We are using DESeq to find differentially expressed genes for RNAseq experiment with two biological replicates. When we did the analyses considering them as biological replicates, we found that among differential expressed genes, there was a very high number of counts in one biorep compared to the others. Then we took biorep1 from experimental group and compared with biorep1 of the control group and there were only 3 genes differentially expressed at padj 0.05. However, there are lot of genes with thousands reads vs 0 in the two groups. Then we did the same with the second biorep and we found about 100 differentially expressed genes. Does anyone know why this is happening?
Seqanswers Leaderboard Ad
Collapse
Announcement
Collapse
No announcement yet.
X
-
Hi Simon,
Here is an example (attached txt file) for the genes that showed differential expression, but between the same experimental group variation was very high. Please let me if it is still not clear. I will try to explain again.Attached Files
Comment
-
Originally posted by Simon Anders View PostI'm not sure I understand your question. Could you give an example, please?
I have quite similar problem for the significant genes detected by DESeq and edgeR. Both of them output some significant candidates which have quite large variation within groups. Such as:
wt1: 2
wt2: 345
treat1: 3
treat2:1
or
wt1: 0
wt2: 345
treat1: 0
treat2: 0
Is it normal to get low p value for such kind of expression pattern? Thanks
Comment
-
Short answer: Please try again with the 'deve' version of DESeq (version 1.5.19), and this oddity should vanish.
Long answer: In the current release version of DESeq (version 1.4.1), we estimate a variance for each gene, fit a line through the mean-variance plot, and then use the fitted value of the variance, i.e., the value typical for a gene of the same expression strength. The 'nbinomTest' function gives you, besides the p values, two columns with the "variance residuals", i.e., the ratio of the gene's variance estimate over the fitted value. Cases such as your should show up as having a large value there and the vignette advises to disregard such hits in the downstream analysis.
Nobody ever read this sentence in the vignette, and also, the solution was rather unsatisfactory anyway, and so we have now changed this. Now, we do not use anymore always the fitted value, but instead the maximum of the per-gene estimate and the fitted value. This avoids artifacts like the ones you see. Have a look at the help page for 'estimateDispersion' in the new version, and also at the vignette, which we have extensively overhauled.
Comment
-
Originally posted by Simon Anders View PostShort answer: Please try again with the 'deve' version of DESeq (version 1.5.19), and this oddity should vanish.
Long answer: In the current release version of DESeq (version 1.4.1), we estimate a variance for each gene, fit a line through the mean-variance plot, and then use the fitted value of the variance, i.e., the value typical for a gene of the same expression strength. The 'nbinomTest' function gives you, besides the p values, two columns with the "variance residuals", i.e., the ratio of the gene's variance estimate over the fitted value. Cases such as your should show up as having a large value there and the vignette advises to disregard such hits in the downstream analysis.
Nobody ever read this sentence in the vignette, and also, the solution was rather unsatisfactory anyway, and so we have now changed this. Now, we do not use anymore always the fitted value, but instead the maximum of the per-gene estimate and the fitted value. This avoids artifacts like the ones you see. Have a look at the help page for 'estimateDispersion' in the new version, and also at the vignette, which we have extensively overhauled.
Thanks for your quick reply. One more question about installation of the devel DESeq.
I have downloaded the newest version of Biobase from bioconductor, but DESeq require even advanced version.(http://www.bioconductor.org/packages...l/Biobase.html )
Do you know where to download >=2.13.6 Biobase? Thanks.
"
Error : package 'Biobase' 2.12.2 was found, but >= 2.13.6 is required by 'DESeq'
"
Comment
-
Originally posted by Gangcai View PostHi Simon,
Thanks for your quick reply. One more question about installation of the devel DESeq.
I have downloaded the newest version of Biobase from bioconductor, but DESeq require even advanced version.(http://www.bioconductor.org/packages...l/Biobase.html )
Do you know where to download >=2.13.6 Biobase? Thanks.
"
Error : package 'Biobase' 2.12.2 was found, but >= 2.13.6 is required by 'DESeq'
"
Comment
-
At http://www.bioconductor.org/packages...l/Biobase.html
However, installing a 'devel' version of Biobase over a 're'ease' installtion of Bioconductor might cause chaos. Better install the devel version of R and then, 'bioclite' will pull 'devel' versions of all Bioc packages.
Comment
-
Hi Simon,
I have tried the deve version of DESeq. The number of significant genes drop quite a lot. It does look better comparing with previous result. But still have some genes have high variation within biological repilcates.
wt1 wt2 treat1 treat2 pvalue_adjusted
928 0 0 0 <<0.01
0 135 0 0 <<0.01
Comment
-
Could you please try again with
Code:cds <- estimateDispersions( cds, method="pooled" )
Comment
Latest Articles
Collapse
-
by seqadmin
Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...-
Channel: Articles
03-22-2024, 06:39 AM -
-
by seqadmin
The field of conservation genomics centers on applying genomics technologies in support of conservation efforts and the preservation of biodiversity. This article features interviews with two researchers who showcase their innovative work and highlight the current state and future of conservation genomics.
Avian Conservation
Matthew DeSaix, a recent doctoral graduate from Kristen Ruegg’s lab at The University of Colorado, shared that most of his research...-
Channel: Articles
03-08-2024, 10:41 AM -
ad_right_rmr
Collapse
News
Collapse
Topics | Statistics | Last Post | ||
---|---|---|---|---|
Started by seqadmin, 03-27-2024, 06:37 PM
|
0 responses
13 views
0 likes
|
Last Post
by seqadmin
03-27-2024, 06:37 PM
|
||
Started by seqadmin, 03-27-2024, 06:07 PM
|
0 responses
11 views
0 likes
|
Last Post
by seqadmin
03-27-2024, 06:07 PM
|
||
Started by seqadmin, 03-22-2024, 10:03 AM
|
0 responses
53 views
0 likes
|
Last Post
by seqadmin
03-22-2024, 10:03 AM
|
||
Started by seqadmin, 03-21-2024, 07:32 AM
|
0 responses
69 views
0 likes
|
Last Post
by seqadmin
03-21-2024, 07:32 AM
|
Comment