Warning in lfproc when using rlog or varianceStabilisingTransformation from DESeq2
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katja • 0
@katja-7627
Last seen 6.5 years ago
Sweden

Hi,

during the analysis of sRNA sequencing data I encountered a warning that I do not understand.

From counts of sRNA sequences I built a DESeqDataSet (7 groups of sRNA sequences x 28 samples) and performed normalisation with rlog function.

rld <- rlog(dds, blind = TRUE)

After that I got a warning:

NOTE: fitType='parametric', but the dispersion trend was not well captured by the
  function: y = a/x + b, and a local regression fit was automatically substituted.
  specify fitType='local' or 'mean' to avoid this message next time.

Warning message:
In lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth,  :
  Estimated rdf < 1.0; not estimating variance

When I used fitType = "mean", there was no warning, but it appeared when I chose fitType = "local":

Warning message:
In lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth,  :
  Estimated rdf < 1.0; not estimating variance

The same thing also happend when I used a function varianceStabilisingTransformation. I also used blind = TRUE and tried different settings of fitType.

I read the vignette from DESeq2 package, documentation for rlog and varianceStabilisingTransformation, but could not find the answer, what the warning means. I also could not find the explanation of lfproc function or rdf. Did anyone encounter the same problem or does anyone know what it means? Could it be that there is not enough datapoints for the methods to work?

Thanks for your help,

Katja

DESeq2 rlog varianceStabilizingTransformation lfproc • 1.5k views
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Entering edit mode
@mikelove
Last seen 2 days ago
United States
I'll take a look at writing a better warning. Yes, with only 7 rows, there are too few points to fit a smooth trend line of dispersion ~ mean. So the mean fit type is all I would use.
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