GenVisR 基因组数据可视化实战(三)

3. genCov画每个突变位点附件的coverage，跟igv有点相似。

这个操作起来很复杂，但是图还是挺有用的。可以考虑。

由于我的reference genome build是hg38

BiocManager::install(c("TxDb.Hsapiens.UCSC.hg38.knownGene","BSgenome.Hsapiens.UCSC.hg38"))

library(TxDb.Hsapiens.UCSC.hg38.knownGene)

library(BSgenome.Hsapiens.UCSC.hg38)

txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene

genome <- BSgenome.Hsapiens.UCSC.hg38

准备这样的数据：

如果有GATK depthOfCoverage的结果（如下图）可以根据interval 转化成上述的的结果。

代码：

gr <- GRanges(seqnames = c("chr10"), ranges=IRanges(start = c(89622195), end = c(89729532)),strand = strand(c("+")))

# Create Data for input

start <- c(89622194:89729524)

end <- c(89622195:89729525)

chr <- 10

cov <- c(rnorm(1e+05, mean = 40), rnorm(7331, mean = 10))

cov_input_A <- as.data.frame(cbind(chr, start, end, cov))

start <- c(89622194:89729524)

end <- c(89622195:89729525)

chr <- 10

cov <- c(rnorm(50000, mean = 40), rnorm(7331, mean = 10), rnorm(50000, mean = 40))

cov_input_B <- as.data.frame(cbind(chr, start, end, cov))

data <- list(`Sample A` = cov_input_A, `Sample B` = cov_input_B)

data

# Call genCov

genCov(data, txdb, gr, genome, gene_labelTranscriptSize = 2, transform = NULL, base = NULL)

genCov(data, txdb, gr, genome, transform = c("Intron", "CDS", "UTR"), base = c(10, 2, 2), reduce = TRUE)

图：