Hello i'm newbie for bioinformatics field, and now studying the R to get the DEG from the samples. (And I apologize with my bad English because i'm NOT USED TO WRITING WITH IN ENGLISH.. )
I have four samples from same cell line which were treated with same treatment, but they are assumed to have different characteristics because of the other factors . (this is just the characteristic of the experiment)
I know that i need to use model.matrix() function in R to design the experiment for edgeR or Voom (limma).
Because of my short knowledge of statistics and BI, i'm really not sure how to design the matrix in proper way.
Is there anybody who can give me the idea how to design the matrix?
There are some ideas that i thought of, but i'm not sure with them because there's no replicate for wild type.
(1) First try:
............| DIFF | WT ResultCell.1 | 1 | 0 ResultCell.2 | 1 | 0 ResultCell.3 | 1 | 0 ResultCell.4 | 1 | 0 WildTypeC | 0 | 1
TAG = factor(c(rep("DIFF",4),"WT")) design = model.matrix(~0+TAG) YY = estimateGLMCommonDisp(YY, design, verbose=TRUE) YY = estimateGLMTrendedDisp(YY, design) YY = estimateGLMTagwiseDisp(YY, design) FIT = glmFit(YY, design) LRT = glmLRT(FIT, contrast = c(1,-1))
(2) Second try:
..............| DIFF | WT ResultCell.1 | 1 | 0 WildTypeCel | 0 | 1 ResultCell.2 | 1 | 0 WildTypeCel | 0 | 1 ResultCell.3 | 1 | 0 WildTypeCel | 0 | 1 ResultCell.4 | 1 | 0 WildTypeCel | 0 | 1
SAMPLES = factor(c(1,1,2,2,3,3,4,4)) GROUP = factor(c(rep(c("DIFF","WT"),4))) design = model.matrix(~GROUP+SAMPLES) y = estimateGLMCommonDisp(y, design, verbose=TRUE) y = estimateGLMTrendedDisp(y, design) y = estimateGLMTagwiseDisp(y, design) FIT = glmFit(y, design) LRT = glmLRT(FIT, contrast = c(0,-1,0,0,0))
I tried both, and the result really different. To me, it was much better to see the plot of the second design matrix, because it showed much more organized form. I really tried to follow edgeR help page and searched some pages, but there was no case that used only one wild type and comparing other samples...... (in case that i searched carefully).