Question: Inquiries about fitType on DESeq2

0

Michael Love ♦

**24k**wrote:hi Yoong,
Let's continue our discussion on the Bioconductor list, as it might be
useful for others as well.
On Sat, Nov 23, 2013 at 10:42 AM, FeiYian Yoong <fyoong@ucdavis.edu>
wrote:
> Dear Mike,
>
> I have a couple questions about fitType on DESeq2 (v 1.2.5). I was
reading
> your responses on SEqAnswers. But, since I couldn't view the
attached
> files, I couldn't get a good idea what you meant by which fitType to
use. I
> have the same warning message when I ran DESeq(dds) command with my
data:
>
> Warning messages:1: In log(ifelse(y == 0, 1, y/mu)) : NaNs
produced2: step size truncated due to divergence 3: In
estimateDispersionsFit(object, fitType = fitType, quiet = quiet) :
> parametric fit failed, trying local fit. use plotDispEsts() to
check the quality of the local fit
>
> The analysis was based on 1,000 genes (a subset of my 57,000 genes)
as a
> test. I am trying to fit these genes into a negative binomial GLM
before
> passing them through your independent filtering using res(). Because
of the
> warning message, I managed to run my data using only fitType=local.
Hence,
> I can't compare my fitType=local result with fitType=parametric.
Also, I
> ran another DESeq(dds) task using fitType=mean. My questions will
be:
>
> 1) Is fitType=local good enough for my analysis? How can I make sure
it's
> as comparable as parametric?
>
âThe plots of dispersion you sent me have a slightly increasing
slope over
the mean countsâ. It makes sense that the parametric fit failed,
because
the parametrization is
y = a/x + b, a,b > 0
then dy/dx = -a/x^2 < 0
The parametrization tries to match dispersions with a decreasing slope
over
the mean counts.
âThe local fit seems better for your data., so you can run DESeq()
with
fitType="local" instead. The instruction to check the quality of the
fit is
to make sure that the curve is not being overly influenced by
individual
genes, but this does not seem the case in the plot you sent me, so I
would
use fitType="local"
> 2) Based on the graphs, would you recommend me using fitType=mean
instead
> of local?
>
>
I don't really understand what it means by numerical integration on
VST for
> local fitType. Do you care to explain?
>
>
This is a more technical detail about the implementation in the man
page,
so maybe not interesting for non-statisticians. âThe variance
stabilizing
transformation involves integration of the variance as a function of
the
mean. When the local fit is used, the integration is not a symbolic
integration using the parametrized function, but a numeric integration
of
the local regression curve. â
âMikeâ
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