I tried to follow your instructions but it did not work. I was playing around with ',' and ')' but ... This is the version "the function I was applying before": > foo <- split ahesc.ox.gr, seqnamesahesc.ox.gr)) > chrMeans <- seqapply(foo, function(x, y) + { + starts = seq(1, y, 300) + ends = starts + 299 + mean(Views(start = starts, end = ends, subject = Gcoverage[[x]]), na.rm = TRUE) + }, names(chrLengths), chrLengths), use.names = FALSE) Unexpected ',' in: " mean(Views(start = starts, end = ends, subject = Gcoverage[[x]]), na.rm = TRUE) }, names(chrLengths), chrLengths)," Thanks Hermann > chrLengths chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 249250621 243199373 198022430 191154276 180915260 171115067 159138663 146364022 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 141213431 135534747 135006516 133851895 115169878 107349540 102531392 90354753 chr17 chr18 chr19 chr20 chr21 chr22 chrX chrY 81195210 78077248 59128983 63025520 48129895 51304566 155270560 59373566 > Gcoverage SimpleRleList of length 24 $chr1 integer-Rle of length 249240530 with 240162 runs Lengths: 10143 210 87 23 225169 ... 18950 172 493 106 Values : 0 1 0 1 0 ... 0 1 0 1 $chr10 integer-Rle of length 135524700 with 106386 runs Lengths: 95292 22 24357 696 1746 ... 55 798 34 50302 102 Values : 0 1 0 1 0 ... 1 0 1 0 1 $chr11 integer-Rle of length 134945522 with 106676 runs Lengths: 175567 185 92 53 14911 ... 152 262 770 94 Values : 0 1 0 1 0 ... 0 1 0 1 $chr12 integer-Rle of length 133813408 with 99614 runs Lengths: 66672 284 6973 159 895 ... 98 4299 165 1939 33 Values : 0 1 0 1 0 ... 1 0 1 0 1 $chr13 integer-Rle of length 115109694 with 66106 runs Lengths: 19525839 16 774 72 ... 616 2458 105 Values : 0 1 0 1 ... 1 0 1 ... <19 more elements > 2013/1/20 Tim Triche, Jr. <tim.triche@gmail.com> > foo <- split( GRanges, seqnames(GRanges) ) > byChr <- seqapply( foo, function you were applying before ) > > --t > > On Jan 20, 2013, at 12:45 PM, Hermann Norpois <hnorpois@googlemail.com> > wrote: > > > I am sorry, but I still have a problem. With your syntax I get a vector > > that is going over all chromosomes. How do I get , for instance separate > > vectors for each chromosomes? > > Thanks > > > > 2013/1/17 Hermann Norpois <hnorpois@googlemail.com> > > > >> Hello, > >> > >> I would like to transform a GRange-object into something with density > >> information related of bins, e.g. 1 bin=200bps. So it starts at > poistion 1 > >> etc ... > >> That means (according to testset.gr): > >> bin 1 0 > >> bin 2 0 > >> ... > >> bin 50 0 > >> bin 51 0.28 #10000-10200 => (200-144)/200 > >> bin 52 0.765 #10200-10400 => 153/200 > >> ... > >> etc > >> according to testset.gr (see below). > >> > >> How does it work? Is there a special function? > >> Thanks > >> Hermann > >> > >> > >>> testset.gr > >> GRanges with 20 ranges and 0 metadata columns: > >> seqnames ranges strand > >> <rle> <iranges> <rle> > >> [1] chr1 [ 10144, 10353] * > >> [2] chr1 [ 10441, 10463] * > >> [3] chr1 [235633, 235766] * > >> [4] chr1 [237717, 237895] * > >> [5] chr1 [521444, 521624] * > >> [6] chr1 [540609, 540786] * > >> [7] chr1 [564495, 564672] * > >> [8] chr1 [565254, 566081] * > >> [9] chr1 [566537, 567272] * > >> ... ... ... ... > >> [12] chr1 [569610, 570190] * > >> [13] chr1 [601057, 601196] * > >> [14] chr1 [713227, 713475] * > >> [15] chr1 [752533, 752578] * > >> [16] chr1 [752654, 752695] * > >> [17] chr1 [754405, 754539] * > >> [18] chr1 [755336, 