Hi all,

 I am looking for a bit of enlightenment regarding edgeR. We are applying
edgeR using ANOVA-like testing. We have 2 conditions (Cases and Controls)
sampled at 2 treatments (untreated and treated)  with 64 biological
replicates per condition (64 X 2 = 128 samples).

 We want to test 3 ways:

1.     DE between untreated and treated for cases.

2.     DE between untreated and treated for controls.

3.     DE between untreated and treated responding differently between
Cases and Controls.

 I am curious if my design matrix is set up properly and if we are testing
with the right coefficients and contrasts as seen below to address these
three approaches.

 Any insight is helpful.

 Yours,
Michael



rawdata <- read.delim("Matrix.txt", check.names=FALSE,
stringsAsFactors=FALSE)
targets <- read.delim("Described.txt", check.names=FALSE,
stringsAsFactors=FALSE)
head(targets)

  Condition Patient Treatments

1      Case    4060     untreated

2      Case    4060     treated

3      Case    4096     untreated

4      Case    4096     treated

5      Case    4099     untreated

6      Case    4099     treated

 y <- DGEList(counts=rawdata[,2:129], genes=rawdata[,1:1])

keep <- rowSums(cpm(y)>1) >= 64
y <- y[keep,]
dim (y)

y <- calcNormFactors(y)
y$samples

design <- model.matrix(~Condition+Condition:Patient+Condition: Treatments,
data=targets)
colnames(design)

[1] "(Intercept)"              "ConditionControl"

[3] "ConditionCase:Patient"    "ConditionControl:Patient"

[5] "ConditionCase:Treatments "      "ConditionControl:Treatments "



y <- estimateGLMCommonDisp(y, design, verbose=TRUE)
y <- estimateGLMTrendedDisp(y, design)
y <- estimateGLMTagwiseDisp(y, design)

fit <- glmFit(y, design)
colnames(fit)

# DE between untreated and treated for cases
lrt <- glmLRT(fit, coef="ConditionCase: Treatments ")

# DE between untreated and treated for cases
lrt2 <- glmLRT(fit, coef="ConditionControl:Treatments ")

# DE between untreated and treated responding differently between cases and
controls
lrt3 <- glmLRT(fit, contrast=c(0,0,0,0,1,-1)

	[[alternative HTML version deleted]]