[BioC] About the three weights in limma

De-Jian,ZHAO zhaodj at ioz.ac.cn
Tue Oct 23 14:34:07 CEST 2007


Dear list members,

There are three kinds of weights in the latest version of limma
(ver. 2.12.0). They are spot quality weights which is used in
function read.maimages, array quality weights, and print-tip quality
weights. All these three weights can be used in linear model fitting
and the default weight is spot quality weight. As we can see in the
source code of lmFit,"if (missing(weights) &&
!is.null(object$weights))  weights <- object$weights"(type lmFit and
enter for detail), thus the spot quality weights, inherited from the
primitive RGList, are utilized in the linear model fitting by
default. However,it can be changed by assigning to the parameter
'weights' of lmFit the array weights or print-tip weights produced
by arrayWeights or printtipWeights.

The three weights are at three different levels, i.e. array level,
print-tip level and spot level. Array level and print-tip level are
based on heteroscedastic model and the corresponding weights are
converted from the array variances or print-tip variances while the
spot quality weights are not. The spot quality weights are generated
using only the information of an individual spot.

My question comes. Can we extend the heteroscedastic model to spot
level?

At array level, all the genes on a chip share the same weight, or
the array weight produced by  arrayWeights. At the print-tip level,
all the genes in the same print tip share the same weight, or
print-tip weight produced by printtipWeights. In these two weights,
I prefer the print-tip weight since it has a better resolution and
it modulates the weight in a finer way. Then I cannot help thinking
whether the weight can be modulated in an even finer way, or at the
spot level. If we apply the heteroscedastic model to spots, can we
convert the variance to  spot weights as done in array weight and
print-tip weight?

I am not an expert in mathematics. I wonder whether this proposal is
reasonable and feasible. Furthermore, I think the best weight for
linear model fitting is print-tip weight up to now.

Thanks in advance for your reply.

Dejian Zhao



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