[BioC] Tissue heterogeneity and TMM normalization

Ni Feng fengni99 at gmail.com
Mon Sep 8 18:15:38 CEST 2014

Dear all,
I have a general question about whether TMM normalization is appropriate
for my data. I apologize for this long winded email. I am not a trained
bioinformatician and therefore have been struggling with some data

A colleague and I did an RNA seq experiment with 6 samples (each had RNA
pooled from 6 individuals) and no biological replicates. The 6 samples
included 2 tissue types collected at 3 different time points. I know that
this is not an ideal experimental set-up, we did this experiment 3 years

We used the Trinity package to do most of the transcriptome assembly and
downstream analyses, such as leveraging EdgeR for differential expression.
Naively I went on with all downstream analyses without verifying whether my
data violated underlying assumptions of TMM normalization.

For example, we found ~30% of our transcripts showed differential
expression between any 2 pairwise comparisons. Does this violate the TMM
assumption that most genes are NOT differentially expressed?

Furthermore, we noticed that there is still a tissue bias after
normalization. Attached is a scatterplot of TMM normalized values for each
tissue (summed across 3 sample groups for each tissue). Plotted in black on
top of all transcripts are CEG (Core Eukaryotic Genes) expression, which we
believe should be good candidates for "house keeping" genes. Both CEGs and
all genes show that at higher expression levels, there is a skew towards
one tissue ("VMN"), whereas in the middle values, there is a skew towards
the other tissue ("H").

I have also attached a density plot of the M values, and a MA plot to
visualize the skew. These plots were generated from 1 pair of tissue
comparisons ("SMH" vs "SMV).

These plots reflect the fact that one tissue is more heterogeneous than the
other. Although TMM normalization is designed to deal with this problem,
our data seems to need further normalization. Our within tissue comparisons
are great and do not show this kind of skew. My questions are:

1) does our data violate TMM normalization assumptions
2) do you have another normalization method to suggest for our data
3) should we just forget about tissue-comparisons

I have also played around with the suggestions about estimating a
dispersion value based on the EdgeR user guide. Can discuss this further.

Thank you for your time and patience, and any advice is much appreciated.

Ni (Jenny) Ye Feng
Ph.D. Candidate
Bass Laboratory
Cornell University
Dept of Neurobiology and Behavior
Ithaca, NY 14853
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