differential_cnv: Do difference analysis of gene level copy number variation...

In huerqiang/GeoTcgaData: Processing Various Types of Data on GEO and TCGA

Do difference analysis of gene level copy number variation data

Description

Do difference analysis of gene level copy number variation data

Usage

differential_CNV(
  cnvData,
  sampleGroup,
  method = "Chisquare",
  adjust.method = "BH",
  ...
)

Arguments

cnvData	data.frame of CNV data, each column is a sample, and each row is a CNV.
sampleGroup	vector of sample group
method	method to do diffenenital analysis, one of "Chisquare", "fisher", and "CATT"(Cochran-Armitage trend test)
adjust.method	adjust.method, one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", and "none".
...	parameters for "Chisquare", "fisher", and "CATT"(Cochran-Armitage trend test)

Value

data.frame with pvalue and estimate

Examples

# use TCGAbiolinks data as example
library(TCGAbiolinks)
query <- GDCquery(
        project = "TCGA-ACC",
        data.category = "Copy Number Variation",
        data.type = "Gene Level Copy Number",
        access = "open"
)
GDCdownload(query)
cnvData <- GDCprepare(query)
aa <- assays(cnvData)$copy_number
bb <- aa
aa[bb == 2] <- 0
aa[bb < 2] <- -1
aa[bb > 2] <- 1
sampleGroup <- sample(c("A", "B"), ncol(cnvData), replace = TRUE)
diffCnv <- differential_CNV(aa, sampleGroup)

# Use sangerbox CNV data as example
cnvData <- fread("Merge_GeneLevelCopyNumber.txt")
class(cnvData) <- "data.frame"
rownames(cnvData) <- cnvData[, 1]
cnvData <- cnvData[, -c(1, 2, 3)]
sampleGroup <- sample(c("A", "B"), ncol(cnvData), replace = TRUE)
diffCnv <- differential_CNV(cnvData, sampleGroup)

# use random data as example
aa <- matrix(sample(c(0, 1, -1), 200, replace = TRUE), 25, 8)
rownames(aa) <- paste0("gene", 1:25)
colnames(aa) <- paste0("sample", 1:8)
sampleGroup <- sample(c("A", "B"), ncol(aa), replace = TRUE)
diffCnv <- differential_CNV(aa, sampleGroup)

huerqiang/GeoTcgaData documentation built on March 21, 2024, 1:42 a.m.