mitch is an R package for multi-dimensional enrichment analysis. At it's heart, it uses a rank-MANOVA based statistical approach to detect sets of genes that exhibit enrichment in the multidimensional space as compared to the background. mitch is useful for pathway analysis of profiling studies with two to or more contrasts, or in studies with multiple omics profiling, for example proteomic, transcriptomic, epigenomic analysis of the same samples. mitch is perfectly suited for pathway level differential analysis of scRNA-seq data.
A typical mitch workflow consists of: 1) Import gene sets with gmt_import() 2) Import profiling data with mitch_import() 3) Calculate enrichments with mitch_calc() 4) And generate plots and reports with mitch_plots() and mitch_report()
More documentation on the github page https://github.com/markziemann/mitch or with ?<function>, eg: ?mitch_import
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # Example workflow
# Import some gene sets
genesetsExample<-gmt_import(system.file('extdata/sample_genesets.gmt',
package = 'mitch'))
# Load some edgeR tables (rna, k9a, k36a).
data(rna,k9a,k36a)
# Create a list of differential profiles
myList<-list('rna'=rna,'k9a'=k9a,'k36a'=k36a)
# Import as edgeR table
myImportedData<-mitch_import(myList,DEtype='edger')
# Calculate enrichment using MANOVA
resExample<-mitch_calc(myImportedData,genesetsExample,priority='effect',
resrows=5,cores=2)
# Generate some high res plots in PDF format
mitch_plots(resExample,outfile='outres.pdf')
#' Generate a report of the analysis in HTML format
mitch_report(resExample,'outres.html')
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.