Thanks Mike,

I have now run exomeCopy to completion.  Unfortunately, the output looks
erroneous.  The percent normal state is very low for all of the samples
(around 10%).  And consequently, when I visualize the plots using:

cnv.cols <- c("red", "orange", "black", "deepskyblue", "blue")
plotCompiledCNV(CNV.segments = CNV.segments, seq.name = "1", col = cnv.cols)
plotCompiledCNV(CNV.segments = CNV.segments, seq.name = "2", col = cnv.cols)
plotCompiledCNV(CNV.segments = CNV.segments, seq.name = "3", col = cnv.cols)
plotCompiledCNV(CNV.segments = CNV.segments, seq.name = "4", col = cnv.cols)

etc,
most plots for all of the individuals are orange.  I presume that there
should be no color if compiled.segments$copy.count == 2 because I removed
them as the vignette suggested:

CNV.segments <- compiled.segments[compiled.segments$copy.count != 2, ]


A few of the model parameters are as follows:

> fit.list[[1]][[1]]@init.par$beta.hat
 intercept     log.bg         GC      GC.sq      width
 137.73955  227.35661 -185.97921  219.07224   -1.41302
> fit.list[[1]][[1]]@final.par$beta
  intercept      log.bg          GC       GC.sq       width
 287.284313  187.588809 -206.468309  214.974768   -1.189761
> fit.list[[1]][[2]]@init.par$beta.hat
   intercept       log.bg           GC        GC.sq        width
 168.7144028  220.0425351 -195.0044913  210.9412808   -0.2804571
> fit.list[[1]][[2]]@final.par$beta
   intercept       log.bg           GC        GC.sq        width
 284.3057111  153.1812321 -204.5005754  217.3399872    0.3090188
> fit.list[[2]][[2]]@init.par$beta.hat
   intercept       log.bg           GC        GC.sq        width
 183.6010329  239.9594618 -215.7970168  229.9454217   -0.3597293
> fit.list[[2]][[2]]@final.par$beta
   intercept       log.bg           GC        GC.sq        width
 252.8972821  131.2518196 -253.0415091  241.4809859   -0.8693721

I see that these parameters are far off from those present in the vignette.
 Is this the problem?
btw - I am using a sorted bed file of CCDS as the input bed; I presumed
that these are not overlapping.  And at any rate, I didn't suspect that
this was the issue.

Any reason why exomeCopy is not "seeing" d=2 as the expected value?


Cheers,

Kevin




On Mon, Apr 29, 2013 at 5:37 PM, Michael Love
<michaelisaiahlove@gmail.com>wrote:

> hi Kevin,
>
> It could be the rows with zero coverage. I have an example of removing
> rows with zero coverage in the third code chunk of section 3.5 of the
> vignette.
>
> Mike
>
>
>
> On Mon, Apr 29, 2013 at 9:32 PM, Kevin Lee <kevinjosephlee@gmail.com>wrote:
>
>> Hello,
>>
>> I am working with ExomeCopy, and I cannot get past this error:
>>
>> fit.list <- lapply(sample.names, runExomeCopy, seqs)
>> *Error in negLogLike(c(logit(goto.cnv), logit(goto.normal), beta.hat,
>> log(phi.hat)),  :*
>> *  NA/NaN/Inf in foreign function call (arg 5)*
>>
>>
>> where:
>> runExomeCopy <- function(sample.name, seqs) { lapply(seqs, function(
>> seq.name)
>> exomeCopy(counts[seq.name], sample.name, X.names = c("log.bg", "GC",
>> "GC.sq", "width"), S = 0:4, d = 2)) }
>>
>> (I have followed the vignette as closely as possible.)
>>
>>
>> There are some exons that have zero reads for all 7 samples.  Could this
>> be
>> causing the error?  And if so, how can I remove these rows (ranges) from
>> the counts RangeData object?
>>
>>
>> Cheers,
>>
>> Kevin
>>
>>
>> --
>> Kevin Lee
>> Georgia Institute of Technology
>> Department of Biology
>> PhD candidate in Bioinformatics
>>
>>         [[alternative HTML version deleted]]
>>
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>>
>
>


-- 
Kevin Lee
Georgia Institute of Technology
Department of Biology
PhD candidate in Bioinformatics

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