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/* Copyright (C) 2012 Ion Torrent Systems, Inc. All Rights Reserved */
#include "ExtendParameters.h"
#include <fstream>
#include <iomanip>
#include <cstdlib>
#include <iostream>
#include <string>
#include <sys/stat.h>
#include <errno.h>
using namespace std;
void VariantCallerHelp() {
printf("Usage: tvc [options]\n");
printf("\n");
printf("General options:\n");
printf(" -h,--help print this help message and exit\n");
printf(" -v,--version print version and exit\n");
printf(" -n,--num-threads INT number of worker threads [2]\n");
printf(" -N,--num-variants-per-thread INT worker thread batch size [500]\n");
printf(" --parameters-file FILE json file with algorithm control parameters [optional]\n");
printf("\n");
printf("Inputs:\n");
printf(" -r,--reference FILE reference fasta file [required]\n");
printf(" -b,--input-bam FILE bam file with mapped reads [required]\n");
printf(" -g,--sample-name STRING sample for which variants are called (In case of input BAM files with multiple samples) [optional if there is only one sample]\n");
printf(" --force-sample-name STRING force all read groups to have this sample name [off]\n");
printf(" -t,--target-file FILE only process targets in this bed file [optional]\n");
printf(" --trim-ampliseq-primers on/off match reads to targets and trim the ends that reach outside them [off]\n");
printf(" -D,--downsample-to-coverage INT ?? [2000]\n");
printf(" --model-file FILE HP recalibration model input file.\n");
printf(" --recal-model-hp-thres INT Lower threshold for HP recalibration.\n");
printf("\n");
printf("Outputs:\n");
printf(" -O,--output-dir DIRECTORY base directory for all output files [current dir]\n");
printf(" -o,--output-vcf FILE vcf file with variant calling results [required]\n");
printf(" --suppress-reference-genotypes on/off write reference calls into the filtered variants vcf [on]\n");
printf(" --suppress-no-calls on/off write filtered variants into the filtered variants vcf [on]\n");
printf(" --suppress-nocall-genotypes on/off do not report a genotype for filtered variants [on]\n");
printf("\n");
printf("Variant candidate generation (FreeBayes):\n");
printf(" --allow-snps on/off allow generation of snp candidates [on]\n");
printf(" --allow-indels on/off allow generation of indel candidates [on]\n");
printf(" --allow-mnps on/off allow generation of mnp candidates [on]\n");
printf(" --allow-complex on/off allow generation of block substitution candidates [off]\n");
printf(" --max-complex-gap INT maximum number of reference alleles between two alternate alleles to allow merging of the alternate alleles [1]\n");
printf(" -m,--use-best-n-alleles INT maximum number of snp alleles [2]\n");
printf(" -M,--min-mapping-qv INT do not use reads with mapping quality below this [4]\n");
printf(" -U,--read-snp-limit INT do not use reads with number of snps above this [10]\n");
printf(" -z,--read-max-mismatch-fraction FLOAT do not use reads with fraction of mismatches above this [1.0]\n");
printf(" --gen-min-alt-allele-freq FLOAT minimum required alt allele frequency to generate a candidate [0.2]\n");
printf(" --gen-min-indel-alt-allele-freq FLOAT minimum required alt allele frequency to generate a homopolymer indel candidate [0.2]\n");
printf(" --gen-min-coverage INT minimum required coverage to generate a candidate [6]\n");
printf("\n");
printf("External variant candidates:\n");
printf(" -c,--input-vcf FILE vcf.gz file (+.tbi) with additional candidate variant locations and alleles [optional]\n");
printf(" --process-input-positions-only on/off only generate candidates at locations from input-vcf [off]\n");
printf(" --use-input-allele-only on/off only consider provided alleles for locations in input-vcf [off]\n");
printf("\n");
printf("Variant candidate scoring options:\n");
printf(" --min-delta-for-flow FLOAT minimum prediction delta for scoring flows [0.1]\n");
printf(" --max-flows-to-test INT maximum number of scoring flows [10]\n");
printf(" --outlier-probability FLOAT probability for outlier reads [0.01]\n");
printf(" --heavy-tailed INT degrees of freedom in t-dist modeling signal residual heavy tail [3]\n");
printf(" --suppress-recalibration on/off Suppress homopolymer recalibration [on].\n");
printf(" --do-snp-realignment on/off Realign reads in the vicinity of candidate snp variants [on].\n");
printf(" --do-mnp-realignment on/off Realign reads in the vicinity of candidate mnp variants [do-snp-realignment].\n");
printf(" --realignment-threshold FLOAT Max. allowed fraction of reads where realignment causes an alignment change [1.0].\n");
printf("\n");
printf("Advanced variant candidate scoring options:\n");
#ifdef __SSE3__
printf(" --use-sse-basecaller on/off Switch to use the vectorized version of the basecaller [on].\n");
#else
printf(" --use-sse-basecaller on/off Switch to use the vectorized version of the basecaller [off].\n");
