[BioC] [Limma] lmFit handle missing value in phenotype

[Moshe Olshansky]

Why do you want to include weight in the design matrix?
It may be more reasonable to include weight in the linear model, i.e.
expression ~ condition + weight and then your design matrix will have two
columns (if there are two conditions): the first column will contain 0's
and 1's depending on the condition (group) of the patient while the second
one will be identically 1. And then the weights of the patients will be in
the values (i.e. the second argument to lmFit) which I believe allows
missing values.
But this implicitly assumes that the weight (or some function of it - you
can use any transformation you like) contributes additively (and linearly)
to the expression (or it's logarithm).

Moshe.

> Hi,
>
> I am using Limma to get differential expressed genes between case and
> control samples. In addition, I want to adjust the "weight" of patients by
> including it in the "design" matrix. However, one weight value of a
> patient
> is missing, so I have a "NA" in design matrix. When I run lmFit, I got the
> error message :Error in qr.default(x) : NA/NaN/Inf in foreign function
> call
> (arg 1).
>
> Can limma handle the missing value in design matrix or I have to remove
> this sample ?
>
> Thanks,
>
> Chen
>
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>
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