[BioC] query on variance parameters for RMA

[James W. MacDonald]

I should note that ideally you would first background correct and 
normalize and then do what I showed below:

Dilution <- bg.correct(Dilution, "rma")
Dilution <- normalize(Dilution)

Best,

Jim



On 2/20/2013 11:07 AM, James W. MacDonald wrote:
> Hi Hugh,
>
> It's simple enough to get these data on a probeset-by-probeset basis:
>
> > library(affydata)
> > data(Dilution)
> > medpolish(log2(pm(Dilution, "1007_s_at")))
> 1: 5.536431
> 2: 4.554366
> Final: 4.528792
>
> Median Polish Results (Dataset: "log2(pm(Dilution, "1007_s_at"))")
>
> Overall: 8.618676
>
> Row Effects:
>  1007_s_at1  1007_s_at2  1007_s_at3  1007_s_at4  1007_s_at5  1007_s_at6
> -0.59973136  0.29592898  0.78257437  2.05732074  2.39466709  1.73948500
>  1007_s_at7  1007_s_at8  1007_s_at9 1007_s_at10 1007_s_at11 1007_s_at12
> -0.04027435 -0.06544218 -0.67467511  0.69974913  0.51478816 -0.13604974
> 1007_s_at13 1007_s_at14 1007_s_at15 1007_s_at16
> -0.15326752 -1.90470573 -1.11026444  0.04027435
>
> Column Effects:
>        20A        20B        10A        10B
>  0.5728390 -0.1144511  0.1202443 -0.6362839
>
> Residuals:
>                     20A        20B        10A         10B
> 1007_s_at1  -0.18749394 -0.0465129  0.0407198  0.17422802
> 1007_s_at2   0.13826450  0.0295685 -0.1240571 -0.03039400
> 1007_s_at3   0.07439714 -0.0317711  0.0259779 -0.03874874
> 1007_s_at4  -0.03633972  0.1518405 -0.0181643  0.01217539
> 1007_s_at5   0.07528392 -0.0683772  0.0625840 -0.09050186
> 1007_s_at6   0.00379623  0.0646288 -0.0087639 -0.11399244
> 1007_s_at7   0.04055849 -0.0460984 -0.0440103  0.03802140
> 1007_s_at8  -0.11484593  0.0062318  0.0840782 -0.00705727
> 1007_s_at9  -0.02900022 -0.0267107  0.1319877  0.02588521
> 1007_s_at10 -0.12805213  0.1904883  0.0268966 -0.03288549
> 1007_s_at11 -0.00067114  0.0083397 -0.1167177  0.00067114
> 1007_s_at12  0.02934276 -0.0062318 -0.2409272  0.00540625
> 1007_s_at13  0.00067114  0.0109860 -0.1899048 -0.00067114
> 1007_s_at14 -0.09698507 -0.0145570  0.0087639  0.07814337
> 1007_s_at15 -0.26554742 -0.0828937  0.1806296  0.08206822
> 1007_s_at16  0.03967331  0.1902100 -0.2177162 -0.03967331
>
> And doing it on a whole array isn't that expensive:
>
> > pms <- pm(Dilution, LISTRUE = TRUE)
> > system.time(meds <- lapply(pms, medpolish, trace.iter=FALSE))
>    user  system elapsed
>  62.387   0.033  62.439
>
> Best,
>
> Jim
>
>
>
> On 2/20/2013 7:39 AM, Hugh Shanahan wrote:
>> Hi,
>>        we would like to compute the parameters (i.e, the other 
>> parameters that are computed via the median polish algorithm) that 
>> are computed in the final summarisation step in RMA. In particular, 
>> we'd like to determine the parameter alpha_i that tells us how the 
>> estimate for the expression varies as a function of the probe. I 
>> guess it's possible to open up the relevant C-code and find it there, 
>> but are there are libraries that allow one to do it more easily ? I 
>> saw that affyPLM appears to be doing something similar - is this 
>> where we should be looking ?
>>
>> Many thanks,
>> Hugh
>>
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>

-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099