How To Call Somatic variants using TS?

Hi there,i have a pair bam data (Tumor and Normal from the same patient), PGM data,i download TS and installed it ,i'm wondering how to call somatic mutaion using TS?

i can't find demo from http://updates.iontorrent.com/tvc_standalone/README.txt can anybody help me ?

Thanks a lot..

Oh,here is my command: python /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/bin/variant_caller_pipeline.py --input-bam Ion_B1701/Ion_B1701.bam --reference-fasta /gpfs/users/yanghao/database/ref/hg19_hg38_MT/hg19_hg38_MT.fa --region-bed OCP_Target.bed --normal-bam Ion_B17NC/Ion_B17NC.bam --parameters-file /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/share/TVC/pluginMedia/parameter_sets/ampliseq_somatic_lowstringency_pgm_parameters.json --output-dir . -g "Sample 1"

and equal to :: /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/bin/tvc --output-dir . --reference "/gpfs/users/yanghao/database/ref/hg19_hg38_MT/hg19_hg38_MT.fa" --input-bam "Ion_B1701/Ion_B1701.bam","Ion_B17NC/Ion_B17NC.bam" --sample-name "Sample 1" --num-threads 12 --target-file "OCP_Target.bed" --parameters-file "/gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/share/TVC/pluginMedia/parameter_sets/ampliseq_somatic_lowstringency_pgm_parameters.json" --output-vcf "small_variants.vcf"

and some ERROR occurs:

`[yanghao@c03b01n02 pt1]$ python /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/bin/variant_caller_pipeline.py --input-bam Ion_B1701/Ion_B1701.bam --reference-fasta /gpfs/users/yanghao/database/ref/hg19_hg38_MT/hg19_hg38_MT.fa --region-bed OCP_Target.bed --normal-bam Ion_B17NC/Ion_B17NC.bam --parameters-file /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/share/TVC/pluginMedia/parameter_sets/ampliseq_somatic_lowstringency_pgm_parameters.json --output-dir . -g "Sample 1" [ Wed 2018-03-21 14:00:13 CST ] Using tvc binary: /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/bin/tvc [ Wed 2018-03-21 14:00:13 CST ] Using tvcutils binary: /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/bin/tvcutils [ Wed 2018-03-21 14:00:13 CST ] Using tmap binary: tmap [ Wed 2018-03-21 14:00:13 CST ] Calling small INDELs and SNPs using tvc ... [ Wed 2018-03-21 14:00:13 CST ] [ Wed 2018-03-21 14:00:13 CST ] Task : Call small indels and SNPs [ Wed 2018-03-21 14:00:13 CST ] Command : /gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/bin/tvc --output-dir . --reference "/gpfs/users/yanghao/database/ref/hg19_hg38_MT/hg19_hg38_MT.fa" --input-bam "Ion_B1701/Ion_B1701.bam","Ion_B17NC/Ion_B17NC.bam" --sample-name "Sample 1" --num-threads 12 --target-file "OCP_Target.bed" --parameters-file "/gpfs/users/yanghao/software/tvc-5.8.0-CentOS_7.2.1511_x86_64-binary/share/TVC/pluginMedia/parameter_sets/ampliseq_somatic_lowstringency_pgm_parameters.json" --output-vcf "small_variants.vcf" [ Wed 2018-03-21 14:00:13 CST ] tvc 5.8-0 (805fda4-c69c74d) - Torrent Variant Caller

