[BioC] Experimental design for RNA-Seq
Steve Lianoglou
mailinglist.honeypot at gmail.com
Fri May 28 22:37:42 CEST 2010
Hi Yifang,
Out of curiosity, what does this have to do with "Experimental design
for RNA-Seq"?
Thanks,
-steve
On Fri, May 28, 2010 at 10:08 AM, Tan, Yifang <Yifang.Tan at nrc-cnrc.gc.ca> wrote:
> Hello list:
>
> I post my questions here again to get help about my experiment design, as I am new and have been struggling with my analysis. I could not find the example design from LIMMA user's guide.
>
>
> The first part of my experiment consists of a loop design to compare the gene expression of at different development stages (10DAP, 22DAP and 35DAP, day-after-pollenization) of the same Brassica line. The purpose is to see the differentiation at different development stages of the same single line. Pooled sample of the same line was used for each stage and treated as biological replicates. I have dye swap plus two technical replicates. The target file consists of three or four columns as file name, Cy3 and Cy5. here is the target file:
> FileName Cy3 Cy5
> AT Oligo 02.11.02.176.gpr.fixed 10DAP 22DAP
> AT Oligo 02.11.02.177.gpr.fixed 22DAP 10DAP
> AT Oligo 02.11.02.178.gpr.fixed 22DAP 10DAP
> AT Oligo 02.11.02.179.gpr.fixed 10DAP 22DAP
> AT Oligo 02.11.02.180.gpr.fixed 22DAP 35DAP
> AT Oligo 02.11.02.181.gpr.fixed 22DAP 35DAP
> AT Oligo 02.11.02.182.gpr.fixed 35DAP 22DAP
> AT Oligo 02.11.02.183.gpr.fixed 35DAP 22DAP
> AT Oligo 02.11.02.184.gpr.fixed 10DAP 35DAP
> AT Oligo 02.11.02.185.gpr.fixed 10DAP 35DAP
> AT Oligo 02.11.02.186.gpr.fixed 35DAP 10DAP
> AT Oligo 02.11.02.187.gpr.fixed 35DAP 10DAP
>
> This experiment is very similar to the design in LIMMA User's Guide section 7.4, except I have technical replicates. From the Guide, should I have to use one sample like "10DAP" as reference, or any sample for a reference? My goal is to see which genes are differentiated from 10DAP, 22DAP and 35 DAP. How do I get the results of: 1)which genes are consistently up/down-regulated across the 3 stages? 2) which genes are up-down-regulated at each development stage?
>
> The second part of my experiment is:
> FileName DPA Cy3 Cy5
> 2009-07-10-atq3.7.3.145-15.gpr 15DPA WT MUTANT
> 2009-07-15-atq3.7.3.146-15.gpr 15DPA MUTANT WT
> 2009-07-15-atq3.7.3.147-15.gpr 15DPA MUTANT WT
> 2009-07-15-atq3.7.3.148-15.gpr 15DPA WT MUTANT
> 2009-07-15-atq3.7.3.149-15.gpr 15DPA WT MUTANT
> 2009-07-17-atq3.7.3.151-20.gpr 20DPA MUTANT WT
> 2009-07-17-atq3.7.3.152-20.gpr 20DPA WT MUTANT
> 2009-07-17-atq3.7.3.153-25.gpr 25DPA MUTANT WT
> 2009-07-17-atq3.7.3.154-25.gpr 25DPA WT MUTANT
> 2009-07-17-atq3.7.3.155-10.gpr 10DPA MUTANT WT
> 2009-07-17-atq3.7.3.156-10.gpr 10DPA WT MUTANT
> 2009-07-17-atq3.7.3.157-30.gpr 30DPA MUTANT WT
> 2009-07-17-atq3.7.3.158-30.gpr 30DPA WT MUTANT
> 2009-07-21-atq3.7.3-159-10.gpr 10DPA MUTANT WT
> 2009-07-21-atq3.7.3-160-20.gpr 20DPA MUTANT WT
> 2009-07-21-atq3.7.3-164-25.gpr 25DPA MUTANT WT
> 2009-07-21-atq3.7.3-256-30.gpr 30DPA MUTANT WT
> 2009-07-22-atq3.7.3-115-10.gpr 10DPA MUTANT WT
> 2009-07-22-atq3.7.3-116-20.gpr 20DPA MUTANT WT
> 2009-07-22-atq3.7.3-117-25.gpr 25DPA MUTANT WT
> 2009-07-22-atq3.7.3-118-30.gpr 30DPA MUTANT WT
> 2009-07-22-atq3.7.3-119-10.gpr 10DPA WT MUTANT
> 2009-07-22-atq3.7.3-120-20.gpr 20DPA WT MUTANT
> 2009-07-22-atq3.7.3-124-25.gpr 25DPA WT MUTANT
> 2009-07-22-atq3.7.3-125-30.gpr 30DPA WT MUTANT
>
> The target file consists of four columns as file name, time, Cy3 and Cy5. This is a time course experiment. Again I want to see the expression differentiation across the stage (10, 15 20, 25 and 30DAP).
> 1)Can I split the analysis into five sub-groups by time course (say, 10, 15, 20 25 and 30DPA separately) instead of a whole?
> 2)If I split the 25 slides into 5 sub-experiments, my feeling is the variance and normalization would be different from each other. Is this correct?
> 3)How do I prepare the biolrep as I treated the pooled sample as biological replicates.?
>
> I would appreciate very much if you could give me some suggestions on these questions. Thanks a lot!
>
>
> Yifang
>
> ________________________________________
> From: bioconductor-bounces at stat.math.ethz.ch [bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Naomi Altman [naomi at stat.psu.edu]
> Sent: Friday, May 28, 2010 9:17 AM
> To: michael watson (IAH-C); bioconductor
> Subject: Re: [BioC] Experimental design for RNA-Seq
>
> At least from the stat theory point of view, the best design is equal
> numbers of biological samples (the more the better) for each
> condition and no technical reps.
>
> So far, there is little indication that there are flowcell
> effects. However, to be on the safe side, you should use the
> blocking principle - as much as possible distribute the reps from the
> different conditions across different flow cells (unless the whole
> experiment fits on a single flow cell).
>
> --Naomi
>
> At 04:02 AM 5/28/2010, michael watson (IAH-C) wrote:
>>Dear List
>>
>>I'm about to design a simple experiment (knockout vs wild-type) and
>>we plan to use RNA-Seq. We're interested in gene expression, for
>>mRNA and microRNAs in particular, and calculating stats for
>>differential expression.
>>
>>I'm aware of DEseq, DEGseq and edgeR. I wanted to ask those who
>>have a lot of experience of this type of analysis if they have any
>>advice for experimental design, in particular, the number of
>>replicates they have used and why (I was planning on going for all
>>biological replicates, no technical).
>>
>>Thanks
>>Mick
>>
>>
>>
>> [[alternative HTML version deleted]]
>>
>>_______________________________________________
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>
> Naomi S. Altman 814-865-3791 (voice)
> Associate Professor
> Dept. of Statistics 814-863-7114 (fax)
> Penn State University 814-865-1348 (Statistics)
> University Park, PA 16802-2111
>
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--
Steve Lianoglou
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
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