Search
Question: estimating size factors in DESeq produces warnings
0
gravatar for Assa Yeroslaviz
3.8 years ago by
Assa Yeroslaviz1.3k
Munich, Germany
Assa Yeroslaviz1.3k wrote:
Hi, I am using Deseq to analyze my data. I have three replica for each of the two conditions. When I am running the script in the normal way: cds = newCountDataSet( Counts_set, condition ) cds = estimateSizeFactors( cds ) # uses the median as location function cds = estimateDispersions( cds ) I get the following error massage: There were 16 warnings (use warnings() to see them) > warnings() Warning messages: 1: In log(ifelse(y == 0, 1, y/mu)) : NaNs produced 2: step size truncated due to divergence ... The dispersion plot looks like that: DispersionPlot.png but with fitType="local" ot looks like that: DispersionPlotLocal.png When I am doing the same analysis, but with fitType="local" the warnings disappears. I read that this happens ,When One is using the analysis without replica, but I have three for each condition. Is it preferable to run the analysis with local fit type? What is the meaning of these warnings? Thanks, Assa -------------- next part -------------- A non-text attachment was scrubbed... Name: DispersionPlot.png Type: image/png Size: 51440 bytes Desc: not available URL: <https: stat.ethz.ch="" pipermail="" bioconductor="" attachments="" 20140114="" 2f903926="" attachment.png=""> -------------- next part -------------- A non-text attachment was scrubbed... Name: DispersionPlotLocal.png Type: image/png Size: 50242 bytes Desc: not available URL: <https: stat.ethz.ch="" pipermail="" bioconductor="" attachments="" 20140114="" 2f903926="" attachment-0001.png="">
ADD COMMENTlink modified 3.8 years ago by Simon Anders3.4k • written 3.8 years ago by Assa Yeroslaviz1.3k
0
gravatar for Simon Anders
3.8 years ago by
Simon Anders3.4k
Zentrum für Molekularbiologie, Universität Heidelberg
Simon Anders3.4k wrote:
Hi Assa On 14/01/14 18:55, Assa Yeroslaviz wrote: > I am using Deseq to analyze my data. I have three replica for each of the > two conditions. First: Please always include some information about the biology of your experiment. These thing tend to matter more than people think when discussing statistics. Your dispersion plot seems to linearly fall down all the way to 10^-6. For biological replicates, this is more than just unusual. Which steps exactly have you replicated in your experiment? > cds = newCountDataSet( Counts_set, condition ) > cds = estimateSizeFactors( cds ) # uses the median as location function > cds = estimateDispersions( cds ) > I get the following error massage: > There were 16 warnings (use warnings() to see them) >> warnings() > Warning messages: > 1: In log(ifelse(y == 0, 1, y/mu)) : NaNs produced > 2: step size truncated due to divergence There is no error, there are warnings. (That's not the same thing; sorry for nitpicking.) Here, the warnings inform you that something might have gone wrong when determining the fit. Hence you should inspect the dispersion plots to verify that the fit worked -- as you did. > Is it preferable to run the analysis with local fit type? No. If you compare your two plots, it is very clear that fitType="parametric" gave you a good fit (red line goes through the point cloud), and for fitType="local", something went completely wrong. I actually have no clue why the fit looks that strange. Why does the plot titles say "using fit-only mode", by the way? You should not use fit-only mode, except in very special cases. > When I am doing the same analysis, but with fitType="local" the warnings > disappears. This is actually odd. The warnings relate to the estimation, not the fitting, so there should be no difference. I would need to see your exact code to get at the bottom of this, but I guess, you somehow accidentally overwrite some data. > I read that this happens ,When One is using the analysis without replica, > but I have three for each condition. No, it has nothing to do with that. > What is the meaning of these warnings? It means that some intermediate calculations during the fit resulted in some infinities. A fit tries various values, if some does not work, the fitter typically tries something else. Therefore, the warning is usually harmless; we should maybe suppress it. Finally: As you are only at the beginning of your analysis, please consider starting over with DESeq2. We intend to phase out support for the old DESeq package with time, as its methodology is rather outdated by now. Simon
ADD COMMENTlink written 3.8 years ago by Simon Anders3.4k
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.2.0
Traffic: 136 users visited in the last hour