TVC: Floating point exceptions enabled. INFO: No sse VCF file specified via -l,--sse-vcf INFO: No input VCF (Hotspot) file specified via -c,--input-vcf error-motifs = (string, parameters json file) INFO: Systematic error motif file not specified via -e hp-max-length = 8 (integer, parameters json file) sse-prob-threshold = 1 (double, parameters json file) min-ratio-reads-non-sse-strand = 0.2 (double, builtin default) sse-relative-safety-level = 0.025 (double, builtin default) do-snp-realignment = false (boolean, parameters json file) do-mnp-realignment = false (boolean, parameters json file) realignment-threshold = 0 (double, parameters json file) indel-as-hpindel = false (boolean, parameters json file) hp-indel-hrun = -1,-1 (int, builtin default) hp-ins-len = -1,-1 (int, builtin default) hp-del-len = -1,-1 (int, builtin default) data-quality-stringency = 10 (double, parameters json file) read-rejection-threshold = 0.5 (double, builtin default) use-position-bias = false (boolean, parameters json file) position-bias-ref-fraction = 0.05 (double, parameters json file) position-bias = 0.75 (double, parameters json file) position-bias-pval = 0.05 (double, parameters json file) use-lod-filter = false (boolean, builtin default) lod-multiplier = 0.6 (double, builtin default) tag-sim-max-cov = 20 (integer, builtin default) downsample-to-coverage = 2000 (integer, parameters json file) tune-sbias = 0.01 (double, builtin default) suppress-reference-genotypes = true (boolean, builtin default) suppress-nocall-genotypes = true (boolean, builtin default) suppress-no-calls = true (boolean, builtin default) heal-snps = true (boolean, builtin default) cleanup-unlikely-candidates = true (boolean, builtin default) report-ppa = false (boolean, parameters json file) hotspots-as-de-novo = false (boolean, builtin default) disable-filters = false (boolean, builtin default) fd-nonsnp-min-var-cov = 0 (integer, builtin default) use-fd-param = false (boolean, parameters json file) min-ratio-for-fd = 0.1 (double, parameters json file) snp-min-cov-each-strand = 4 (integer, parameters json file) snp-min-variant-score = 6 (double, parameters json file) snp-min-allele-freq = 0.02 (double, parameters json file) snp-min-coverage = 100 (integer, parameters json file) snp-min-var-coverage = 0 (integer, builtin default) snp-strand-bias = 0.95 (double, parameters json file) snp-strand-bias-pval = 0.01 (double, parameters json file) Retrieving the snp parameters from the command line and parameter_json["torrent_variant_caller"]["snp"]: snp-min-cov-each-strand = 4 (integer, builtin default) snp-min-variant-score = 6 (double, builtin default) snp-min-allele-freq = 0.02 (double, builtin default) snp-min-coverage = 100 (integer, builtin default) snp-min-var-coverage = 0 (integer, builtin default) snp-strand-bias = 0.95 (double, builtin default) snp-strand-bias-pval = 0.01 (double, builtin default) (Note): Here, "builtin default" may be referred to as the the parameter has been set previously. Retrieving snp parameter set complete. mnp-min-cov-each-strand = 4 (integer, parameters json file) mnp-min-variant-score = 6 (double, parameters json file) mnp-min-allele-freq = 0.02 (double, parameters json file) mnp-min-coverage = 100 (integer, parameters json file) mnp-min-var-coverage = 0 (integer, builtin default) mnp-strand-bias = 0.95 (double, parameters json file) mnp-strand-bias-pval = 0.01 (double, parameters json file) Retrieving the mnp parameters from the command line and parameter_json["torrent_variant_caller"]["mnp"]: mnp-min-cov-each-strand = 4 (integer, builtin default) mnp-min-variant-score = 6 (double, builtin default) mnp-min-allele-freq = 0.02 (double, builtin default) mnp-min-coverage = 100 (integer, builtin default) mnp-min-var-coverage = 0 (integer, builtin default) mnp-strand-bias = 0.95 (double, builtin default) mnp-strand-bias-pval = 0.01 (double, builtin default) (Note): Here, "builtin default" may be referred to as the the parameter has been set previously. Retrieving mnp parameter set complete. indel-min-cov-each-strand = 4 (integer, parameters json file) indel-min-variant-score = 6 (double, parameters json file) indel-min-allele-freq = 0.02 (double, parameters json file) indel-min-coverage = 100 (integer, parameters json file) indel-min-var-coverage = 0 (integer, builtin default) indel-strand-bias = 0.9 (double, parameters json file) indel-strand-bias-pval = 1 (double, parameters json file) Retrieving the indel parameters from the command line and parameter_json["torrent_variant_caller"]["indel"]: indel-min-cov-each-strand = 4 (integer, builtin default) indel-min-variant-score = 6 (double, builtin default) indel-min-allele-freq = 0.02 (double, builtin default) indel-min-coverage = 100 (integer, builtin default) indel-min-var-coverage = 0 (integer, builtin default) indel-strand-bias = 0.9 (double, builtin default) indel-strand-bias-pval = 1 (double, builtin default) (Note): Here, "builtin default" may be referred to as the the parameter has been set previously. Retrieving indel parameter set complete.

