Help needed for exomeCNV

[sht41]

Hi there,

I am now working on a project of CNV analysis of exome sequencing data. By using exomeCNV, so far I obtained DepthOfCoverage files by GATK for all 8 samples.

The problems are:
1. The 8 samples all 8 cases, no paired controls available.
2. If I use one as control and all others as cases, by using classify.eCNV I can get the results of one comparison. How can I combine the results of all comparison into one?

Thanks!

sht41

[shruti]

Hi..

I am running ExomeCNV too.. but facing another issue
I used bam2coverage.sh for DFepth of coverage and I get files for each chromosome, however when I read the files then I see that the coverage is calculated for all the chromosomes for each file and they have different outputs (below) did you have the same output?

-clustershell-3.2$ head tumor.chr1.exon_parsed.coverage
probe chr probe_start probe_end targeted base sequenced base coverage average coverage base with >10 coverage
probe1 chr1 3206095 3207055 961 961 104089 108.3132154 961
probe2 chr1 3411761 3412001 241 241 10022 41.58506224 241
probe3 chr1 3660595 3661075 481 481 115178 239.4553015 481
probe4 chr1 3670956 3671556 601 601 54714 91.03826955 601
probe5 chr1 4334491 4334641 151 151 6045 40.03311258 151


-clustershell-3.2$ head tumor.chr2.exon_parsed.coverage
probe chr probe_start probe_end targeted base sequenced base coverage average coverage base with >10 coverage
probe1 chr1 3206095 3207055 961 1870 263547 274.2424558 1642
probe2 chr1 3411761 3412001 241 11824 1521051 6311.414938 11815
probe3 chr1 3660595 3661075 481 3962 577520 1200.665281 3958
probe4 chr1 3670956 3671556 601 0 0 0 0
probe5 chr1 4334491 4334641 151 1445 189457 1254.682119 1445


Also running the R script for few chromosomes gives me an error

Error in if (lim.logR[1] == -Inf) lim.logR[1] = min(all.ecnv$logR[all.ecnv$logR != :
missing value where TRUE/FALSE needed
Calls: do.plot.eCNV
Execution halted

Any help would be really great..

thanks

shruti

[ymc]

Maybe you can pool 7 of them as control and 1 as case? Then repeat this process for eight times and you have data for 8 cases.