RNASeqSuite is a set of handy cli wrapper functions in R around common RNASeq processing libraries to ease the workflow, simplify user input, and allow for quick, on-the-fly switching of algorithms and statistical tests. The main focus is on differential gene expression. RNASeqSuite depends on edgeR, DESeq2, and HTSFilter for statistical backends. Additionally, RNASeqSuite uses geneConvert, an integrated XML parsing and SQL database builder, for internal conversion of gene annotations for further analysis.


Using the R package, devtools run devtools::install_github("Dudemanguy/RNASeqSuite").

Quick Usage

To use RNASeqSuite, one only needs a data frame of read counts and data frame of sample/group information. featureCounts in the subread package is recommended for generating a read count matrix. Creating a simple, tab-delimited list with one column containing the columns in the read count matrix and the other column containing the corresponding group is also recommended. The rownames for the group data frame need to be the names of the samples for grpSelection to work properly. To quickly perform a Fisher's Exact Test, one only needs to do the following.

data <- read.delim('/path/to/count/matrix')
frame <- read.delim('/path/to/colnames/and/group')
group <- grpSelection(frame, c('name of group A', 'name of group B'))
y <- exactWrapper(data, group)

y is the object containing the adjusted p-values for the genes. By default, exactWrapper will filter data for you based on HTSFilter which uses a Jaccard index to remove low, constant expression genes. There are more options available in the manpages. A qlfWrapper function is also available for edgeR's glmQLFTest. Additional gene annotation can be added to the results object by the use of the idAdd function.

y <- idAdd(y, species, input, output)

idAdd uses geneConvert for gene conversions. Out of the box, it has support for human, mouse, and rat genes. However, other organisms can be added. See the geneConvert page for more details. To write results to a file, use the write.output wrapper.

write.output(y, Directory, fdr)

This outputs the console output of the object, the full results table from the exact test, and the significant results table from the exact test to separate files within the specified directory. The fdr is merely a cutoff for the significant results file. It defaults to 0.05, but can be specified to something else.



Dudemanguy/RNASeqSuite documentation built on Dec. 5, 2019, 12:45 a.m.