CITPP correction

gistfile1.r

## The script [I'd edited] used to be;
#-----------------------------------------
cur.marker.id <- cbind(cur.marker.id, abs((cur.gene$startcoord+cur.gene$endcoord)/2 - cur.marker.id$chr_pos))
names(cur.marker.id)[6] <- c("dis_from_cur_gene")
cur.marker.id <- which.min(cur.marker.id$dis_from_cur_gene) # cur.marker.id is now the row in the cur.marker.id matrix which represents the marker closest to the current gene

## having found the closes cna, we assign it's values to the cur.marker
cur.marker <- cna[,cur.marker.id]
#-----------------------------------------

## Which works for chromosome 1 because cur.marker.id ends up being a number from 1 to the number of chr1 markers. 
## However, when we get to chromosome 2, cur.marker.id gets set to a number between 1 and number of chr2 markers, which still indexes into the cna[] array into
## chromosome 1 markers (there are fewer chr2 markers than chr1 markers).

## Easy fix is just;

#-----------------------------------------
cur.marker.id <- cbind(cur.marker.id, abs((cur.gene$startcoord+cur.gene$endcoord)/2 - cur.marker.id$chr_pos))
names(cur.marker.id)[6] <-c("dis_from_cur_gene")
cur.marker.id <- cur.marker.id[which.min(cur.marker.id$dis_from_cur_gene), ] # so now we set cur.marker.id to the full vector containing all the info on the marker we want to select

## having found the closes cna, we assign it's values to the cur.marker
cur.marker <- cna[,cur.marker.id$marker_id] # we can pull the correct marker from cna via its $marker_id field, which is for this specific purpose!
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