# From Mark Robinson, 31 October 2010
# Yep, pretty straightforward extension -- basically replace your 'windows' RangedData object with something containing the TSSs of interest.

#library(rtracklayer)
#session <- browserSession("ucsc")
#q <- ucscTableQuery(session, "ensGene", range="hg18")
#ensGene <- getTable(q)
# need column names to match these
#anno <- data.frame(chr=ensGene$chrom, strand=ensGene$strand, start=ensGene$txStart, end=ensGene$txEnd, name=ensGene$name)
#head(anno)

library(rtracklayer)
session <- browserSession("UCSC")
genome(session) <- "hg18"
#trackNames(session) ## list the track names
q <- ucscTableQuery(session, "knownGene")
knownGene <- getTable(q)
anno <- data.frame(chr=knownGene$chrom, strand=knownGene$strand, start=knownGene$txStart, end=knownGene$txEnd, name=knownGene$name)

# You have other choices than "ensGene" and of course you can construct this from 
# sucking in a flat file from disk.  'rtracklayer' allows you to suck any table 
# from UCSC, which can be quite useful for other purposes too.

# Then, all you do is replace your annotationBlocksCounts() call with annotationCounts() 
# ... the former uses start-end (like 1kb regions genome-wide), whereas the 
# latter will do the -1500 to +1000 calculation, obeying the strand information:

#[...]
fragSize<-200
counts <- annotationCounts(grl, anno, bpUp=1500, bpDown=1000, seqLen=fragSize, verbose=TRUE)
head(counts)




session <- browserSession("UCSC")
genome(session) <- "hg18"
trackNames(session) ## list the track names
q <- ucscTableQuery(session, "knownGene")
knownGene <- getTable(q)
anno <- data.frame(chr=knownGene$chrom, strand=knownGene$strand, start=knownGene$txStart, end=knownGene$txEnd, name=knownGene$name)


## choose the Conservation track for a portion of mm9 chr1
query <- ucscTableQuery(session, "Conservation",
                        GenomicRanges(57795963, 57815592, "chr12"))
## list the table names
tableNames(query)
## get the phastCons30way track
tableName(query) <- "phastCons30way"
## retrieve the track data
track(query)
## get a data.frame summarizing the multiple alignment
tableName(query) <- "multiz30waySummary"
getTable(query)

genome(session) <- "hg18"
query <- ucscTableQuery(session, "snp129",
                        names = c("rs10003974", "rs10087355", "rs10075230"))
getTable(query)
## End(Not run)