I'm analyzing cancer samples sequenced with Molecular Inversion Probes (MIPs) which contain cnv's in the BRCA1 gene.
Since cn.mops is used to analyze WES data I want try if the program is able to call CNVs in my MIP data.
I'm now using the following code to run the program.
library(cn.mops) pdf("cn_mops_plot.pdf") BAMFiles <- as.matrix(read.table('/home/koen/bam_filelist_cn_mops.txt')) #segments <- read.table("/home/koen/cnv_tool_comparison/reference_files/BRCA_1_2_new_mip_panel_sorted_merged_only_normal_mips.bed",sep="\t",as.is=TRUE) segments <- read.table("/home/koen/cnv_tool_comparison/reference_files/BRCA1_2_new_mip_panel_sorted_no_snpmips_non_overlapping_no_chr22.bed",sep="\t",as.is=TRUE) gr <- GRanges(segments[,1],IRanges(segments[,2]-30,segments[,3]+30)) gr <- reduce(gr) X <- getSegmentReadCountsFromBAM(BAMFiles,GR=gr,mode="paired",parallel=12) resCNMOPS <- exomecn.mops(X,parallel=12) resCNMOPS <- calcIntegerCopyNumbers(resCNMOPS) plot(resCNMOPS,which=1) dev.off()
It fails however with the following output:
Normalizing... Starting local modeling, please be patient... Reference sequence: chr13 Reference sequence: chr17 Starting segmentation algorithm... Using "fastseg" for segmentation. No CNVs detected. Try changing "normalization", "priorImpact" or "thresholds". Warning message: In cn.mops(input = input, I = I, classes = classes, priorImpact = priorImpact, : Normalization might not be applicable for this small number of segments. Error in calcIntegerCopyNumbers(resCNMOPS) : No CNV regions in result object. Rerun cn.mops with different parameters! Calls: calcIntegerCopyNumbers -> calcIntegerCopyNumbers Execution halted
Can someone point me in the right direction about which settings to use?
Thank you very much for your help!