Re: [Mev-tm4-devel] Log transformations...

[Braisted, J. C. <bra...@ti...>]

Hi Carthika,
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The mev files are directly loadable into MeV if you would prefer not to
have to do
the log ratio ratios in Excel.  An annotation (.ann) file would be
needed
to load related annotation.  The data directory an example of the
annotation
file under 'TIGR_files' and there is a description in the MeV manual
appendix on=20
file formats.
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=3D=3D=3D=3D
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MeV simply uses the values in the TDMS file and does not perform a log
transformation
on the input data.  I gather that since you are focusing on a fold
change within a
particular array that you have replicate hybridizations of your
experimental condition samples
against reference samples or some sort of control condition sample and
that you are using=20
one sample TTEST to find significant genes.
=20
If this is not the case please describe the design a bit more since your
options will
vary based on whether you have one, two, or multiple experimental
groups.
=20
It is possible and likely that some genes will be statistically
significant yet will have a
mean fold change that is not far from 1.   Roughly speaking,
significance is a function
of mean difference over a measure of the variability of the
measurements.
It can happen that a gene is not highly over expressed or under
expressed yet the measurements
are so tight that the conclusion is made that there is a significant
change given the
confidence in the mean value (low replicate variability).  This can
happen even given
biological variation when thousands of genes are considered.
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I think it is valid to use t-test or SAM to find statistically
significant genes and report them
all or have them all ready in a supplemental table and then filter the
list to focus on those
genes that have more biologically significant changes (mean fold change
is larger).
*The fold change criteria or cutoff is arbitrary so I think reporting
all statistically significant genes
sorted by mean fold change would be a good compromise.  That way you
capture all
significant genes but the focus can be on those that were up or down
regulated by
the greatest magnitude fold change.
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**This is email going out to others in the MeV development group in case
there are other
opinions or ideas to add.  Please let us know if there are additional
question.
Thanks for using MeV and the TM4 suite.
=20
Best Regards,
=20
John Braisted
The Institute for Genomic Research
=20
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________________________________

From: Carthika Luxmanan [mailto:car...@an...]=20
Sent: Wednesday, October 11, 2006 9:54 PM
To: mev
Subject: Log transformations...


Hi there.=20

I have used MIDAS to carry out some normalisations on my mucroarray
data. The result is an MDS.mev file, which contains normalised data as
specified in MIDAS. Then I open these MDS.mev files for each of my
arrays in excel, and work out the Cy5/Cy3 ratio, log2 transform this
ratio, and make a file containing my log transformed data for each of my
arrays. Then I load this as a TDMS file in MeV, and carry out my
analyses. My question is, do I need to manually log transform my data
following MIDAS normalisation, or does MeV automatically take care of
this? I am generally finding that my expression ratios are quite low
when I look at differentially expressed genes from Mev, and I suspect
that perhaps my data is being log transformed twice. One my top
differentially expressed gene (with a very small p value) only has an
dye ratio of 1.1 fold (after I anti-log it). I would appreciate your
thoughts on this.

Thanks heaps
Carthika



________________________________________________________

Carthika Luxmanan, BSc(Hons)

Dept. Anatomy & Structural Biology

University of Otago

Dunedin

New Zealand

Office: +64 3 479 5182

Lab: +64 3 479 5792