Hi,
May be this helps:
dat1 <- read.table(text="Sample Genotype Region
sample1 A Region1
sample1 B Region1
sample1 A Region1
sample2 A Region1
sample2 A Region1
sample3 A Region1
sample4 B Region1",sep="",header=TRUE,stringsAsFactors=FALSE)
library(plyr)
unique(ddply(dat1,.(Sample),mutate, Genotype=if(length(unique(Genotype))>1)
{"E"} else Genotype))
dat2 <- read.table(text="Sample Genotype Region
sample1 A Region1
sample1 B Region1
sample1 A Region1
sample2 A Region1
sample2 A Region1
sample3 A Region1
sample4 B Region1
sample1 A Region2
sample1 B Region2
sample1 A Region2
sample2 A Region2
sample2 A Region2",sep="",header=TRUE,stringsAsFactors=FALSE)
unique(ddply(dat2,.(Region,Sample),mutate,
Genotype=if(length(unique(Genotype))>1) {"E"} else Genotype))
#or
aggregate(Genotype~.,data=dat2,function(x) x <- if(length(unique(x))>1) "E"
else unique(x))
A.K.
I would like to transform this data:
Sample Genotype Region
sample1 A Region1
sample1 B Region1
sample1 A Region1
sample2 A Region1
sample2 A Region1
sample3 A Region1
sample4 B Region1
In that format, tagging with "E" samples with more than one genotype and
unifying samples with the same genotype 2 times:
Sample Genotype Region
sample1 E Region1
sample2 A Region1
sample3 A Region1
sample4 B Region1
I have one list with many regions (Region1 - Regionx). It is possible to do in
R software? Thanks a lot.
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