Retrieving the indel parameters that will be propagate to the fd-0 parameters: indel-min-cov-each-strand = 4 (integer, parameters json file) indel-min-variant-score = 6 (double, parameters json file) indel-min-allele-freq = 0.02 (double, parameters json file) indel-min-coverage = 100 (integer, parameters json file) indel-min-var-coverage = 0 (integer, builtin default) indel-strand-bias = 0.9 (double, parameters json file) indel-strand-bias-pval = 1 (double, parameters json file) Translating the above indel parameters to the fd-0 parameters. Retrieving the fd-0 parameters from the command line and parameter_json["torrent_variant_caller"]["fd_0"]: fd-0-min-cov-each-strand = 4 (integer, builtin default) fd-0-min-variant-score = 6 (double, builtin default) fd-0-min-allele-freq = 0.02 (double, builtin default) fd-0-min-coverage = 100 (integer, builtin default) fd-0-min-var-coverage = 0 (integer, builtin default) fd-0-strand-bias = 0.9 (double, builtin default) fd-0-strand-bias-pval = 1 (double, builtin default) (Note): Here, "builtin default" may be referred to as the the parameter has been set previously. Retrieving fd-0 parameter set complete.

Retrieving the snp parameters that will be propagate to the fd-5 parameters: snp-min-cov-each-strand = 4 (integer, parameters json file) snp-min-variant-score = 6 (double, parameters json file) snp-min-allele-freq = 0.02 (double, parameters json file) snp-min-coverage = 100 (integer, parameters json file) snp-min-var-coverage = 0 (integer, builtin default) snp-strand-bias = 0.95 (double, parameters json file) snp-strand-bias-pval = 0.01 (double, parameters json file) Translating the above snp parameters to the fd-5 parameters. Retrieving the fd-5 parameters from the command line and parameter_json["torrent_variant_caller"]["fd_5"]: fd-5-min-cov-each-strand = 4 (integer, builtin default) fd-5-min-variant-score = 6 (double, builtin default) fd-5-min-allele-freq = 0.02 (double, builtin default) fd-5-min-coverage = 100 (integer, builtin default) fd-5-min-var-coverage = 0 (integer, builtin default) fd-5-strand-bias = 0.95 (double, builtin default) fd-5-strand-bias-pval = 0.01 (double, builtin default) (Note): Here, "builtin default" may be referred to as the the parameter has been set previously. Retrieving fd-5 parameter set complete.

