Hi Cyrus,
Try this:
pcr<-data.frame(Ct=runif(66,10,20),Gene=rep(LETTERS[1:22],3),
Type=rep(c("Std","Unkn"),33),Rep=rep(1:3,each=22))
testagg<-aggregate(pcr$Ct,c(pcr["Gene"],pcr["Type"],pcr["Rep"]),
FUN=function(x){c(mean(x), sd(x), sd(x)/sqrt(sd(x)))})
nxcol<-dim(testagg$x)[2]
newxs<-paste("x",1:nxcol,sep="")
for(col in 1:nxcol)
testagg[[newxs[col]]]<-testagg$x[,col]
testagg$x<-NULL
Jim
On Thu, Mar 28, 2019 at 12:39 PM cir p via R-help <r-help@r-project.org> wrote:
>
> Dear users,
> i am trying to summarize data using "aggregate" with the following command:
>
> aggregate(pcr$Ct,c(pcr["Gene"],pcr["Type"],pcr["Rep"]),FUN=function(x){c(mean(x),
> sd(x), sd(x)/sqrt(sd(x)))})
>
> and the structure of the resulting data frame is
>
> 'data.frame': 66 obs. of 4 variables:
> $ Gene: Factor w/ 22 levels "14-3-3e","Act5C",..: 1 2 3 4 5 6 7 8 9 10 ...
> $ Type: Factor w/ 2 levels "Std","Unkn": 2 2 2 2 2 2 2 2 2 2 ...
> $ Rep : int 1 1 1 1 1 1 1 1 1 1 ...
> $ x : num [1:66, 1:3] 16.3 16.7 18.2 17.1 18.6 ...
>
> The actual data is "bundled" in a matrix $x of the data frame. I would like
> to have the columns of this matrix as individual numeric columns in the same
> data frame instead of a matrix, but cant really figure it out how to do this
> in an efficient way. Could someone help me with the construction of this?
>
> Thanks a lot,
>
> Cyrus
>
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