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Magda Price
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@magda-price-6411
Last seen 7.8 years ago
Hi!
I'm writing with a few questions about applying ComBat (sva package)
to a
set of ~50 samples run on the the Illumina Infinium
HumanMethylation450
BeadChip array (~450,000 DNA methylation data points).
There is a large amount of variation in my data due to both the batch
the
samples were run in (3 different batches), in addition to the position
they
were located on the chip - specifically the row (6 different rows),
but not
the column. The chips are set up in a 6 row * 2 column format like
this:
sample 01 sample 02
sample 03 sample 04
sample 05 sample 06
sample 07 sample 08
sample 09 sample 10
sample 11 sample 12
I read Dr. Evan Johnson's suggestions to someone else with this
"2-batch-effect-variable" problem in the ComBat google group (
https://groups.google.com/forum/#!topic/combat-user-
forum/PcTxNlaUmAI). He
had 2 good suggestions:
1. Combine the two batch variables into one, if 3-4 reps are left
in
each batch
2. Use ComBat twice, adjusting for the first batch using the second
batch as a covariate, and then adjust for the second batch.
I cannot go with the first suggestion because combining the 2 batch
variables would create 18 batch categories (3 batches * 6 rows), and I
would not have enough replicates per batch category.
So I tried the second option - applying ComBat twice. I first
corrected for
row and then took the row-corrected data and applied ComBat again,
correcting for batch. It seems to have worked & the correlation of my
technical replicates improves. I am seeking advice on two points:
1. The google group post is now a few years old, is it still
thought
that the step-wise correction is a valid approach?
2. Row would be better treated as a continuous adjustment variable
than
a factor. In the version of sva that I am using (3.0.2) I believe
that only
factors adjustment variables are supported. I have seen mention in
a few
forums that there might be an update to ComBat to adjust for a
numeric
batch variable, is one available?
Thank you in advanced for your help!
Magda Price,
University of British Columbia
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