Retrieving the mnp parameters that will be propagate to the fd-10 parameters: mnp-min-cov-each-strand = 4 (integer, parameters json file) mnp-min-variant-score = 6 (double, parameters json file) mnp-min-allele-freq = 0.02 (double, parameters json file) mnp-min-coverage = 100 (integer, parameters json file) mnp-min-var-coverage = 0 (integer, builtin default) mnp-strand-bias = 0.95 (double, parameters json file) mnp-strand-bias-pval = 0.01 (double, parameters json file) Translating the above mnp parameters to the fd-10 parameters. Retrieving the fd-10 parameters from the command line and parameter_json["torrent_variant_caller"]["fd_10"]: fd-10-min-cov-each-strand = 4 (integer, builtin default) fd-10-min-variant-score = 6 (double, builtin default) fd-10-min-allele-freq = 0.02 (double, builtin default) fd-10-min-coverage = 100 (integer, builtin default) fd-10-min-var-coverage = 0 (integer, builtin default) fd-10-strand-bias = 0.95 (double, builtin default) fd-10-strand-bias-pval = 0.01 (double, builtin default) (Note): Here, "builtin default" may be referred to as the the parameter has been set previously. Retrieving fd-10 parameter set complete. hotspot-min-cov-each-strand = 4 (integer, parameters json file) hotspot-min-variant-score = 6 (double, parameters json file) hotspot-min-allele-freq = 0.02 (double, parameters json file) hotspot-min-coverage = 100 (integer, parameters json file) hotspot-min-var-coverage = 0 (integer, builtin default) hotspot-strand-bias = 0.95 (double, parameters json file) hotspot-strand-bias-pval = 0.01 (double, parameters json file) Retrieving the hotspot parameters from the command line and parameter_json["torrent_variant_caller"]["hotspot"]: hotspot-min-cov-each-strand = 4 (integer, builtin default) hotspot-min-variant-score = 6 (double, builtin default) hotspot-min-allele-freq = 0.02 (double, builtin default) hotspot-min-coverage = 100 (integer, builtin default) hotspot-min-var-coverage = 0 (integer, builtin default) hotspot-strand-bias = 0.95 (double, builtin default) hotspot-strand-bias-pval = 0.01 (double, builtin default) (Note): Here, "builtin default" may be referred to as the the parameter has been set previously. Retrieving hotspot parameter set complete. max-flows-to-test = 10 (integer, parameters json file) min-delta-for-flow = 0.1 (double, builtin default) prediction-precision = 1 (double, parameters json file) outlier-probability = 0.005 (double, parameters json file) germline-prior-strength = 0 (double, builtin default) heavy-tailed = 3 (integer, parameters json file) adjust-sigma = false (boolean, builtin default) filter-unusual-predictions = 0.12 (double, parameters json file) soft-clip-bias-checker = 0.1 (double, builtin default) filter-deletion-predictions = 0.2 (double, parameters json file) filter-insertion-predictions = 0.2 (double, parameters json file) max-detail-level = 0 (integer, builtin default) min-detail-level-for-fast-scan = 0 (integer, parameters json file) try-few-restart-freq = false (boolean, builtin default) shift-likelihood-penalty = 0.3 (double, builtin default) minimum-sigma-prior = 0.085 (double, builtin default) slope-sigma-prior = 0.0084 (double, builtin default) sigma-prior-weight = 1 (double, builtin default) k-zero = 3 (double, builtin default) num-threads = 12 (integer, command line option) num-variants-per-thread = 250 (integer, builtin default) use-sse-basecaller = true (boolean, builtin default) do-json-diagnostic = false (boolean, builtin default) do-minimal-diagnostic = false (boolean, builtin default) process-input-positions-only = false (boolean, builtin default) suppress-recalibration = false (boolean, parameters json file) resolve-clipped-bases = false (boolean, builtin default) use-sse-basecaller = true (boolean, builtin default) do-indel-assembly = true (boolean, builtin default) output-multi-min-allele-freq = false (boolean, builtin default) multi-min-allele-freq = 0.05,0.1,0.15,0.2 (float, builtin default) suppress-mol-tags = false (boolean, builtin default) min-tag-fam-size = 3 (integer, builtin default) indel-func-size-offset = 0 (integer, builtin default) tag-trim-method = sloppy-trim (string, builtin default) min-cov-fraction = 0 (double, builtin default) allow-indels = true (boolean, parameters json file) allow-snps = true (boolean, parameters json file) allow-mnps = true (boolean, parameters json file) allow-complex = false (boolean, parameters json file) merge-variant-lookahead = -1 (integer, builtin default) allele-cigar-output = false (boolean, builtin default) left-align-indels = false (boolean, builtin default) use-best-n-alleles = 2 (integer, builtin default) use-best-n-nonsnp-alleles = 0 (integer, builtin default) max-alt-num = 20 (integer, builtin default) use-input-allele-only = false (boolean, builtin default) min-mapping-qv = 4 (integer, parameters json file) read-snp-limit = 10 (integer, parameters json file) read-max-mismatch-fraction = 1 (double, parameters json file) read-mismatch-limit = 0 (integer, builtin default) max-complex-gap = 1 (integer, builtin default) gen-min-alt-allele-freq = 0.01 (double, parameters json file) gen-min-coverage = 6 (integer, parameters json file) gen-min-indel-alt-allele-freq = 0.01 (double, parameters json file) override-limits = false (boolean, builtin default) prefix-exclude = 6 Limit check parameter data-quality-stringency: lim. 0 <= 10? OK! Limit check parameter read-rejection-threshold: lim. 0 <= 0.5 <= lim. 1? OK! Limit check parameter downsample-to-coverage: lim. 20 <= 2000 <= lim. 200000? OK! Limit check parameter position-bias-ref-fraction: lim. 0 <= 0.05 <= lim. 1? OK! Limit check parameter position-bias: lim. 0 <= 0.75 <= lim. 1? OK! Limit check parameter position-bias-pval: lim. 0 <= 0.05 <= lim. 1? OK! Limit check parameter tune-sbias: lim. 0.001 <= 0.01 <= lim. 1000? OK! Limit check parameter lod-multiplier: lim. 0 <= 0.6? OK! Limit check parameter tag-sim-max-cov: lim. 0 <= 20? OK! Limit check parameter min-read-ratio-for-fd: lim. 0 <= 0.1 <= lim. 1? OK! Limit check parameter fd-nonsnp-min-var-cov: lim. 0 <= 0? OK! Limit check parameter hp-max-length: lim. 1 <= 8? OK! Limit check parameter sse-prob-threshold: lim. 0 <= 1 <= lim. 1? OK! Limit check parameter min-ratio-reads-non-sse-strand: lim. 0 <= 0.2 <= lim. 1? OK! Limit check parameter sse-relative-safety-level: lim. 0 <= 0.025 <= lim. 1? OK! Limit check parameter realignment-threshold: lim. 0 <= 0 <= lim. 1? OK! Size check parameters hp-indel-hrun, hp-ins-len, hp-del-len: hp_indel_hrun.size()==hp_ins_len.size()==hp_del_len.size()? OK! Limit check parameter snp-min-cov-each-strand: lim. 0 <= 4? OK! Limit check parameter snp-min-variant-score: lim. 0 <= 6? OK! Limit check parameter snp-min-allele-freq: lim. 0 <= 0.02 <= lim. 1? OK! Limit check parameter snp-min-coverage: lim. 0 <= 100? OK! Limit check parameter snp-strand-bias: lim. 0.5 <= 0.95 <= lim. 1? OK! Limit