Hi Adrian,
Try this:
sm$rowmeans<-rowMeans(sm[,2:length(sm)])
sm<-sm[order(sm$Gene,sm$rowmeans,decreasing=TRUE),]
sm[-which(duplicated(sm$Gene)),]
Jim
On Fri, Aug 19, 2016 at 7:33 AM, Adrian Johnson
<oriolebaltim...@gmail.com> wrote:
> Hi Group,
> I have a data matrix sm (dput code given below).
>
> I want to create a data matrix with rows with same variable that have
> higher mean.
>
>> sm
> Gene GSM529305 GSM529306 GSM529307 GSM529308
> 1 A1BG 6.57 6.72 6.83 6.69
> 2 A1CF 2.91 2.80 3.08 3.00
> 3 A2LD1 5.82 7.01 6.62 6.87
> 4 A2M 9.21 9.35 9.32 9.19
> 5 A2M 2.94 2.50 3.16 2.76
> 6 A4GALT 6.86 5.75 6.06 7.04
> 7 A4GNT 3.97 3.56 4.22 3.88
> 8 AAA1 3.39 2.90 3.16 3.23
> 9 AAAS 8.26 8.63 8.40 8.70
> 10 AAAS 6.82 7.15 7.33 6.51
>
> For example in rows 4 and 5 have same variable Gene A2M. I want to
> select only row that has higher mean. I wrote the following code that
> gives me duplicate rows with higher mean but I cannot properly write
> the result. Could someone help. Thanks
>
> ugns <- unique(sm$Gene)
>
> exwidh = c()
>
> for(i in 1:length(ugns)){
> k = ugns[i]
> exwidh[i] <-
> sm[names(sort(rowMeans(sm[which(sm[,1]==k),2:ncol(sm)]),decreasing=TRUE)[1]),]
> }
>
>
>
>
>
> structure(list(Gene = c("A1BG", "A1CF", "A2LD1", "A2M", "A2M",
> "A4GALT", "A4GNT", "AAA1", "AAAS", "AAAS"), GSM529305 = c(6.57,
> 2.91, 5.82, 9.21, 2.94, 6.86, 3.97, 3.39, 8.26, 6.82), GSM529306 = c(6.72,
> 2.8, 7.01, 9.35, 2.5, 5.75, 3.56, 2.9, 8.63, 7.15), GSM529307 = c(6.83,
> 3.08, 6.62, 9.32, 3.16, 6.06, 4.22, 3.16, 8.4, 7.33), GSM529308 = c(6.69,
> 3, 6.87, 9.19, 2.76, 7.04, 3.88, 3.23, 8.7, 6.51)), .Names = c("Gene",
> "GSM529305", "GSM529306", "GSM529307", "GSM529308"), row.names = c(NA,
> 10L), class = "data.frame")
>
> ______________________________________________
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