mut_strand | R Documentation |
Find strand of mutations
mut_strand(vcf, ranges, mode = "transcription")
vcf |
GRanges containing the VCF object |
ranges |
GRanges object with the genomic ranges of: 1. (transcription mode) the gene bodies with strand (+/-) information, or 2. (replication mode) the replication strand with 'strand_info' metadata |
mode |
"transcription" or "replication", default = "transcription" |
For transcription mode: Definitions of gene bodies with strand (+/-) information should be defined in a GRanges object.
For the base substitutions that are within gene bodies, it is determined whether the "C" or "T" base is on the same strand as the gene definition. (Since by convention we regard base substitutions as C>X or T>X.)
Base substitutions on the same strand as the gene definitions are considered "untranscribed", and on the opposite strand of gene bodies as "transcribed", since the gene definitions report the coding or sense strand, which is untranscribed.
No strand information "-" is returned for base substitutions outside gene bodies, or base substitutions that overlap with more than one gene body on the same strand.
For replication mode: Replication directions of genomic ranges should be defined in GRanges object. The GRanges object should have a "strand_info" metadata column, which contains only two different annotations, e.g. "left" and "right", or "leading" and "lagging". The genomic ranges cannot overlap, to allow only one annotation per location.
For each base substitution it is determined on which strand it is located. No strand information "-" is returned for base substitutions in unannotated genomic regions.
With the package we provide an example dataset, see example code.
Character vector with transcriptional strand information with length of vcf: "-" for positions outside gene bodies, "U" for untranscribed/sense/coding strand, "T" for transcribed/anti-sense/non-coding strand.
read_vcfs_as_granges
,
## For this example we need our variants from the VCF samples, and ## a known genes dataset. See the 'read_vcfs_as_granges()' example ## for how to load the VCF samples. vcfs <- readRDS(system.file("states/read_vcfs_as_granges_output.rds", package = "MutationalPatterns" )) ## For transcription strand: ## You can obtain the known genes from the UCSC hg19 dataset using ## Bioconductor: # source("https://bioconductor.org/biocLite.R") # biocLite("TxDb.Hsapiens.UCSC.hg19.knownGene") library("TxDb.Hsapiens.UCSC.hg19.knownGene") genes_hg19 <- genes(TxDb.Hsapiens.UCSC.hg19.knownGene) mut_strand(vcfs[[1]], genes_hg19, mode = "transcription") ## For replication strand: ## Read example bed file with replication direction annotation ## Read replistrand data repli_file <- system.file("extdata/ReplicationDirectionRegions.bed", package = "MutationalPatterns" ) repli_strand <- read.table(repli_file, header = TRUE) repli_strand_granges <- GRanges( seqnames = repli_strand$Chr, ranges = IRanges( start = repli_strand$Start + 1, end = repli_strand$Stop ), strand_info = repli_strand$Class ) ## UCSC seqlevelsstyle seqlevelsStyle(repli_strand_granges) <- "UCSC" mut_strand(vcfs[[1]], repli_strand_granges, mode = "transcription")
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