Quality control and differential expression for bcbio RNA-seq experiments.
This is an R package.
source("https://bioconductor.org/biocLite.R")Ensure that these dependencies install correctly:
biocLite(c(
"steinbaugh/basejump",
"lpantano/DEGreport",
"tidyverse",
"rmarkdown",
"knitr",
"formatR",
"GenomeInfoDbData"
))Now you’re ready to install bcbioRNASeq:
biocLite("hbc/bcbioRNASeq")For the Functional Analysis R Markdown template, these additional libraries are required:
biocLite(c(
"clusterProfiler",
"DOSE",
"pathview"
))library(bcbioRNASeq)
bcb <- loadRNASeq(
uploadDir = file.path("bcbio_rnaseq_run", "final"),
interestingGroups = c("genotype", "treatment"))This will return a bcbioRNASeq object, which is an extension of the Bioconductor SummarizedExperiment container class.
Parameters:
uploadDir: Path to the bcbio final upload directory.interestingGroups: Character vector of the column names of interest in the sample metadata, which is stored in the colData() accessor slot of the bcbioRNASeq object. These values should be formatted in camelCase, and can be reassigned in the object after creation (e.g. metadata(bcb)$interestingGroups <- c("batch", "age")). They are used for data visualization in the quality control utility functions.Consult help("loadRNASeq", "bcbioRNASeq") for additional documentation.
This package provides multiple RMarkdown templates, including Quality Control and Differential Expression using DESeq2, which are available in RStudio at File -> New File -> R Markdown... -> From Template.
View example HTML reports rendered from the default RMarkdown templates included in the package: