I have some question about normalization in package tweeDEseq which using
TMM method in edgeR to normalize count data. I run normalization as manual
and found something unusual. The read count before normalization of gene 4
sample X1 and X2 is 0, but after normalization it turn to 4 and 3. Why
normalization add count into 0 count? Did it effect from tagwise
dispersions? I post my code under here for more information. Thank you in
advance.

Sermsawat Tunlaya-anukit

> library(tweeDEseq)
> y <- read.table("rawcount.txt", header=T )
> group <- c(1,1,1,2,2,2,2,3,3,3,4,4)
> yN <- normalizeCounts(y, group)
Using edgeR normalization methods.
Calculating library sizes from column totals.
Calculating normalization factors with the TMM method.
Estimating common dispersion.
Estimating tagwise dispersions.
Calculating effective library sizes.
Adjusting counts to effective library sizes using tagwise dispersions.
> head(y)
   X1  X2   X3   X4  X5  X6   X7   X8  X9  X10 X11 X12
1   0   0    0    1  11  18   16   12   9   12  25  19
2  14  28   84   56  54  40  114   86  43   91 150  83
3  12   8   18   15  12  10   32   19  27   31  44  21
4   0   0    0    0   0   0    0    0   0    0   0   0
5   4   6    8    3   7  12   22   44  14    1   1   2
6 899 725 1563 1342 173 129 1072 1607 172 1184 720 524
> head(yN)
       X1   X2   X3   X4  X5  X6  X7   X8  X9 X10 X11 X12
[1,]    1    1    0    1  13  22   7    7  13   8  13  17
[2,]   39   64   81   56  63  51  49   53  65  58  77  76
[3,]   29   18   17   15  14  13  13   11  39  20  22  19
[4,]    4    3    0    0   0   1   0    0   1   0   0   0
[5,]   10   13    8    3   8  15  10   28  21   0   0   2
[6,] 2306 1652 1497 1342 201 164 468 1001 261 752 363 476
> sessionInfo()
R version 2.14.1 (2011-12-22)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] C/en_US.UTF-8/C/C/C/C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] tweeDEseq_1.0.11

loaded via a namespace (and not attached):
[1] MASS_7.3-16  edgeR_2.4.3  limma_3.10.2 tools_2.14.1

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