Question: Highly biased experiment showing funny histogram of p values for all tests. Suggestions?
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gravatar for Mozart
4 weeks ago by
Mozart140
Mozart140 wrote:

Dear all, I am struggling (as usual) with a really important/expensive experiment we manage to complete. Having done this in different days, plus given the fact we are not expecting a strong phenotype (we are treating cells with a molecule that shouldn't change these ones that much), I would imagine not so many genes differentially expressed. Perfect. I initially corrected the experiment for batch effect. Indeed, I added an extra column to my model matrix in this way:

Table <- data.frame(condition = factor(c("A","A","A","B","B","B","C","C","C","A","B","C","D","D","D","D")))

Table$batch = factor(c('day1','day2','day3','day1','day2','day3','day1','day2','day3','day4','day4','day4','day4','day1','day2','day3'))

table(sampleTable)

Thus, having:

> table(Table)
     batch
condition day1 day2 day3 day4
    A      1    1    1    1
    B      1    1    1    1
    C      1    1    1    1
    D      1    1    1    1

Then:

dds <- DESeqDataSetFromTximport(txi.kallisto.tsv, Table, ~batch+condition)
dds <- DESeq(dds)
nrow(dds) **#[1] 29654**
res = results(dds)

Say I want to compare A(treated) vs B(untreated):

dds$condition <- relevel(dds$condition, ref = "B")
dds <- DESeq(dds)

results_A_vs_B<-results(dds, c("condition", "A", "B"))

If I plot the histogram of p values I get something like this: enter image description here Which is pretty odd I guess, given the fact I get a lot of unfiltered values in my final experiment that are around pval=1.

then, I decided to remove low counts by arbitrarily choosing the following filtering parameter:

idx <- rowSums( counts(dds, normalized=TRUE) >= 8 ) >= 6
dds <- dds[idx,]
res = results(dds)

then,

dds$condition <- relevel(dds$condition, ref = "B")
dds <- DESeq(dds)

results_A_vs_B<-results(dds, c("condition", "A", "B"))

it's even worse, I guess:

enter image description here

So there's no doubt there's something wrong here but not sure how to get rid of it.

Do you have any ideas?

Thanks

filtering rna-seq deseq2 • 119 views
ADD COMMENTlink written 4 weeks ago by Mozart140

I cannot see the figures, is it me or something went wrong?

ADD REPLYlink written 28 days ago by Fabio Marroni2.3k
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