SEQanswers

Go Back   SEQanswers > Applications Forums > RNA Sequencing

Similar Threads
Thread Thread Starter Forum Replies Last Post
DESeq Variance Stabilizing Transformation john_nl Bioinformatics 8 04-30-2014 12:14 PM
Converting FPKM from Cufflinks to raw counts for DESeq jebe Bioinformatics 34 02-05-2014 09:19 AM
large variance of raw read numbers between samples mrfox RNA Sequencing 4 07-16-2013 10:23 AM
Can DEXSeq output variance stabilized data like DESeq? elizzybethy Bioinformatics 0 09-19-2012 08:09 AM
Error message in DESeq (estimateVaranceFunctions, preplot.locfit.raw) aquila RNA Sequencing 4 02-02-2011 09:42 AM

Reply
 
Thread Tools
Old 04-17-2014, 06:14 AM   #1
narges
Member
 
Location: Finland

Join Date: Aug 2012
Posts: 29
Default DESeq raw variance

Variance in DESeq is the sum of shot noise and raw variance. The raw variance is the smooth function of estimated read counts and experimental condition. In the corresponding paper, it is mentioned that this function aim to pool the genes with the same strength to estimate the variance(due to the more probable few number of replicates).
I am not sure if I have understand it correctly. Does this means that DESeq groups n genes (i1, i2, ...in) from a common condition with similar expression levels and then calculate the variance for them? So, instead of calculating the variance for a specific gene, it calculates the variance for a group of similar gene and associate that value for all of them?
And how does it decide which genes have similar strength (? similar expression levels)?
Then can we conclude that DESeq does not calculate the gene-specific variance but group of genes-specific variance?
narges is offline   Reply With Quote
Old 04-17-2014, 07:00 AM   #2
dpryan
Devon Ryan
 
Location: Freiburg, Germany

Join Date: Jul 2011
Posts: 3,480
Default

Well, variance is the sum of technical (shot noise) and biological sources, though perhaps you mean the latter by "raw".

The process of fitting the smooth curve to the data is essentially the "pooling information" step, since variances are then shrunken toward it (generally you use distance from this line as a penalty and perform maximum-likelihood estimation of the variance with that, though I recall DESeq2 also treats genes with variance >3sigma (or something like that, it's in their paper) from the expected differently). So no, DESeq2 doesn't group genes from a common condition with similar expression levels and then calculates variance from that. It calculates per-gene variance and then shrinks that toward the expected value.
dpryan is offline   Reply With Quote
Old 04-17-2014, 07:47 AM   #3
narges
Member
 
Location: Finland

Join Date: Aug 2012
Posts: 29
Default

Quote:
Originally Posted by dpryan View Post
Well, variance is the sum of technical (shot noise) and biological sources, though perhaps you mean the latter by "raw".
Yes, I meant the biological oriented variance.
Thanks!
Is it true that point "Px" in smooth curve is the mean of count values for gene gene x in the condition p? So, it forms the curve based on the means for each gene of a condition and next shrunken the variances to their corresponding point on the mean-specific smooth curve?
narges is offline   Reply With Quote
Old 04-17-2014, 11:24 AM   #4
dpryan
Devon Ryan
 
Location: Freiburg, Germany

Join Date: Jul 2011
Posts: 3,480
Default

No, that's not strictly true. It will typically be the case that there's only 1 gene with a mean expression of a certain value, so that would mean that the curve must go through that mean, which will typically not be the case. The curve is fit to the means, as you mentioned (at least that's my recollection), so the remainder of what you wrote looks correct.
dpryan is offline   Reply With Quote
Reply

Tags
deseq, variance estimation

Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off




All times are GMT -8. The time now is 11:02 PM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2021, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO