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Chunk06-Construct the biggest gene expression matrix for all datasets.R
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Chunk06-Construct the biggest gene expression matrix for all datasets.R
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################################################################################
# &&&....&&& % Project: Identification of HKG candidates in C. elegans #
# &&&&&&..&&&&&& % Author: Bo Li, Jingxin Tao, Youjin Hao #
# &&&&&&&&&&&&&& % Date: Dec. 24th, 2019 #
# &&&&&&&&&&&& % #
# &&&&&&&& % Environment: R version 3.5.3; #
# &&&& % Platform: x86_64-pc-linux-gnu (64-bit) #
# & % #
################################################################################
### ****************************************************************************
### code chunk number 06: Construct the gene expression matrix.
### ****************************************************************************
###- RMA Expression Matrix --------------------------------------------------###
len.DS <- length(data_rma)
RMA_exprs <- list()
for (i in 1:len.DS) {
### S1. One2one gene expression matrix.
one2one.matrix <- data_rma[[i]][one2one.probe$PROBEID, ]
rownames(one2one.matrix) == one2one.probe$PROBEID
### S2. More2one gene expression matrix.
more2one.matrix <- NULL
for (s in 1:length(more2one)) {
pos <- which(one2any.probe$SYMBOL == more2one[s])
probe.pos <- one2any.probe$PROBEID[pos]
tmp <- data_rma[[i]][probe.pos, ]
exp <- apply(tmp, 2, median)
more2one.matrix <- rbind(more2one.matrix, exp)
}
rownames(more2one.matrix) <- more2one
dim(more2one.matrix)
### S3. Whole gene expression matrix.
whole.matrix <- rbind(one2one.matrix, more2one.matrix)
### S4. Gene expression matrix.
RMA_exprs[[i]] <- whole.matrix
}
###- MAS Expression Matrix --------------------------------------------------###
len.DS <- length(data_mas)
MAS_exprs <- list()
for (i in 1:len.DS) {
### S1. One2one gene expression matrix.
one2one.matrix <- data_mas[[i]][one2one.probe$PROBEID, ]
rownames(one2one.matrix) == one2one.probe$PROBEID
### S2. More2one gene expression matrix.
more2one.matrix <- NULL
for (s in 1:length(more2one)) {
pos <- which(one2any.probe$SYMBOL == more2one[s])
probe.pos <- one2any.probe$PROBEID[pos]
tmp <- data_mas[[i]][probe.pos, ]
exp <- apply(tmp, 2, median)
more2one.matrix <- rbind(more2one.matrix, exp)
}
rownames(more2one.matrix) <- more2one
dim(more2one.matrix)
### S3. Whole gene expression matrix.
whole.matrix <- rbind(one2one.matrix, more2one.matrix)
### S4. Gene expression matrix.
MAS_exprs[[i]] <- whole.matrix
}
###- GCRMA Expression Matrix ------------------------------------------------###
len.DS <- length(data_gcrma)
GCRMA_exprs <- list()
for (i in 1:len.DS) {
### S1. One2one gene expression matrix.
one2one.matrix <- data_gcrma[[i]][one2one.probe$PROBEID, ]
rownames(one2one.matrix) == one2one.probe$PROBEID
### S2. More2one gene expression matrix.
more2one.matrix <- NULL
for (s in 1:length(more2one)) {
pos <- which(one2any.probe$SYMBOL == more2one[s])
probe.pos <- one2any.probe$PROBEID[pos]
tmp <- data_gcrma[[i]][probe.pos, ]
exp <- apply(tmp, 2, median)
more2one.matrix <- rbind(more2one.matrix, exp)
}
rownames(more2one.matrix) <- more2one
dim(more2one.matrix)
### S3. Whole gene expression matrix.
whole.matrix <- rbind(one2one.matrix, more2one.matrix)
### S4. Gene expression matrix.
GCRMA_exprs[[i]] <- whole.matrix
}
###- DCHIP Expression Matrix ------------------------------------------------###
len.DS <- length(data_dchip)
DCHIP_exprs <- list()
for (i in 1:len.DS) {
### S1. One2one gene expression matrix.
one2one.matrix <- data_dchip[[i]][one2one.probe$PROBEID, ]
rownames(one2one.matrix) == one2one.probe$PROBEID
### S2. More2one gene expression matrix.
more2one.matrix <- NULL
for (s in 1:length(more2one)) {
pos <- which(one2any.probe$SYMBOL == more2one[s])
probe.pos <- one2any.probe$PROBEID[pos]
tmp <- data_dchip[[i]][probe.pos, ]
exp <- apply(tmp, 2, median)
more2one.matrix <- rbind(more2one.matrix, exp)
}
rownames(more2one.matrix) <- more2one
dim(more2one.matrix)
### S3. Whole gene expression matrix.
whole.matrix <- rbind(one2one.matrix, more2one.matrix)
