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  • Error -- SPP package, MSER -- could you please help

    Hi,

    I have some ChIp-seq data (Illumina v1.4; and ELAND extended mapped) and trying to analyze them using spp R package (http://www.nature.com/nbt/journal/v2.../nbt.1508.html) and package (http://compbio.med.harvard.edu/Supplements/ChIP-seq/). I am following the tutorial and it was going fine until MSER step which I really need. I got the following error:

    mser <- get.mser(RLTA_chip.data, RLTA_input.data, step.size=1e5, test.agreement=0.99, n.chains=10, cluster=NULL, fdr=0.05, method=tag.wtd, whs=detection.window.halfsize)

    excluding systematic background anomalies ... done
    calculating statistical thresholds
    FDR 0.05 threshold= Inf
    chained subsampling using fraction 0.9510645 .

    Error in ecdf(-mpd$re) : 'x' must have 1 or more non-missing values

    In addition: Warning messages:
    1: In min(npld$y[npld$fdr <= fdr]) :
    no non-missing arguments to min; returning Inf
    2: In min(npld$y[npld$fdr <= fdr]) :
    no non-missing arguments to min; returning Inf
    3: In min(npld$y[npld$fdr <= fdr]) :
    no non-missing arguments to min; returning Inf
    4: In is.na(mpd$re) :
    is.na() applied to non-(list or vector) of type 'NULL'
    5: In is.na(mpd$oe) :
    is.na() applied to non-(list or vector) of type 'NULL'




    > sessionInfo()
    R version 2.9.0 (2009-04-17)
    x86_64-unknown-linux-gnu

    locale:
    LC_CTYPE=en_US.UTF-8;LC_
    NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US.UTF-8;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C

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

    other attached packages:
    [1] nws_1.7.0.0 snow_0.3-3 spp_1.0 caTools_1.9 bitops_1.0-4.1

    loaded via a namespace (and not attached):
    [1] tools_2.9.0

    ----------------

    Could you please help to understand where is the error........................and how can I solve this. (I have a data set where control has much much more tags then in sample IP................14 million versus 2 million.....................so, I want to use the mser)

    Also in get.mser function: >> method=tag.wtd ............................I wanted to change it like method=tag.lwcc........................like following:



    mser <- get.mser(RLTA_chip.data, RLTA_input.data, step.size=1e5, test.agreement=0.99, n.chains=10, cluster=NULL, fdr=0.05, method=tag.lwcc, whs=detection.window.halfsize, skip.control.normalization = F)

    I got following error:


    chained subsample step 0 :
    finding background exclusion regions ... done
    determining peaks on provided 1 control datasets:
    using reversed signal for FDR calculations
    bg.weight= 2.936861 processing chr1 in 7 steps [Error in lwcc(x, y, s, e, return.peaks = return.peaks, bg.x = bg.x, bg.y = bg.y, :
    unused argument(s) (skip.control.normalization = TRUE)


    I did not find any documentation about skip.control.normalization....................................tried to write tha "FALSE"................but it then gave me two un used arguments (TRUE and FALSE)...........................so, how to solve this problem ??


    Thank you in advance for your generous help.

    may be you can ans in my mail directly:

    Khademul
    [email protected]

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