Description Usage Arguments Details Value Note Author(s) References Examples
View source: R/Z4_normalization_for_Luc2.r
Estimate normalization factor using suctom normalization factor such as the relative RPKM of house-keeping genes or Luciferase.
1 | BridgeRNormalizationForLuc2(filename, group, hour, InforColumn = 4, NormFactor = "BridgeR_3_Normalizaion_factor_dataset", OutputFile = "BridgeR_4_Normalized_expression_data.txt")
|
filename |
File path/name |
group |
Vector(string) |
hour |
Vector(number) |
InforColumn |
Integer |
NormFactor |
File path/name |
OutputFile |
File path/name |
Estimate normalization factor using suctom normalization factor such as the relative RPKM of house-keeping genes or Luciferase.
text file
2015-11-05
Naoto Imamachi
https://github.com/Naoto-Imamachi/BRIC-seq_data_analysis/tree/master/BridgeR
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##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
#inputfile <- "BridgeR_1_Relative_expression_dataset.txt"
#nf <- "BridgeR_3_Normalizaion_factor_HouseKeepingGenes.txt"
#outputfile <- "BridgeR_4_Normalized_expression_dataset.txt"
#group <- c("Control","knockdown1","knockdown2")
#hour <- c(0,1,2,4,8,12)
#BridgeRNormalizationForLuc2(filename=inputfile, group=group, hour=hour, NormFactor=nf, OutputFile=outputfile)
## The function is currently defined as
function (filename, group, hour, InforColumn = 4, NormFactor = "BridgeR_3_Normalizaion_factor_dataset",
OutputFile = "BridgeR_4_Normalized_expression_data.txt")
{
group_number <- length(group)
time_points <- length(hour)
nf_st <- 2
nf_ed <- time_points + 1
nf_Luc2 <- NULL
normalization_factor <- fread(NormFactor, header = T)[, nf_st:nf_ed,
with = F]
for (a in 1:group_number) {
if (is.null(nf_Luc2)) {
nf_Luc2 <- as.vector(as.matrix(normalization_factor[a,
]))
}
else {
nf_Luc2 <- append(nf_Luc2, as.vector(as.matrix(normalization_factor[a,
])))
}
}
input_file <- fread(filename, header = T)
output_file <- OutputFile
cat("", file = output_file)
hour_label <- NULL
for (a in 1:group_number) {
if (!is.null(hour_label)) {
cat("\t", file = output_file, append = T)
}
hour_label <- NULL
for (x in hour) {
label <- x
if (x < 10) {
label <- paste("0", x, sep = "")
}
hour_label <- append(hour_label, paste("T", label,
"_", a, sep = ""))
}
infor_st <- 1 + (a - 1) * (time_points + InforColumn)
infor_ed <- (InforColumn) * a + (a - 1) * time_points
infor <- colnames(input_file)[infor_st:infor_ed]
cat(infor, hour_label, sep = "\t", file = output_file,
append = T)
}
cat("\n", sep = "", file = output_file, append = T)
gene_number <- length(input_file[[1]])
for (x in 1:gene_number) {
data <- as.vector(as.matrix(input_file[x, ]))
for (a in 1:group_number) {
if (a != 1) {
cat("\t", sep = "", file = output_file, append = T)
}
infor_st <- 1 + (a - 1) * (time_points + InforColumn)
infor_ed <- (InforColumn) * a + (a - 1) * time_points
exp_st <- infor_ed + 1
exp_ed <- infor_ed + time_points
gene_infor <- data[infor_st:infor_ed]
exp <- as.numeric(data[exp_st:exp_ed])
nf_Luc2_st <- (time_points) * (a - 1) + 1
nf_Luc2_ed <- (time_points) * a
nf_Luc2_exp <- nf_Luc2[nf_Luc2_st:nf_Luc2_ed]
normalized_exp <- NULL
normalized_exp <- exp/nf_Luc2_exp
cat(gene_infor, sep = "\t", file = output_file, append = T)
cat("\t", sep = "\t", file = output_file, append = T)
cat(normalized_exp, sep = "\t", file = output_file,
append = T)
}
cat("\n", sep = "\t", file = output_file, append = T)
}
}
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