Okay, sorry.  Here's more information:

The model design I am using is       *design <- model.matrix( ~ geno * trt)*,
where "geno" has 76 values and "trt" has 2 (sun, shade)

Using glmLRT, I am testing "trt", so      *  lrt <- glmLRT(dge, fit , coef
= grep("trt", colnames(design))*

The logFC values returned by topTags, then, are for columns
*trtshade, geno2.trtshade, geno3.trtshade
*, etc.

I also test "geno", where the logFC values are for columns        *geno2,
geno3, geno2.trtshade, geno3.trtshade*, etc.

Ultimately I test the interaction, so logFC values are for columns
  *geno2.trtshade,
geno3.trtshade, geno4.trtshade*, etc.

I am trying to figure out what these logFC coefficients are compared to, in
each case.  If I am interested in specific genotype effects, will I get a
more appropriate answer by testing "geno2" individually, rather than "geno"
all at once?

Thanks - I do appreciate it.







*****
Susan Bush, Ph. D.
Postdoctoral Scholar
Maloof Lab, Dept of Plant Biology
University of California, Davis
1 Shields Avenue
Davis, CA 95616

email: smbush@ucdavis.edu
lab: 530-752-8086
cell: 507-828-8958


On Tue, Aug 27, 2013 at 5:05 PM, Gordon K Smyth <smyth@wehi.edu.au> wrote:

> Dear Susan,
>
>  Date: Mon, 26 Aug 2013 18:28:03 -0700 (PDT)
>> From: "Susan [guest]" <guest@bioconductor.org>
>> To: bioconductor@r-project.org, smbush@ucdavis.edu
>> Subject: [BioC] edgeR topTags output (logFC)
>>
>>
>> I'm just wanting to confirm my understanding of the edgeR topTags()
>> output.  I'm using a design matrix with many coefficients (76 genotypes, 2
>> treatments[sun, shade]).
>>
>> 1) In the topTags output, I am looking at logFC which represents the
>> estimated or predicted means -- NOT coefficients, correct?
>>
>
> Incorrect.  As the abbreviation suggests, logFC gives you
> log-fold-changes.  logFC are indeed coefficients, not group means.
>
>  2) I have selected one parental genotype to be my reference genotype, and
>> I am comfortable interpreting the logFC values for the other genotypes as
>> comparisons to this genotype.  I have selected one treatment as the
>> reference (sun).  When I see the logFC values for 'trtshade', I assume this
>> is also in comparison to the reference genotype in the reference treatment.
>>
>
> Yes, assuming that trt is what you have called the treatment factor, then
> trtshade would the coefficient estimating the log-fold-change between the
> shade and sun treatments.
>
>  My question is about looking at 'geno2.trtshade' values - are these
>> values in comparison to 'trtshade' or 'geno2' or the reference
>> genotype/reference treatment values?
>>
>
> Without knowing what model you have fitted, or which coefficients you have
> tested for, it is impossible to tell.
>
> Best wishes
> Gordon
>
>  For example:  this is calling glmLRT with coef = grep("trt",
>> colnames(Design)) to identify treatment effects
>>
>>           Row.names       logFC.trtsha    logFC.genoIL1.1.trtsha   logCPM
>>        LR        PValue           FDR
>> 1 Solyc08g078300.2.1    0.9440264           -0.379030370 4.207443
>> 1135.8061 1.450273e-188 1.637938e-184
>> 2 Solyc06g060830.2.1    0.9630343            0.038988710 4.511893
>> 1095.1525 2.539194e-180 1.433883e-176
>> 3 Solyc06g067910.2.1    1.2468599           -0.096499016 4.795789
>> 1040.5813 2.722511e-169 1.024935e-165
>> 4 Solyc06g008580.2.1    1.1500683           -0.451731914 3.300982
>>  696.1677 6.043868e-101  1.706486e-97
>> 5 Solyc07g017600.2.1    0.5026292            0.007208458 5.209938
>>  694.2070 1.451776e-100  3.279271e-97
>> 6 Solyc10g083760.1.1   -0.2877568            0.045952894 7.033394
>>  651.8629  2.232759e-92  4.202796e-89
>>
>> Thanks so much!
>>
>>
>> -- output of sessionInfo():
>>
>>  sessionInfo()
>>>
>> R version 3.0.1 (2013-05-16)
>> Platform: x86_64-pc-linux-gnu (64-bit)
>>
>> locale:
>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C         LC_TIME=C
>>  LC_COLLATE=C         LC_MONETARY=C        LC_MESSAGES=C        LC_PAPER=C
>> [8] LC_NAME=C            LC_ADDRESS=C         LC_TELEPHONE=C
>> LC_MEASUREMENT=C     LC_IDENTIFICATION=C
>>
>> attached base packages:
>> [1] splines   stats     graphics  grDevices utils     datasets  methods
>> base
>>
>> other attached packages:
>> [1] ggplot2_0.9.3.1 reshape_0.8.4   plyr_1.8        edgeR_3.2.3
>> limma_3.16.4
>>
>> loaded via a namespace (and not attached):
>> [1] MASS_7.3-26        RColorBrewer_1.0-5 colorspace_1.2-2
>> dichromat_2.0-0    digest_0.6.3       grid_3.0.1         gtable_0.1.2
>> labeling_0.1
>> [9] munsell_0.4        proto_0.3-10       reshape2_1.2.2     scales_0.2.3
>>       stringr_0.6.2      tools_3.0.1
>>
>
>
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