755918] * > >> [19] chr1 [756027, 756458] * > >> [20] chr1 [756793, 756843] * > >> --- > >> seqlengths: > >> chr1 chr10 chr11 chr12 chr13 chr14 ... chr6 chr7 chr8 chr9 chrX > >> chrY > >> NA NA NA NA NA NA ... NA NA NA NA > >> NA NA > >>> dput testset.gr) > >> new("GRanges" > >> , seqnames = new("Rle" > >> , values = structure(1L, .Label = c("chr1", "chr10", "chr11", > "chr12", > >> "chr13", > >> "chr14", "chr15", "chr16", "chr17", "chr18", "chr19", "chr2", > >> "chr20", "chr21", "chr22", "chr3", "chr4", "chr5", "chr6", "chr7", > >> "chr8", "chr9", "chrX", "chrY"), class = "factor") > >> , lengths = 20L > >> , elementMetadata = NULL > >> , metadata = list() > >> ) > >> , ranges = new("IRanges" > >> , start = c(10144L, 10441L, 235633L, 237717L, 521444L, 540609L, > >> 564495L, > >> 565254L, 566537L, 567450L, 568038L, 569610L, 601057L, 713227L, > >> 752533L, 752654L, 754405L, 755336L, 756027L, 756793L) > >> , width = c(210L, 23L, 134L, 179L, 181L, 178L, 178L, 828L, 736L, > 453L, > >> 545L, 581L, 140L, 249L, 46L, 42L, 135L, 583L, 432L, 51L) > >> , NAMES = NULL > >> , elementType = "integer" > >> , elementMetadata = NULL > >> , metadata = list() > >> ) > >> , strand = new("Rle" > >> , values = structure(3L, .Label = c("+", "-", "*"), class = "factor") > >> , lengths = 20L > >> , elementMetadata = NULL > >> , metadata = list() > >> ) > >> , elementMetadata = new("DataFrame" > >> , rownames = NULL > >> , nrows = 20L > >> , listData = structure(list(), .Names = character(0)) > >> , elementType = "ANY" > >> , elementMetadata = NULL > >> , metadata = list() > >> ) > >> , seqinfo = new("Seqinfo" > >> , seqnames = c("chr1", "chr10", "chr11", "chr12", "chr13", "chr14", > >> "chr15", > >> "chr16", "chr17", "chr18", "chr19", "chr2", "chr20", "chr21", > >> "chr22", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8", "chr9", > >> "chrX", "chrY") > >> , seqlengths = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, > >> NA_integer_, > >> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, > >> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, > >> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, > >> NA_integer_, NA_integer_, NA_integer_, NA_integer_) > >> , is_circular = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, > >> NA, NA, > >> NA, NA, NA, NA, NA, NA, NA, NA, NA) > >> , genome = c(NA_character_, NA_character_, NA_character_, > >> NA_character_, > >> NA_character_, NA_character_, NA_character_, NA_character_, > NA_character_, > >> NA_character_, NA_character_, NA_character_, NA_character_, > NA_character_, > >> NA_character_, NA_character_, NA_character_, NA_character_, > NA_character_, > >> NA_character_, NA_character_, NA_character_, NA_character_, > NA_character_ > >> ) > >> ) > >> , metadata = list() > >> ) > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor@r-project.org > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > [[alternative HTML version deleted]]

