[BioC] rtrackalyer too slow?

[Wu, Xiwei]

Hi,

I recently started to use rtracklayer, so I am still new to it. Here I
am trying to get conservation score for a number of genomic loci. The
code below works, but extremely slow. I found it took several seconds to
get one done, so it becomes impossible when it gets to over 1000 sites.
What is missing here? Is there any alternative way to get this done? Any
help will be highly appreciated.

> head(dum)
   chr     start       end
1 chr1   7233717   7233734
2 chr1  48238854  48238870
3 chr1 175465350 175465366
4 chr1 206969193 206969209
5 chr1 214532960 214532976
6 chr1 216671605 216671622

> getConserv <- function(genome="hg18", data) {
+ 	session <- browserSession()
+ 	result <- numeric()
+ 	genome(session) <- genome
+ 	for (i in 1:nrow(data)) {
+ 		query <- ucscTableQuery(session,
"cons44way",GenomicRanges(data[i,"start"]), data[i, "end"],
data[i, "chr"]))
+ 		tableName(query) <- "phyloP44wayPlacMammal"
+ 		a <- track(query)
+ 		result[i] <- mean(score(a))
+ 	}
+ 	return(result)
+ }
> b <- getConserv(data=dum)
> head(b)
[1] -1.76180289 -0.28795906  0.05897465 -0.23541347 -0.26477671
0.29019661


> sessionInfo()
R version 2.11.0 Under development (unstable) (2010-01-28 r51065) 
x86_64-unknown-linux-gnu 

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=C              LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base


other attached packages:
 [1] rtracklayer_1.6.0                  RCurl_1.3-1

 [3] bitops_1.0-4.1                     smRNAseq_1.0

 [5] time_1.0
BSgenome.Hsapiens.UCSC.hg18_1.3.16
 [7] ShortRead_1.5.11                   lattice_0.18-3

 [9] BSgenome_1.15.4                    Biostrings_2.15.19

[11] IRanges_1.5.36                    

loaded via a namespace (and not attached):
[1] Biobase_2.7.4 grid_2.11.0   hwriter_1.1   tools_2.11.0  XML_2.6-0   

Xiwei


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