[BioC] limma-voom

[Yi, Ming (NIH/NCI) [C]]

Thanks a lot for all of your inputs, which are all very helpful! Indeed, I did use the barcode to get the matched normals for the tumors of the same patients. My normals are all code 11, which are supposed to be solid tissues as Steve mentioned. Also the plotMDS plots seem showing a very separation of normal vs tumors in all cases, which seem promising. I agreed with Tim, there are always concern or precaution about what the normal tissues are and how they are collected, which however are not under our own controls. Thanks again for the great info and discussions!  Ming

-----Original Message-----
From: Tim Triche, Jr. [mailto:tim.triche at gmail.com] 
Sent: Wednesday, February 05, 2014 11:16 PM
To: Jeremy Ng
Cc: Steve Lianoglou; Gordon K Smyth; Bioconductor mailing list
Subject: Re: [BioC] limma-voom

Yes, "normal" is a euphemism. Very often, asymptomatic cells will turn out to have microenvironmental cues that lead to co-opting by tumor cells or blasts. But they're nearby, and they looked normal at the time of debulking/collection, and so it goes.

The blood samples are for germline genotyping in solid tumors (obviously that wouldn't have worked for leukemia, so in that case skin punches were used as normals).  As it happens, that's more interesting than somatic mutations in some cases. But that's another topic :-)

TCGA had some issues early on, but mistaking blood for solid tissue was not one of them. You have to use the barcode (or, later, the UUID) to obtain full information on a given sample. 

--t

> On Feb 5, 2014, at 7:19 PM, Jeremy Ng <jeremy.ng.wk1990 at gmail.com> wrote:
> 
> Hi,
> 
> Just wanted to add in a little more on the "normal" adjacent samples that
> TCGA uses.
> 
> I work with breast cancer samples, and it has appeared that some(if not
> many) of these "normal" adjacent samples are really similar to the tumour
> themselves. This has been reported earlier (see
> http://cancerres.aacrjournals.org/cgi/content/meeting_abstract/72/24_MeetingAbstracts/P1-03-02
> ).
> 
> Just thought it will be worth sharing.
> 
> Cheers,
> Jeremy
> 
> 
> 
> On Thu, Feb 6, 2014 at 7:23 AM, Steve Lianoglou <lianoglou.steve at gene.com>wrote:
> 
>> Hi,
>> 
>> Just wanted to comment on the "paired" TCGA data:
>> 
>>> On Wed, Feb 5, 2014 at 2:38 PM, Gordon K Smyth <smyth at wehi.edu.au> wrote:
>>> [snip]
>>> I have analysed similar data from TCGA, and the separation is really much
>>> too good.  Furthermore there is little evidence of matching.  It would
>>> appear that the matched normal cells are not really comparable cells to
>> the
>>> tumours.  The matched normal samples may actually be profiles of whole
>>> blood, a cell type which has a radically different expression profile to
>>> epithelial cells.  I really wonder what one can hope to learn about
>> cancer
>>> by comparing epithelial tumours to blood.
>> 
>> There are samples where you have the "correct" matched sample for gene
>> expression, as indeed comparing a solid tumor to "normal blood" to
>> identify changes in gene expression would make very little sense.
>> 
>> You just need to be careful in parsing the sample barcodes to ensure
>> you are working with the correct stuff.
>> 
>> An explanation of the barcode scheme is here:
>> https://wiki.nci.nih.gov/display/TCGA/TCGA+Barcode
>> 
>> You are interested in decoding the "sample" value, which ranges from 01-29.
>> 
>> Explanation is here:
>> 
>> https://tcga-data.nci.nih.gov/datareports/codeTablesReport.htm?codeTable=Sample%20type
>> 
>> There are samples taken from "normal blood" (code = 10), however
>> code=11 are solid tissue normals (presumably from the correct tissue
>> ;-)
>> 
>> The preponderance of blood samples is, I believe, primarily to be used
>> in order to identify somatic mutations -- presumably using the
>> exome-seq from "normal blood" would be cleaner than primary tissue,
>> depending on how close to the tumor the tissue was taken from.
>> 
>> To figure out what was extracted from the "sample" (DNA, RNA, etc),
>> you just decode the "Analyte" part of the barcode:
>> 
>> https://tcga-data.nci.nih.gov/datareports/codeTablesReport.htm?codeTable=portion%20analyte
>> 
>> 
>> HTH,
>> -steve
>> 
>> --
>> Steve Lianoglou
>> Computational Biologist
>> Genentech
>> 
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