Question: DESEQ2 Finding Unchanged Genes
1
gravatar for tirza.doniger
12 months ago by
tirza.doniger20 wrote:

Hi,

 

I think I followed the correct steps to find significant unchanged genes between the conditions, but it returns no significant genes.

What does that mean? Isn't the basic assumption of the analysis that most of the genes are unchanged?

Version: DESeq2_1.20.0     

Thanks!

Tirza Doniger

======================================================

dataset <- DESeqDataSetFromMatrix(countData = merged_counts,
                                  colData = colData,
                                  design= ~Treatment)

ddsNoPrior <- DESeq(dataset, betaPrior=FALSE)
resLA <- results(ddsNoPrior, lfcThreshold=0.1, altHypothesis="lessAbs")

=============================================================

> summary(resLA)

out of 21068 with nonzero total read count
adjusted p-value < 0.1
LFC > 0.10 (up)    : 0, 0%
LFC < -0.10 (down) : 0, 0%
outliers [1]       : 0, 0%
low counts [2]     : 0, 0%
(mean count < 0)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results

==================================================

 

 

ADD COMMENTlink modified 12 months ago by Michael Love25k • written 12 months ago by tirza.doniger20
Answer: DESEQ2 Finding Unchanged Genes
0
gravatar for Michael Love
12 months ago by
Michael Love25k
United States
Michael Love25k wrote:

hi Tirza,

The short answer is that you don't have enough precision on the LFCs to say that any are within (-0.1, 0.1). If you expanded the range, you could probably reject some of the null hypotheses at your current sample size, or if you had more samples you could get more precision on the LFC estimates.

ADD COMMENTlink written 12 months ago by Michael Love25k
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