install.packages("countToFPKM")
library(countToFPKM)
file.readcounts <- system.file("extdata", "RNA-seq.read.counts.csv", package="countToFPKM")
file.annotations <- system.file("extdata", "Biomart.annotations.hg38.txt", package="countToFPKM")
file.sample.metrics <- system.file("extdata", "RNA-seq.samples.metrics.txt", package="countToFPKM")
# Import the read count matrix data into R.
counts <- as.matrix(read.csv(file.readcounts))
# Import feature annotations.
# Assign feature lenght into a numeric vector.
gene.annotations <- read.table(file.annotations, sep="\t", header=TRUE)
featureLength <- gene.annotations$length
# Import sample metrics.
# Assign mean fragment length into a numeric vector.
samples.metrics <- read.table(file.sample.metrics, sep="\t", header=TRUE)
meanFragmentLength <- samples.metrics$meanFragmentLength
# Return FPKM into a numeric matrix.
fpkm_matrix <- fpkm (counts, featureLength, meanFragmentLength)
# Plot log10(FPKM+1) heatmap of top 30 highly variable features
fpkmheatmap(fpkm_matrix, topvar=30, showfeaturenames=TRUE, return_log = TRUE)
屏幕截图 2020-01-30 03.50.23.png
heatmap.png
