[BioC] limma: NA coefficients due to missing values

[Shi, Tao]

Thank you very much, Gordon!  That will do.  I also just saw one of your older posts ( https://stat.ethz.ch/pipermail/bioconductor/2007-October/019889.html  ).   It clears things up even better.

Tao



>________________________________
> From: Gordon K Smyth <smyth at wehi.EDU.AU>
>To: "Shi, Tao" <shidaxia at yahoo.com> 
>Cc: "bioconductor at r-project.org" <bioconductor at r-project.org> 
>Sent: Tuesday, May 14, 2013 4:34 PM
>Subject: Re: limma: NA coefficients due to missing values
> 
>
>Dear Tao,
>
>The coefficients for days 2-4 have already been estimated without NAs, see 
>fit1$coef[,11:13].
>
>Using contrasts will introduce NAs unless you remove the missing patient 
>effect.  This can be done by,
>
>  > fit.day <- fit1[,11:13]
>  > colnames(fit.day)
>  [1] "day2" "day3" "day4"
>  > head(fit.day$coef)
>            day2        day3        day4
>  [1,]  0.1018951  0.14728872  0.01348279
>  [2,]  0.8222967  0.95183289  0.02500825
>  [3,]  0.6601298 -0.27436185  0.16624044
>  [4,] -0.7082047  0.04495111  0.25636112
>  [5,] -0.0628469 -0.04033322 -0.59622820
>  [6,] -0.0296513 -0.31283864  0.14225534
>
>Then you can happily take as many contrasts as you like of the day 
>effects, using fit3 instead of fit1.  For example:
>
>   cont.mat <- makeContrasts(day3-day2, levels=colnames(fit.day))
>
>Best wishes
>Gordon
>
>---------------------------------------------
>Professor Gordon K Smyth,
>Bioinformatics Division,
>Walter and Eliza Hall Institute of Medical Research,
>1G Royal Parade, Parkville, Vic 3052, Australia.
>http://www.statsci.org/smyth
>
>On Tue, 14 May 2013, Shi, Tao wrote:
>
>> Dear Gordon and list,
>
>Please see the example below and R output.  The coefficients for Probe #2 
>can't be estimated b/c patient 10 data were missing.  But in fact, they 
>can be estimated just using data from other 9 patients.  Is there a way to 
>tell limma to do that?
>
>Thanks!
>
>Tao
>
>
>
>library(limma)
>dat <- matrix(rnorm(400), ncol=40)
>ptID <- factor(rep(1:10, each=4))
>day <- factor(rep(1:4,10))
>dat[2, 37:40] <- NA
>design <- model.matrix(~0+ptID+day)
>contrast.matrix <- makeContrasts(day2=day2, day3=day3,day4=day4, levels=design)
>fit1 <- lmFit(dat, design=design)
>fit2 <- eBayes(contrasts.fit(fit1, contrast.matrix))
>
>
>Warning message:
>Partial NA coefficients for 1 probe(s) 
>> fit2$p.value
>       Contrasts
>              day2      day3      day4
>   [1,] 0.40027892 0.4917185 0.0387787
>   [2,]         NA        NA        NA
>   [3,] 0.05281279 0.4914354 0.6088744
>   [4,] 0.72648798 0.6816108 0.7551084
>   [5,] 0.35528206 0.7962423 0.9827632
>   [6,] 0.09552328 0.3458950 0.1327465
>   [7,] 0.76918217 0.5945065 0.4511735
>   [8,] 0.40125232 0.1066155 0.1269416
>   [9,] 0.56923379 0.2981261 0.9285374
>  [10,] 0.04276991 0.4693320 0.3139434
>> fit2$coef
>       Contrasts
>              day2       day3         day4
>   [1,]  0.3737307  0.3054398  0.921284513
>   [2,]         NA         NA           NA
>   [3,] -0.8628711 -0.3056396 -0.227256710
>   [4,] -0.1553395  0.1821986  0.138509886
>   [5,] -0.4107858  0.1146613 -0.009593154
>   [6,]  0.7421089 -0.4188821  0.668951727
>   [7,] -0.1303084 -0.2364268 -0.334736056
>   [8,] -0.3729581 -0.7182350 -0.679192601
>   [9,]  0.2528092  0.4624636  0.039823091
>  [10,] -0.9030535 -0.3214420 -0.447554386
>
>
>> sessionInfo()
>R version 3.0.0 (2013-04-03)
>Platform: x86_64-w64-mingw32/x64 (64-bit)
>
>locale:
>[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
>[5] LC_TIME=English_United States.1252   
>
>attached base packages:
>[1] grDevices datasets  splines   graphics  stats     tcltk     utils     methods   base    
>
>other attached packages:
>[1] limma_3.16.3    svSocket_0.9-55 TinnR_1.0-5     R2HTML_2.2.1    Hmisc_3.10-1.1  survival_2.37-4
>
>loaded via a namespace (and not attached):
>[1] cluster_1.14.4  grid_3.0.0      lattice_0.20-15 svMisc_0.9-69   tools_3.0.0   
>>
>
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