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  • #31
    Hello Gonghong,

    Yes, Novoalign is it's own beast (an excellent one at that) and is from Novocraft. So first run your reads through their aligner and then process your data with USeq. For chIP-seq you can probably get by with little loss in resolution using the xxx.sorted.gz alignments that came off the default Eland aligner that runs with the Illumina pipeline. Or barring those, use Bowtie for fast ungapped alignments.

    -cheers, D

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    • #32
      comparing peak set profiles in chip-seq datasets

      Hi,

      Is there any tool that will tell me how different/similar two chip-seq peak sets are in two different parts of the genome?

      E.g. if I have a ~10Kb region in the genome with a series of peaks and another ~10Kb region in the genome with another set of peaks from the same experiment, can I calculate a distance measure between these two peak set profiles with any available tool?

      Cheers

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      • #33
        Yes, I've built a rather sophisticated tool for doing just this sort of thing. See IntersectRegions in the USeq package.

        **************************************************************************************
        ** Intersect Regions: August 2008 **
        **************************************************************************************
        IR intersects lists of regions (tab delimited: chrom start stop(inclusive)). Random
        regions can also be used to calculate a p-value and fold enrichment.

        -f First regions files, a single file, or a directory of files.
        -s Second regions files, a single file, or a directory of files.
        -g Max gap, defaults to 0. A max gap of 0 = regions must abut, negative values force
        overlap (ie -1= 1bp overlap, be careful not to exceed the length of the smaller
        region), positive values enable gaps (ie 1=1bp gap).
        -e Score intersections where second regions are entirely contained by first regions.
        -r Make random regions matched to the second regions file(s) and intersect with the
        first. Enter the full path directory text containing chromosome specific
        interrogated regions files (ie named: chr1, chr2 ...: chrom start stop(inclusive)).
        -c Match GC content of second regions file(s) when selecting random regions, rather
        slow. Provide a full path directory text containing chromosome specific genomic
        sequences. To speed the matching place the fraction GC in the last column of
        your region file(s).
        -n Number of random region trials, defaults to 1000.
        -w Write intersections and differences.
        -x Write paired intersections.
        -p Print length distribution histogram for gaps between first and closest second.
        -q Parameters for histogram, comma delimited list, no spaces:
        minimum length, maximum length, number of bins. Defaults to -100, 2400, 100.

        Example: java -Xmx1500M -jar pathTo/Apps/IntersectRegions -f /data/miRNAs.txt
        -s /data/DroshaLists/ -g 500 -n 1000 -r /data/InterrogatedRegions/

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