Hi, This looks very much like this other thread (subject: GRanges averaging) from last October: https://stat.ethz.ch/pipermail/bioconductor/2012-October/048338.html Actually Hermann's "density" problem can be seen as a particular case of the "average per bin" problem where the metadata column to average contains only 1's. Here is a proposal for a function that tries to solve the "average per bin" problem (not sure averagePerBin is a good name for this function): ### 'x': a GenomicRanges objects with non-NA seqlengths. ### 'binsize': a single positive integer. ### 'mcolnames': names of numeric metadata columns in 'x' to "average" ### i.e. to propagate to the result after averaging them ### on each bin. ### Returns a GRanges object with: (a) the same seqinfo as 'x', ### (b) ranges of width 'binsize' covering all the sequences in ### 'seqinfo(x)', and (c) the "averaged" metadata columns specified ### in 'mcolnames'. averagePerBin <- function(x, binsize, mcolnames=NULL) { if (!is(x, "GenomicRanges")) stop("'x' must be a GenomicRanges object") if (anyis.na(seqlengths(x)))) stop("'seqlengths(x)' contains NAs") bins <- IRangesList(lapply(seqlengths(x), function(seqlen) IRanges(breakInChunks(seqlen, binsize)))) ans <- as(bins, "GRanges") seqinfo(ans) <- seqinfo(x) if (is.null(mcolnames)) return(ans) averageMCol <- function(colname) { cvg <- coverage(x, weight=colname) views_list <- RleViewsList( lapply(names(cvg), function(seqname) Views(cvg[[seqname]], bins[[seqname]]))) unlist(viewMeans(views_list), use.names=FALSE) } mcols(ans) <- DataFrame(lapply(mcols(x)[mcolnames], averageMCol)) ans } Using it to solve Hermann's "density" problem: library(BSgenome.Hsapiens.UCSC.hg19) ## Set the sequence lengths. seqlengthstestset.gr) <- seqlengths(Hsapiens)[seqlevelstestset.gr)] ## Add the density metadata col. mcolstestset.gr)$density <- 1 ## Compute the average per bin for the specified metadata cols. avg_per_bin <- averagePerBintestset.gr, 200, mcolnames="density") > avg_per_bin[50:54] GRanges with 5 ranges and 1 metadata column: seqnames ranges strand | density <rle> <iranges> <rle> | <numeric> [1] chr1 [ 9801, 10000] * | 0 [2] chr1 [10001, 10200] * | 0.285 [3] chr1 [10201, 10400] * | 0.765 [4] chr1 [10401, 10600] * | 0.115 [5] chr1 [10601, 10800] * | 0 --- seqlengths: chr1 chr10 chr11 chr12 ... chr9 chrX chrY 249250621 135534747 135006516 133851895 ... 141213431 155270560 59373566 Note that calling averagePerBin() without specifying 'mcolnames' is a convenient way to generate genomic bins covering the entire genome (and in that case the supplied GRanges doesn't even need to contain ranges): > empty_gr <- GRanges(seqinfo=seqinfo(Hsapiens)) > empty_gr GRanges with 0 ranges and 0 metadata columns: seqnames ranges strand <rle> <iranges> <rle> --- seqlengths: chr1 chr2 ... chrUn_gl000249 249250621 243199373 ... 38502 > averagePerBin(empty_gr, 25000000) GRanges with 205 ranges and 0 metadata columns: seqnames ranges strand <rle> <iranges> <rle> [1] chr1 [ 1, 25000000] * [2] chr1 [ 25000001, 50000000] * [3] chr1 [ 50000001, 75000000] * [4] chr1 [ 75000001, 100000000] * [5] chr1 [100000001, 125000000] * [6] chr1 [125000001, 150000000] * [7] chr1 [150000001, 175000000] * [8] chr1 [175000001, 200000000] * [9] chr1 [200000001, 225000000] * ... ... ... ... [197] chrUn_gl000241 [1, 42152] * [198] chrUn_gl000242 [1, 43523] * [199] chrUn_gl000243 [1, 43341] * [200] chrUn_gl000244 [1, 39929] * [201] chrUn_gl000245 [1, 36651] * [202] chrUn_gl000246 [1, 38154] * [203] chrUn_gl000247 [1, 36422] * [204] chrUn_gl000248 [1, 39786] * [205] chrUn_gl000249 [1, 38502] * --- seqlengths: chr1 chr2 ... chrUn_gl000249 249250621 243199373 ... 