Hi,
I have found that my selected gene, probe I.D 201667_at is differentially expressed between WDLPS and DDLPS tumour tissue samples after performing microarray DEG analysis.
Instead of just a p value in a table format:
Probe I.D "201667_at" logFC 10.8205874181535 AveExpr 10.6925705768407 t 82.8808890739766 P.Value 3.10189446528995e-88 adj.P Val 3.10189446528995e-88 "B" 191.589248589131
I have decided to present the data as a scatter plot/plot MDS (with an error bar) using expression values of the specific gene between the two tumour types (40 vs 52 samples) to show that it is differentially expressed. So 92 dots/points in total.
Does anyone know how I might do this, if I used these commands for microarray differential expression analysis.
library("arrayQualityMetrics")
library(GEOquery)
library(oligo)
library(Biobase)
library(affy)
library("splitstackshape")
library("tidyr")
library("dplyr")
celFiles <- list.celfiles()
affyRaw <- oligo::rma(affyraw)
eset <- oligo::rma(affyRaw)
library(limma)
pData(eset)
Groups <- c("DDLPS", "DDLPS", "WDLPS", "WDLPS")
design <- model.matrix(~factor(Groups))
colnames(design) <- c("DDLPS", "DDLPSvsWDLPS")
fit <- lmFit(eset, design)
fit <- eBayes(fit)
option (digits =2)
res <- topTable (fit, number = Inf, adjust.method = "none", coef = 1)
write.table(res, "diff_exp.txt", sep= "\t)
require(hgu133a.db)
annotLookup <- select(hgu133a.db, keys = probes,
columns = c('PROBEID', 'ENSEMBL', 'SYMBOL'))
Thankyou
duplicate biostars post https://www.biostars.org/p/9540169/#9540169