Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • 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]

Latest Articles

Collapse

  • seqadmin
    Strategies for Sequencing Challenging Samples
    by seqadmin


    Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
    03-22-2024, 06:39 AM
  • seqadmin
    Techniques and Challenges in Conservation Genomics
    by seqadmin



    The field of conservation genomics centers on applying genomics technologies in support of conservation efforts and the preservation of biodiversity. This article features interviews with two researchers who showcase their innovative work and highlight the current state and future of conservation genomics.

    Avian Conservation
    Matthew DeSaix, a recent doctoral graduate from Kristen Ruegg’s lab at The University of Colorado, shared that most of his research...
    03-08-2024, 10:41 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, Yesterday, 06:37 PM
0 responses
12 views
0 likes
Last Post seqadmin  
Started by seqadmin, Yesterday, 06:07 PM
0 responses
10 views
0 likes
Last Post seqadmin  
Started by seqadmin, 03-22-2024, 10:03 AM
0 responses
52 views
0 likes
Last Post seqadmin  
Started by seqadmin, 03-21-2024, 07:32 AM
0 responses
68 views
0 likes
Last Post seqadmin  
Working...
X