check parameter snp-strand-bias-pval: lim. 0 <= 0.01 <= lim. 1? OK! Limit check parameter snp-min-var-coverage: lim. 0 <= 0? OK! Limit check parameter mnp-min-cov-each-strand: lim. 0 <= 4? OK! Limit check parameter mnp-min-variant-score: lim. 0 <= 6? OK! Limit check parameter mnp-min-allele-freq: lim. 0 <= 0.02 <= lim. 1? OK! Limit check parameter mnp-min-coverage: lim. 0 <= 100? OK! Limit check parameter mnp-strand-bias: lim. 0.5 <= 0.95 <= lim. 1? OK! Limit check parameter mnp-strand-bias-pval: lim. 0 <= 0.01 <= lim. 1? OK! Limit check parameter mnp-min-var-coverage: lim. 0 <= 0? OK! Limit check parameter indel-min-cov-each-strand: lim. 0 <= 4? OK! Limit check parameter indel-min-variant-score: lim. 0 <= 6? OK! Limit check parameter indel-min-allele-freq: lim. 0 <= 0.02 <= lim. 1? OK! Limit check parameter indel-min-coverage: lim. 0 <= 100? OK! Limit check parameter indel-strand-bias: lim. 0.5 <= 0.9 <= lim. 1? OK! Limit check parameter indel-strand-bias-pval: lim. 0 <= 1 <= lim. 1? OK! Limit check parameter indel-min-var-coverage: lim. 0 <= 0? OK! Limit check parameter hotspot-min-cov-each-strand: lim. 0 <= 4? OK! Limit check parameter hotspot-min-variant-score: lim. 0 <= 6? OK! Limit check parameter hotspot-min-allele-freq: lim. 0 <= 0.02 <= lim. 1? OK! Limit check parameter hotspot-min-coverage: lim. 0 <= 100? OK! Limit check parameter hotspot-strand-bias: lim. 0.5 <= 0.95 <= lim. 1? OK! Limit check parameter hotspot-strand-bias-pval: lim. 0 <= 0.01 <= lim. 1? OK! Limit check parameter hotspot-min-var-coverage: lim. 0 <= 0? OK! Limit check parameter fd-0-min-cov-each-strand: lim. 0 <= 4? OK! Limit check parameter fd-0-min-variant-score: lim. 0 <= 6? OK! Limit check parameter fd-0-min-allele-freq: lim. 0 <= 0.02 <= lim. 1? OK! Limit check parameter fd-0-min-coverage: lim. 0 <= 100? OK! Limit check parameter fd-0-strand-bias: lim. 0.5 <= 0.9 <= lim. 1? OK! Limit check parameter fd-0-strand-bias-pval: lim. 0 <= 1 <= lim. 1? OK! Limit check parameter fd-0-min-var-coverage: lim. 0 <= 0? OK! Limit check parameter fd-5-min-cov-each-strand: lim. 0 <= 4? OK! Limit check parameter fd-5-min-variant-score: lim. 0 <= 6? OK! Limit check parameter fd-5-min-allele-freq: lim. 0 <= 0.02 <= lim. 1? OK! Limit check parameter fd-5-min-coverage: lim. 0 <= 100? OK! Limit check parameter fd-5-strand-bias: lim. 0.5 <= 0.95 <= lim. 1? OK! Limit check parameter fd-5-strand-bias-pval: lim. 0 <= 0.01 <= lim. 1? OK! Limit check parameter fd-5-min-var-coverage: lim. 0 <= 0? OK! Limit check parameter fd-10-min-cov-each-strand: lim. 0 <= 4? OK! Limit check parameter fd-10-min-variant-score: lim. 0 <= 6? OK! Limit check parameter fd-10-min-allele-freq: lim. 0 <= 0.02 <= lim. 1? OK! Limit check parameter fd-10-min-coverage: lim. 0 <= 100? OK! Limit check parameter fd-10-strand-bias: lim. 0.5 <= 0.95 <= lim. 1? OK! Limit check parameter fd-10-strand-bias-pval: lim. 0 <= 0.01 <= lim. 1? OK! Limit check parameter fd-10-min-var-coverage: lim. 0 <= 0? OK! Limit check parameter max-flows-to-test: lim. 1 <= 10 <= lim. 100? OK! Limit check parameter min-delta-for-flow: lim. 0.01 <= 0.1 <= lim. 0.5? OK! Limit check parameter prediction-precision: lim. 0.1 <= 1? OK! Limit check parameter outlier-probability: lim. 1e-07 <= 0.005 <= lim. 1? OK! Limit check parameter germline-prior-strength: lim. 0 <= 0 <= lim. 1000? OK! Limit check parameter heavy-tailed: lim. 1 <= 3? OK! Limit check parameter filter-unusual-predictions: lim. 