### S4. Gene expression matrix.
DCHIP_exprs[[i]] <- whole.matrix
}
###- PLIER Expression Matrix ------------------------------------------------###
len.DS <- length(data_plier)
PLIER_exprs <- list()
for (i in 1:len.DS) {
### S1. One2one gene expression matrix.
one2one.matrix <- data_plier[[i]][one2one.probe$PROBEID, ]
rownames(one2one.matrix) == one2one.probe$PROBEID
### S2. More2one gene expression matrix.
more2one.matrix <- NULL
for (s in 1:length(more2one)) {
pos <- which(one2any.probe$SYMBOL == more2one[s])
probe.pos <- one2any.probe$PROBEID[pos]
tmp <- data_plier[[i]][probe.pos, ]
exp <- apply(tmp, 2, median)
more2one.matrix <- rbind(more2one.matrix, exp)
}
rownames(more2one.matrix) <- more2one
dim(more2one.matrix)
### S3. Whole gene expression matrix.
whole.matrix <- rbind(one2one.matrix, more2one.matrix)
### S4. Gene expression matrix.
PLIER_exprs[[i]] <- whole.matrix
}
###- VSN Expression Matrix ------------------------------------------------###
len.DS <- length(data_vsn)
VSN_exprs <- list()
for (i in 1:len.DS) {
### S1. One2one gene expression matrix.
one2one.matrix <- data_vsn[[i]][one2one.probe$PROBEID, ]
rownames(one2one.matrix) == one2one.probe$PROBEID
### S2. More2one gene expression matrix.
more2one.matrix <- NULL
for (s in 1:length(more2one)) {
pos <- which(one2any.probe$SYMBOL == more2one[s])
probe.pos <- one2any.probe$PROBEID[pos]
tmp <- data_vsn[[i]][probe.pos, ]
exp <- apply(tmp, 2, median)
more2one.matrix <- rbind(more2one.matrix, exp)
}
rownames(more2one.matrix) <- more2one
dim(more2one.matrix)
### S3. Whole gene expression matrix.
whole.matrix <- rbind(one2one.matrix, more2one.matrix)
### S4. Gene expression matrix.
VSN_exprs[[i]] <- whole.matrix
}
### Checking the dimension of each gene expression
dim(RMA_exprs[[1]])
dim(MAS_exprs[[1]])
dim(GCRMA_exprs[[1]])
dim(DCHIP_exprs[[1]])
dim(PLIER_exprs[[1]])
dim(VSN_exprs[[1]])
### renaming the six gene expression lists.
#
names(RMA_exprs) <- names(MAS_exprs) <- names(GCRMA_exprs) <- names(DCHIP_exprs) <- names(PLIER_exprs) <- names(VSN_exprs) <- Series.name
### Merging six gene expression lists into an large list consisting of all gene expression matrices.
exprs.mat2 <- list(RMA_exprs = RMA_exprs,
MAS_exprs = MAS_exprs,
GCRMA_exprs = GCRMA_exprs,
DCHIP_exprs = DCHIP_exprs,
PLIER_exprs = PLIER_exprs,
VSN_exprs = VSN_exprs)
### Cleaning the menmory of computer.
rm(RMA_exprs)
rm(MAS_exprs)
rm(GCRMA_exprs)
rm(DCHIP_exprs)
rm(PLIER_exprs)
rm(VSN_exprs)
### Checking the data integrity
rma <- exprs.mat2$RMA_exprs
mas <- exprs.mat2$MAS_exprs
gcrma <- exprs.mat2$GCRMA_exprs
dchip <- exprs.mat2$DCHIP_exprs
plier <- exprs.mat2$PLIER_exprs
vsn <- exprs.mat2$VSN_exprs
names(rma) == names(mas)
setwd("/Users/libo/Desktop/")
save(exprs.mat2, file = "HKs_149ds.RData")
###--------------------------------------------------------------------------###