The whole ExomeCNV pipeline works well using the demo data. Unfortunately, there are some errors when I read into the coverage returned by GATK (v2.1-13-g1706365, Compiled 2012/10/12 19:21:06) DepthOfCoverage.
My data sets are deep whole-exome human normal and cancer genomes. I followed the instruction at https://secure.genome.ucla.edu/index...CNV_User_Guide. After GATK calculates the coverage, I used "read.all.coverage" to load the normal and tumor coverage information. However, I got the following message:
> norm = read.all.coverage(prefix, suffix, chr.list, header=T)
Warning messages:
1: In `[<-.factor`(`*tmp*`, ri, value = c(109L, 200L, 98L, 26L, 29L, :
invalid factor level, NAs generated
2: In `[<-.factor`(`*tmp*`, ri, value = c(76L, 216L, 96L, 70L, 88L, :
invalid factor level, NAs generated
3: In `[<-.factor`(`*tmp*`, ri, value = c(12L, 53L, 77L, 76L, 74L, :
invalid factor level, NAs generated
4: In `[<-.factor`(`*tmp*`, ri, value = c(14L, 83L, 101L, 100L, 81L, :
invalid factor level, NAs generated
5: In `[<-.factor`(`*tmp*`, ri, value = c(28L, 46L, 4L, 10L, 60L, 47L, :
invalid factor level, NAs generated
6: In `[<-.factor`(`*tmp*`, ri, value = c(28L, 128L, 242L, 74L, 35L, :
invalid factor level, NAs generated
7: In `[<-.factor`(`*tmp*`, ri, value = c(1L, 86L, 70L, 18L, 65L, 131L, :
invalid factor level, NAs generated
8: In `[<-.factor`(`*tmp*`, ri, value = c(1L, 1L, 33L, 30L, 20L, 28L, :
invalid factor level, NAs generated
9: In `[<-.factor`(`*tmp*`, ri, value = c(88L, 68L, 73L, 39L, 54L, :
invalid factor level, NAs generated
Then I went to the coverage file and the format is as below.
Target total_coverage average_coverage Sample_2N_total_cvg Sample_2N_mean_cvg Sample_2N_granular_Q1 Sample_2N_granular_median Sample_2N_granular_Q3 Sample_2N_%_above_15
chr1:69090-70008 1212 1.32 1212 1.32 1 1 2 0.0
Interestingly I found some lines include items '>500', which I suspect cause the reading problem:
chr21:10969051-10969151 48274 477.96 48274 477.96 384 >500 >500 100.0
chr21:10969985-10970085 53197 526.70 53197 526.70 487 >500 >500 100.0
I wonder if I missed something or if anybody have any idea what happened to my data.
My data sets are deep whole-exome human normal and cancer genomes. I followed the instruction at https://secure.genome.ucla.edu/index...CNV_User_Guide. After GATK calculates the coverage, I used "read.all.coverage" to load the normal and tumor coverage information. However, I got the following message:
> norm = read.all.coverage(prefix, suffix, chr.list, header=T)
Warning messages:
1: In `[<-.factor`(`*tmp*`, ri, value = c(109L, 200L, 98L, 26L, 29L, :
invalid factor level, NAs generated
2: In `[<-.factor`(`*tmp*`, ri, value = c(76L, 216L, 96L, 70L, 88L, :
invalid factor level, NAs generated
3: In `[<-.factor`(`*tmp*`, ri, value = c(12L, 53L, 77L, 76L, 74L, :
invalid factor level, NAs generated
4: In `[<-.factor`(`*tmp*`, ri, value = c(14L, 83L, 101L, 100L, 81L, :
invalid factor level, NAs generated
5: In `[<-.factor`(`*tmp*`, ri, value = c(28L, 46L, 4L, 10L, 60L, 47L, :
invalid factor level, NAs generated
6: In `[<-.factor`(`*tmp*`, ri, value = c(28L, 128L, 242L, 74L, 35L, :
invalid factor level, NAs generated
7: In `[<-.factor`(`*tmp*`, ri, value = c(1L, 86L, 70L, 18L, 65L, 131L, :
invalid factor level, NAs generated
8: In `[<-.factor`(`*tmp*`, ri, value = c(1L, 1L, 33L, 30L, 20L, 28L, :
invalid factor level, NAs generated
9: In `[<-.factor`(`*tmp*`, ri, value = c(88L, 68L, 73L, 39L, 54L, :
invalid factor level, NAs generated
Then I went to the coverage file and the format is as below.
Target total_coverage average_coverage Sample_2N_total_cvg Sample_2N_mean_cvg Sample_2N_granular_Q1 Sample_2N_granular_median Sample_2N_granular_Q3 Sample_2N_%_above_15
chr1:69090-70008 1212 1.32 1212 1.32 1 1 2 0.0
Interestingly I found some lines include items '>500', which I suspect cause the reading problem:
chr21:10969051-10969151 48274 477.96 48274 477.96 384 >500 >500 100.0
chr21:10969985-10970085 53197 526.70 53197 526.70 487 >500 >500 100.0
I wonder if I missed something or if anybody have any idea what happened to my data.
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