerics", "BiocParallel", "DEDS", "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("nghiavtr/BPSC", "cz-ye/DECENT", "mohuangx/SAVER", "statOmics/zingeR") ipak(githubpackages, repository = "github")
When this is done, you should be able to install the package we're after with this code:
devtools::install_github("bvieth/powsimR", build_vignettes = TRUE, dependencies = FALSE) library("powsimR")