0 <= 0.12? OK! Limit check parameter soft-clip-bias-checker: lim. 0 <= 0.1 <= lim. 1? OK! Limit check parameter filter-deletion-predictions: lim. 0 <= 0.2? OK! Limit check parameter filter-insertion-predictions: lim. 0 <= 0.2? OK! Limit check parameter max-detail-level: lim. 0 <= 0 <= lim. 10000? OK! Limit check parameter min-detail-level-for-fast-scan: lim. 0 <= 0? OK! Limit check parameter shift-likelihood-penalty: lim. 0.01 <= 0.3? OK! Limit check parameter minimum-sigma-prior: lim. 0.01 <= 0.085? OK! Limit check parameter slope-sigma-prior: lim. 0 <= 0.0084? OK! Limit check parameter sigma-prior-weight: lim. 0.01 <= 1? OK! Limit check parameter k-zero: lim. 0 <= 3? OK! Limit check parameter num-threads: lim. 1 <= 12 <= lim. 128? OK! Limit check parameter num-variants-per-thread: lim. 1 <= 250 <= lim. 10000? OK! Limit check parameter multi-min-allele-freq[0]: lim. 0 <= 0.05 <= lim. 1? OK! Limit check parameter multi-min-allele-freq[1]: lim. 0 <= 0.1 <= lim. 1? OK! Limit check parameter multi-min-allele-freq[2]: lim. 0 <= 0.15 <= lim. 1? OK! Limit check parameter multi-min-allele-freq[3]: lim. 0 <= 0.2 <= lim. 1? OK! Limit check parameter min-cov-fraction: lim. 0 <= 0 <= lim. 1? OK! Limit check parameter use-best-n-alleles: lim. 0 <= 2 <= lim. 20? OK! Limit check parameter use-best-n-nonsnp-alleles: lim. 0 <= 0 <= lim. 20? OK! Limit check parameter min-mapping-qv: lim. 0 <= 4? OK! Limit check parameter read-snp-limit: lim. 0 <= 10? OK! Limit check parameter read-max-mismatch-fraction: lim. 0 <= 1 <= lim. 1? OK! Limit check parameter read-mismatch-limit: lim. 0 <= 0? OK! Limit check parameter gen-min-alt-allele-freq: lim. 0 <= 0.01 <= lim. 1? OK! Limit check parameter gen-min-coverage: lim. 0 <= 6? OK! Limit check parameter max-alt-num: lim. 1 <= 20? OK! Limit check parameter gen-min-indel-alt-allele-freq: lim. 0 <= 0.01 <= lim. 1? OK! Limit check parameter tag-trim-method: lim. 0 <= 1 <= lim. 1? OK! Limit check parameter min-tag-fam-size: lim. 1 <= 3? OK! Limit check parameter indel-func-size-offset: lim. 0 <= 0? OK! TargetsManager: Loaded targets file OCP_Target.bed TargetsManager: 2530 target(s) (1544 after merging) Merged 0 unique comment lines into combined BAM header. Encountered 4 duplicate comments. SampleManager: Found 1 read group(s) and 1 sample(s). SampleManager: Primary sample "Sample 1" (set via -g) 1 read group(s) Found a total of 1 different flow orders of max flow lengths: 500 Recalibration was detected from comment lines in bam file(s): 1 unique blocks of recalibration info detected. TVC: Parsing Indel Assembly parameters. read-limit = 1000000 (integer, builtin default) kmer-len = 19 (integer, parameters json file) min-var-count = 5 (integer, parameters json file) short-suffix-match = 5 (integer, parameters json file) min-indel-size = 4 (integer, parameters json file) max-hp-length = 8 (integer, parameters json file) min-var-freq = 0.15 (double, parameters json file) min-var-score = 10 (double, builtin default) relative-strand-bias = 0.8 (double, parameters json file) output-mnv = 0 (integer, parameters json file) ERROR: two reads having the same run_id and X/Y: WY9V0:01422:02734 and WY9V0:01422:02734 Maybe multiple runs with the same run id, please fix that [ Wed 2018-03-21 14:00:13 CST ] ERROR: command failed with status 1 `

Beside,i don't want use GATK Mutect2 or some else tools,i just want to use TS.

iontorrent / TS

How To Call Somatic variants using TS? #40