Dear BioStars,

I have a genomic ranges (GR) list object called "lgr.test" and would like to simply add several columns to its metadata. How would I do that? I have a list of numeric vectors "lvec.test" of the same lengths as the GRs in lgr.test.

Thank you!

> summary(lvec.test)

      Length Class  Mode   
chr1  589    -none- numeric
chr2  790    -none- numeric
chr3  482    -none- numeric
chr4  681    -none- numeric
chr5  698    -none- numeric
chr6  492    -none- numeric
chr7  713    -none- numeric
chr8  489    -none- numeric
chr9  590    -none- numeric
chr10 521    -none- numeric
chr11 853    -none- numeric
chr12 395    -none- numeric
chr13 373    -none- numeric
chr14 358    -none- numeric
chr15 388    -none- numeric
chr16 340    -none- numeric
chr17 465    -none- numeric
chr18 287    -none- numeric
chr19 357    -none- numeric

> summary(lgr.test)

      Length Class   Mode
chr1  589    GRanges S4  
chr2  790    GRanges S4  
chr3  482    GRanges S4  
chr4  681    GRanges S4  
chr5  698    GRanges S4  
chr6  492    GRanges S4  
chr7  713    GRanges S4  
chr8  489    GRanges S4  
chr9  590    GRanges S4  
chr10 521    GRanges S4  
chr11 853    GRanges S4  
chr12 395    GRanges S4  
chr13 373    GRanges S4  
chr14 358    GRanges S4  
chr15 388    GRanges S4  
chr16 340    GRanges S4  
chr17 465    GRanges S4  
chr18 287    GRanges S4  
chr19 357    GRanges S4

Ok, a for loop works (see below), but if some GR gurus see this, please save me from my ignorance and tell me how to do this using standard GR functions (Map , endoapply, mendoapply, Reduce). The for solution is fast enough but doesn't use the names of the objects in the lists, so it depends entirely on their order.

Cheers!

For solution:

for (i in 1:length(lgr.test)) { values(lgr.test[[i]])$NEW<-lvec.test[[i]] }

One lazy way is to use the merge function:

merged <- merged(lvec.test, lgr.test, by='row.names')

This won't give you the final product, it will give you something like:

Row.names Length.x Class.x Mode.x Length.y Class.y Mode.y

chr1 589 NA numeric 589 GRanges S4 ...

You can then clean it up and drop the columns you don't like, for example by

rownames(merged) <- merged[,1]

merged <- merged[-1]

merged <- merged[-2] etc.