[BioC] fastest way to keep score when reduce Granges data

[Hervé Pagès]

Hi Jianhong,

It would help enormously if you could send code that we can actually
run. Thanks!

H.


On 02/24/2014 07:53 AM, Ou, Jianhong wrote:
> Hi ALL,
>
> I want to reduce a GRanges data by fixed window size and keep scores after reduce. My code is
>
> .dat <- GRanges("chr1", Iranges(start=1:50, width=2), strand="+", score=Sample(1:50, 50))
> windowSize <- 10
> Grwin <- GRanges("chr1", IRanges(start=(0:5)*windowSize+scale[1]-1,
>                                            width=windowSize), strand="+")
> ol <- findOverlaps(.dat, GRwin)
> ol <- as.data.frame(ol)
> ol <- ol[!duplicated(ol[,1]),]
> .dat <- split(.dat, ol[,2])
> reduceValue <- function(.datReduce){
>                  .datReduceM <- reduce(.datReduce, with.mapping=TRUE)
>                  wid <- width(.datReduce)
>                  .datReduceScore <- .datReduce$value
>                  .datReduceM$score <- sapply(.datReduceM$mapping, function(.idx){
>                      round(sum(.datReduceScore[.idx]*wid[.idx])/sum(wid[.idx]))
>                  })
>                  .datReduceM$mapping <- NULL
>                  .datReduceM
>              }
> .dat <- lapply(.dat, reduceValue)
> .dat <- unlist(GRangesList(.dat))
>
> But the efficiency is very low. What is the best way to keep scores when reduce GRanges data by fixed window size? Thanks for your help.
>
> Yours sincerely,
>
> Jianhong Ou
>
> LRB 670A
> Program in Gene Function and Expression
> 364 Plantation Street Worcester,
> MA 01605
>
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>
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-- 
Hervé Pagès

Program in Computational Biology
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