38502 If that seems useful/general enough, we should add this to the GenomicRanges package. Could even be made a generic with methods for IRanges and GenomicRanges. Suggestions? Cheers, H. On 01/21/2013 03:23 PM, Martin Morgan wrote: > On 01/20/2013 12:45 PM, Hermann Norpois wrote: >> I am sorry, but I still have a problem. With your syntax I get a vector >> that is going over all chromosomes. How do I get , for instance separate >> vectors for each chromosomes? > > I wrote Dario's original solution as: > > Get seqlengths (probably these should have been added to testset.gr when > it was created, e.g., coverage(BamFile("myBam")) > > library(BSgenome.Hsapiens.UCSC.hg19) > seqlengthstestset.gr) <- seqlengths(Hsapiens)[seqlevelstestset.gr)] > > Calculate coverage > > Gcoverage <- coveragetestset.gr) > > Here's Dario's function, revised to take a width argument and for the > first argument, 'x', to be the coverage of a single chromosome > > FUN <- function(x, y, width=200) { > starts <- seq(1, y, width) > mean(Views(x, start = starts, width=width), na.rm = TRUE) > } > > Then the calculation over all chromosomes > > coverageMeans <- > unlist(Map(FUN, Gcoverage, seqlengthstestset.gr)), use.names=FALSE) > > And then to get separate vectors for each chromosome, it's just a matter > of not unlisting > > binsByChr <- Map(FUN, Gcoverage, seqlengthstestset.gr)) > > with, e.g., > > binsByChr$chr1 > > But maybe I'm not understanding what you're after? > > Martin > >> Thanks >> >> 2013/1/17 Hermann Norpois <hnorpois at="" googlemail.com=""> >> >>> Hello, >>> >>> I would like to transform a GRange-object into something with density >>> information related of bins, e.g. 1 bin=200bps. So it starts at >>> poistion 1 >>> etc ... >>> That means (according to testset.gr): >>> bin 1 0 >>> bin 2 0 >>> ... >>> bin 50 0 >>> bin 51 0.28 #10000-10200 => (200-144)/200 >>> bin 52 0.765 #10200-10400 => 153/200 >>> ... >>> etc >>> according to testset.gr (see below). >>> >>> How does it work? Is there a special function? >>> Thanks >>> Hermann >>> >>> >>>> testset.gr >>> GRanges with 20 ranges and 0 metadata columns: >>> seqnames ranges strand >>> <rle> <iranges> <rle> >>> [1] chr1 [ 10144, 10353] * >>> [2] chr1 [ 10441, 10463] * >>> [3] chr1 [235633, 235766] * >>> [4] chr1 [237717, 237895] * >>> [5] chr1 [521444, 521624] * >>> [6] chr1 [540609, 540786] * >>> [7] chr1 [564495, 564672] * >>> [8] chr1 [565254, 566081] * >>> [9] chr1 [566537, 567272] * >>> ... ... ... ... >>> [12] chr1 [569610, 570190] * >>> [13] chr1 [601057, 601196] * >>> [14] chr1 [713227, 713475] * >>> [15] chr1 [752533, 752578] * >>> [16] chr1 [752654, 752695] * >>> [17] chr1 [754405, 754539] * >>> [18] chr1 [755336, 755918] * >>> [19] chr1 [756027, 756458] * >>> [20] chr1 [756793, 756843] * >>> --- >>> seqlengths: >>> chr1 chr10 chr11 chr12 chr13 chr14 ... chr6 chr7 chr8 chr9 >>> chrX >>> chrY >>> NA NA NA NA NA NA ... NA NA NA NA >>> NA NA >>>> dput testset.gr) >>> new("GRanges" >>> , seqnames = new("Rle" >>> , values = structure(1L, .Label = c("chr1", "chr10", "chr11", >>> "chr12", >>> "chr13", >>> "chr14", "chr15", "chr16", "chr17", "chr18", "chr19", "chr2", >>> "chr20", "chr21", "chr22", "chr3", "chr4", "chr5", "chr6", "chr7", >>> "chr8", "chr9", "chrX", "chrY"), class = "factor") >>> , lengths = 20L >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , ranges = new("IRanges" >>> , start = c(10144L, 10441L, 235633L, 237717L, 521444L, 540609L, >>> 564495L, >>> 565254L, 566537L, 567450L, 568038L, 569610L, 601057L, 713227L, >>> 752533L, 752654L, 754405L, 755336L, 756027L, 756793L) >>> , width = c(210L, 23L, 134L, 179L, 181L, 178L, 178L, 828L, 736L, >>> 453L, >>> 545L, 581L, 140L, 249L, 46L, 42L, 135L, 583L, 432L, 51L) >>> , NAMES = NULL >>> , elementType = "integer" >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , strand = new("Rle" >>> , values = structure(3L, .Label = c("+", "-", "*"), class = >>> "factor") >>> , lengths = 20L >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , elementMetadata = new("DataFrame" >>> , rownames = NULL >>> , nrows = 20L >>> , listData = structure(list(), .Names = character(0)) >>> , elementType = "ANY" >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , seqinfo = new("Seqinfo" >>> , seqnames = c("chr1", "chr10", "chr11", "chr12", "chr13", "chr14", >>> "chr15", >>> "chr16", "chr17", "chr18", "chr19", "chr2", "chr20", "chr21", >>> "chr22", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8", "chr9", >>> "chrX", "chrY") >>> , seqlengths = c(NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, >>> NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_) >>> , is_circular = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, >>> NA, NA, >>> NA, NA, >>> NA, NA, NA, NA, NA, NA, NA, NA, NA) >>> , genome = c(NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, >>> NA_character_ >>> ) >>> ) >>> , metadata = list() >>> ) >>>> >>> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > -- Hervé Pagès Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M1-B514 P.O. Box 19024 Seattle, WA 98109-1024 E-mail: hpages at fhcrc.org Phone: (206) 667-5791 Fax: (206) 667-1319

This was very helpful and is exactly what I want. Thanks Hermann 2013/1/22 Martin Morgan <mtmorgan@fhcrc.org> > On 01/20/2013 12:45 PM, Hermann Norpois wrote: > >> I am sorry, but I still have a problem. With your syntax I get a vector >> that is going over all chromosomes. How do I get , for instance separate >> vectors for each chromosomes? >> > > I wrote Dario's original solution as: > > Get seqlengths (probably these should have been added to testset.gr when > it was created, e.g., coverage(BamFile("myBam")) > > library(BSgenome.Hsapiens.**UCSC.hg19) > seqlengthstestset.gr) <- seqlengths(Hsapiens)[**seqlevelstestset.gr)] > > Calculate coverage > > Gcoverage <- coveragetestset.gr) > > Here's Dario's function, revised to take a width argument and for the > first argument, 'x', to be the coverage of a single chromosome > > FUN <- function(x, y, width=200) { > starts <- seq(1, y, width) > mean(Views(x, start = starts, width=width), na.rm = TRUE) > } > > Then the calculation over all chromosomes > > coverageMeans <- > unlist(Map(FUN, Gcoverage, seqlengthstestset.gr)), use.names=FALSE) > > And then to get separate vectors for each chromosome, it's just a matter > of not unlisting > > binsByChr <- Map(FUN, Gcoverage, seqlengthstestset.gr)) > > with, e.g., > > binsByChr$chr1 > > But maybe I'm not understanding what you're after? > > Martin > > Thanks >> >> 2013/1/17 Hermann Norpois <hnorpois@googlemail.com> >> >> Hello, >>> >>> I would like to transform a GRange-object into something with density >>> information related of bins, e.g. 1 bin=200bps. So it starts at poistion >>> 1 >>> etc ... >>> That means (according to testset.gr): >>> bin 1 0 >>> bin 2 0 >>> ... >>> bin 50 0 >>> bin 51 0.28 #10000-10200 => (200-144)/200 >>> bin 52 0.765 #10200-10400 => 153/200 >>> ... >>> etc >>> according to testset.gr (see below). >>> >>> How does it work? Is there a special function? >>> Thanks >>> Hermann >>> >>> >>> testset.gr >>>> >>> GRanges with 20 ranges and 0 metadata columns: >>> seqnames ranges strand >>> <rle> <iranges> <rle> >>> [1] chr1 [ 10144, 10353] * >>> [2] chr1 [ 10441, 10463] * >>> [3] chr1 [235633, 235766] * >>> [4] chr1 [237717, 237895] * >>> [5] chr1 [521444, 521624] * >>> [6] chr1 [540609, 540786] * >>> [7] chr1 [564495, 564672] * >>> [8] chr1 [565254, 566081] * >>> [9] chr1 [566537, 567272] * >>> ... ... ... ... >>> [12] chr1 [569610, 570190] * >>> [13] chr1 [601057, 601196] * >>> [14] chr1 [713227, 713475] * >>> [15] chr1 [752533, 752578] * >>> [16] chr1 [752654, 752695] * >>> [17] chr1 [754405, 754539] * >>> [18] chr1 [755336, 755918] * >>> [19] chr1 [756027, 756458] * >>> [20] chr1 [756793, 756843] * >>> --- >>> seqlengths: >>> chr1 chr10 chr11 chr12 chr13 chr14 ... chr6 chr7 chr8 chr9 chrX >>> chrY >>> NA NA NA NA NA NA ... NA NA NA NA >>> NA NA >>> >>>> dput testset.gr) >>>> >>> new("GRanges" >>> , seqnames = new("Rle" >>> , values = structure(1L, .Label = c("chr1", "chr10", "chr11", >>> "chr12", >>> "chr13", >>> "chr14", "chr15", "chr16", "chr17", "chr18", "chr19", "chr2", >>> "chr20", "chr21", "chr22", "chr3", "chr4", "chr5", "chr6", "chr7", >>> "chr8", "chr9", "chrX", "chrY"), class = "factor") >>> , lengths = 20L >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , ranges = new("IRanges" >>> , start = c(10144L, 10441L, 235633L, 237717L, 521444L, 540609L, >>> 564495L, >>> 565254L, 566537L, 567450L, 568038L, 569610L, 601057L, 713227L, >>> 752533L, 752654L, 754405L, 755336L, 756027L, 756793L) >>> , width = c(210L, 23L, 134L, 179L, 181L, 178L, 178L, 828L, 736L, >>> 453L, >>> 545L, 581L, 140L, 249L, 46L, 42L, 135L, 583L, 432L, 51L) >>> , NAMES = NULL >>> , elementType = "integer" >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , strand = new("Rle" >>> , values = structure(3L, .Label = c("+", "-", "*"), class = >>> "factor") >>> , lengths = 20L >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , elementMetadata = new("DataFrame" >>> , rownames = NULL >>> , nrows = 20L >>> , listData = structure(list(), .Names = character(0)) >>> , elementType = "ANY" >>> , elementMetadata = NULL >>> , metadata = list() >>> ) >>> , seqinfo = new("Seqinfo" >>> , seqnames = c("chr1", "chr10", "chr11", "chr12", "chr13", "chr14", >>> "chr15", >>> "chr16", "chr17", "chr18", "chr19", "chr2", "chr20", "chr21", >>> "chr22", "chr3", "chr4", "chr5", "chr6", "chr7", "chr8", "chr9", >>> "chrX", "chrY") >>> , seqlengths = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, >>> NA_integer_, NA_integer_, NA_integer_, NA_integer_) >>> , is_circular = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, >>> NA, >>> NA, NA, >>> NA, NA, NA, NA, NA, NA, NA, NA, NA) >>> , genome = c(NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, >>> NA_character_, >>> NA_character_, NA_character_, NA_character_, NA_character_, NA_character_ >>> ) >>> ) >>> , metadata = list() >>> ) >>> >>>> >>>> >>> >> [[alternative HTML version deleted]] >> >> ______________________________**_________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/**listinfo/bioconductor<https: stat.e="" thz.ch="" mailman="" listinfo="" bioconductor=""> >> Search the archives: http://news.gmane.org/gmane.** >> science.biology.informatics.**conductor<http: news.gmane.org="" gmane="" .science.biology.informatics.conductor=""> >> >> > > -- > Computational Biology / Fred Hutchinson Cancer Research Center > 1100 Fairview Ave. N. > PO Box 19024 Seattle, WA 98109 > > Location: Arnold Building M1 B861 > Phone: (206) 667-2793 > [[alternative HTML version deleted]]