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DPClust pre-processing
This R package contains various functions to produce input data for DPClust using SNV variant calls and copy number data from Battenberg. Most importantly, it contains the runGetDirichletProcessInfo function that produces the input data for SNV based clustering.
Installation instructions
dpclust3p is an R package and can be installed with the commands right below. It also requires the alleleCounter tool to be in $PATH.
source("http://bioconductor.org/biocLite.R"); biocLite(c("optparse","VariantAnnotation","GenomicRanges","Rsamtools","ggplot2","IRanges","S4Vectors","reshape2"))'
devtools::install_github("Wedge-Oxford/dpclust3p")
Running pre-processing
The typical usage is to create the DPClust input data. See inst/example for a few example pipelines. A pipeline typically consists of three steps:
- Transform loci from a VCF file into a loci file
- Obtain allele counts for all mutations, either by invoking alleleCount or by dumping counts from the VCF file
- Convert allele counts and copy number information into DPClust input
The R package contains many functions from which one can build their own pipeline
| File | Description |
|---|---|
| preprocessing.R | Main preprocessing functions to create DPClust input, perform mutation phasing, filter by mutational signature |
| allelecount.R | Functions to count alleles in a BAM file, or dump counts from a range of VCF formats |
| kataegis.R | Functions to identify kataegis events (requires fastPCF.R) |
| copynumber.R | Various functions related to copy number |
| qualitycontrol.R | Create plots that can be used for QCing |
| interconvertMutationBurdens.R | Basic functions for data transformations |
| util.R | Various utility functions |
Docker
This package has been Dockerised, build as follows:
docker build -t dpclust3p:1.0.8 .