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- Views on a 10000000-length Rle subject
- views:
- start end width
- [1] 1 1000 1000 [100 100 100 100 100 100 100 100 100 100 ...]
- [2] 1001 2000 1000 [190 190 190 190 190 190 190 190 190 190 ...]
- [3] 2001 3000 1000 [280 280 280 280 280 280 280 280 280 280 ...]
- [4] 3001 4000 1000 [370 370 370 370 370 370 370 370 370 370 ...]
- [5] 4001 5000 1000 [460 460 460 460 460 460 460 460 460 460 ...]
- ... ... ... ... ...
- [9996] 995001 9996000 9001000 [89650 89650 89650 89650 89650 89650 ...]
- [9997] 996001 9997000 9001000 [89740 89740 89740 89740 89740 89740 ...]
- [9998] 997001 9998000 9001000 [89830 89830 89830 89830 89830 89830 ...]
- [9999] 998001 9999000 9001000 [89920 89920 89920 89920 89920 89920 ...]
- [10000] 999001 10000000 9001000 [90010 90010 90010 90010 90010 90010 ...]
- [1] 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
- library('GenomicRanges')
- # generating data frame
- df=data.frame(chrom=rep('Chr1',100000),start=seq(1,1000000,by=1000),end=seq(1000,10000000,by=1000),strand=rep("+",100000))
- # making GRanges object
- gr=GRanges(seqnames=as.vector(df[,1]),IRanges(start=df[,2],end=df[,3]),strand=df[,4])
- # obtaining coverage using function coverage in the form of RLE object
- gr.cov=coverage(gr)
- # generating views for specific start and end
- gr.views=Views(gr.cov[[1]],start=seq(1,1000000,by=1000),end=seq(1000,10000000,by=1000))
- # putting in temp variable
- d=gr.views
- # this following code calculates the matrix (where each line is 20 points) for 10 lines
- # reduce or increase the number in the outermost sapply loop to increase/decrease the lines to be calculated
- sapply(1:10,function(j)
- sapply(1:20,
- function(i)as.numeric(
- format(
- mean(
- as(d[[j]][(
- seq(0,length(d[[j]]),floor(length(d[[j]])/20))+1)[i]:
- c((seq(0,length(d[[j]]),floor(length(d[[j]])/20)))[
- -length((seq(0,length(d[[j]]),floor(length(d[[j]])/20))))
- ],length(d[[j]]))[i+1]],
- "RangedData")$score),
- digits=2)
- )
- )
- )
- genes <- GRanges(seqnames, IRanges(geneStarts, geneEnds))
- n <- 50L
- starts0 <- Map(function(...) floor(seq(...)), start(genes), end(genes),
- MoreArgs=list(length.out=n + 1L))
- ends <- lapply(starts0, function(x) floor(x)[-1])
- starts <- lapply(starts0, function(x) x[-length(x)])
- v <- Views(gr.cov[[1]], start=unlist(starts), end=unlist(ends))
- split(viewMeans(v), rep(seq_along(genes), each=n))
- > (x <- Rle(c(rep(100, 10), rep(200, 10))))
- numeric-Rle of length 20 with 2 runs
- Lengths: 10 10
- Values : 100 200
- > runValue(x)
- [1] 100 200
- > runLength(x)
- [1] 10 10
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