Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • abmmki
    Junior Member
    • Nov 2009
    • 5

    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

  • SEQadmin2
    Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
    by SEQadmin2



    Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
    ...
    Yesterday, 11:10 AM
  • SEQadmin2
    Cancer Drug Resistance: The Lingering Barrier to Rising Survival
    by SEQadmin2



    Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

    There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
    07-08-2026, 05:17 AM
  • GATTACAT
    Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
    by GATTACAT
    Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
    07-01-2026, 11:43 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, Yesterday, 10:04 AM
0 responses
10 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-08-2026, 10:08 AM
0 responses
7 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-07-2026, 11:05 AM
0 responses
15 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-02-2026, 11:08 AM
0 responses
31 views
0 reactions
Last Post SEQadmin2  
Working...