Hello,
Let me give it a try.
This last post made it clear, I hope. I have two interpretations of your
problem.
1. 'l1' only has three columns, corresponding to clusters (genotypes) XX,
XY and YY, and 'l2' has one less column, corresponding to the midpoints
between their closest genotype cluster.
2. 'l1' can have any number of columns and 'l2' is the same as above,
i.e., has one less column.
In any case, the result is not the pairwise products of all possible
combinations of columns of 'l1' and 'l2' matrices, but only those at a
certain distance. In this case, fun2 below is more general.
fun1<- function(x, y){
cbind((x[, 1] + y[, 1])/2, (x[, 2] + y[, 1])/2,
(x[, 2] + y[, 2])/2, (x[, 3] + y[, 2])/2)
}
fun2<- function(x, y){
midpoint<- function(i, j) (x[, i] + y[, j])/2
colx<- ncol(x)
res<- matrix(nrow = nrow(x), ncol = 2*colx - 2)
k<- 1
res[, k]<- midpoint(1, 1)
for(cx in seq_len(colx)[-c(1, colx)])
for(dist in 1:0)
res[, k<- k + 1]<- midpoint(cx, cx - dist)
res[, k + 1]<- midpoint(colx, colx - 1)
res
}
lapply(seq_len(length(l1)), function(i) fun1(l1[[i]], l2[[i]]))
lapply(seq_len(length(l1)), function(i) fun2(l1[[i]], l2[[i]]))
If I'm wrong, sorry for the mess.
Rui Barradas
Em 25-05-2012 11:00, r-help-requ...@r-project.org escreveu:
Date: Thu, 24 May 2012 15:37:51 -0700 (PDT)
From: Hans Thompson<hans.thompson1@gmail.**com<hans.thomps...@gmail.com>
To:r-help@r-project.org
Subject: Re: [R] applying cbind (or any function) across all
components in a list
Message-ID:<1337899071674-**4631260.p...@n4.nabble.com<1337899071674-4631260.p...@n4.nabble.com>
Content-Type: text/plain; charset=us-ascii
The function I am giving for context is cbind. Are you asking how I would
like to apply the answer to my question?
I am trying to take the results of a Fluidigm SNP microarray, organized by
assay into a list (each component is the results of one assay), find
coordinate midpoints ([1,] and [2,] of my XX, XY, and YY clusters (these
are
genotypes) and is represented by l1. l2 is the midpoint between XX/XY and
XY/YY although I did not give this in my example for simplicity, and I am
now trying to find the midpoint between these new midpoints and their
closest genotype clusters. This is represented as
cbind((l1[[1]][,1]+l2[[1]][,1]**)/2, (l1[[1]][,2]+l2[[1]][,1])/2,
(l1[[1]][,2]+l2[[1]][,2])/2, (l1[[1]][,3]+l2[[1]][,2])/2)
but only works for one assay in the list of 96. I want to apply this to
the
entire list. My entire code so far is:
## OPEN .CSV and ORGANIZE BY ASSAY
file=""
{
rawdata<- read.csv(file, skip = 15)
OrgAssay<- split(rawdata, rawdata$Assay)
## RETURN MIDPOINTS FOR EACH CLUSTER WITHOUT NO CALLS
#for loop
ClustMidPts<-list()
for(locus in 1:length(names(OrgAssay))){
ClustMidPts[[locus]]<-t(cbind(**tapply(OrgAssay[[locus]][,"**
Allele.X.1"],
OrgAssay[[locus]][,"Final"], mean,na.rm=T),
tapply(OrgAssay[[locus]][,"**Allele.Y.1"],
OrgAssay[[locus]][,"Final"], mean,na.rm=T)))}
names(ClustMidPts)=names(**OrgAssay)
## CREATE CLUSTER-CLUSTER MIDPOINT
#for loop
ClustClustMidPts<- list()
for(locus in 1:length(names(ClustMidPts))){
ClustClustMidPts[[locus]]<-
cbind(XXYX=(ClustMidPts[[**locus]][,"XX"]+ClustMidPts[[**
locus]][,"YX"])/2,
YXYY=(ClustMidPts[[locus]][,"**YX"]+ClustMidPts[[locus]][,"**YY"])/2)
}
names(ClustClustMidPts)=names(**ClustMidPts)
Please also let me know how I messed up the formatting because it shows up
fine in gmail even when I post on Nabble. How did I assume you were using
Nabble? Is this topic included in the posting guide?
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