#endif
printf(" --resolve-clipped-bases on/off If 'true', the basecaller is used to solve soft clipped bases [off].\n");
printf(" --prediction-precision FLOAT prior weight in bias estimator [30.0]\n");
printf(" --shift-likelihood-penalty FLOAT penalize log-likelihood for solutions involving large systematic bias [0.3]\n");
printf(" --minimum-sigma-prior FLOAT prior variance per data point, constant [0.085]\n");
printf(" --slope-sigma-prior FLOAT prior rate of increase of variance over minimum by signal [0.0084]\n");
printf(" --sigma-prior-weight FLOAT weight of prior estimate of variance compared to observations [1.0]\n");
printf(" --k-zero FLOAT variance increase for adding systematic bias [3.0]\n");
printf(" --sse-relative-safety-level FLOAT dampen strand bias detection for SSE events for low coverage [0.025]\n");
printf(" --tune-sbias FLOAT dampen strand bias detection for low coverage [0.01]\n");
printf(" --max-detail-level INT number of evaluated frequencies for a given hypothesis, reduce for very high coverage, set to zero to disable this option [0]\n");
printf("\n");
printf("Variant filtering:\n");
// Filters depending on the variant type
printf(" -k,--snp-min-coverage INT filter out snps with total coverage below this [6]\n");
printf(" -C,--snp-min-cov-each-strand INT filter out snps with coverage on either strand below this [0]\n");
printf(" -B,--snp-min-variant-score FLOAT filter out snps with QUAL score below this [10.0]\n");
printf(" -s,--snp-strand-bias FLOAT filter out snps with strand bias above this [0.95] given pval < snp-strand-bias-pval\n");
printf(" --snp-strand-bias-pval FLOAT filter out snps with pval below this [1.0] given strand bias > snp-strand-bias\n");
// printf(" -s,--snp-strand-bias FLOAT filter out snps with strand bias above this [0.95]\n");
printf(" -A,--snp-min-allele-freq FLOAT minimum required alt allele frequency for non-reference snp calls [0.2]\n");
printf(" --mnp-min-coverage INT filter out mnps with total coverage below this [snp-min-coverage]\n");
printf(" --mnp-min-cov-each-strand INT filter out mnps with coverage on either strand below this, [snp-min-cov-each-strand]\n");
printf(" --mnp-min-variant-score FLOAT filter out mnps with QUAL score below this [snp-min-variant-score]\n");
printf(" --mnp-strand-bias FLOAT filter out mnps with strand bias above this [snp-strand-bias] given pval < mnp-strand-bias-pval\n");
printf(" --mnp-strand-bias-pval FLOAT filter out mnps with pval below this [snp-strand-bias-pval] given strand bias > mnp-strand-bias\n");
printf(" --mnp-min-allele-freq FLOAT minimum required alt allele frequency for non-reference mnp calls [snp-min-allele-freq]\n");
printf(" --indel-min-coverage INT filter out indels with total coverage below this [30]\n");
printf(" --indel-min-cov-each-strand INT filter out indels with coverage on either strand below this [1]\n");
printf(" --indel-min-variant-score FLOAT filter out indels with QUAL score below this [10.0]\n");
printf(" -S,--indel-strand-bias FLOAT filter out indels with strand bias above this [0.95] given pval < indel-strand-bias-pval\n");
printf(" --indel-strand-bias-pval FLOAT filter out indels with pval below this [1.0] given strand bias > indel-strand-bias\n");
// printf(" -S,--indel-strand-bias FLOAT filter out indels with strand bias above this [0.85]\n");
printf(" --indel-min-allele-freq FLOAT minimum required alt allele frequency for non-reference indel call [0.2]\n");
printf(" --hotspot-min-coverage INT filter out hotspot variants with total coverage below this [6]\n");
printf(" --hotspot-min-cov-each-strand INT filter out hotspot variants with coverage on either strand below this [snp-min-cov-each-strand]\n");
printf(" --hotspot-min-variant-score FLOAT filter out hotspot variants with QUAL score below this [snp-min-variant-score]\n");
printf(" --hotspot-strand-bias FLOAT filter out hotspot variants with strand bias above this [0.95] given pval < hotspot-strand-bias-pval\n");
printf(" --hotspot-strand-bias-pval FLOAT filter out hotspot variants with pval below this [1.0] given strand bias > hotspot-strand-bias\n");
// printf(" --hotspot-strand-bias FLOAT filter out hotspot variants with strand bias above this [0.95]\n");
printf(" -H,--hotspot-min-allele-freq FLOAT minimum required alt allele frequency for non-reference hotspot variant call [0.2]\n");
// Filters not depending on the variant score
printf(" -L,--hp-max-length INT filter out indels in homopolymers above this [8]\n");
printf(" -e,--error-motifs FILE table of systematic error motifs and their error rates [optional]\n");
printf(" --sse-prob-threshold FLOAT filter out variants in motifs with error rates above this [0.2]\n");
printf(" --min-ratio-reads-non-sse-strand FLOAT minimum required alt allele frequency for variants with error motifs on opposite strand [0.2]\n");
printf(" --indel-as-hpindel on/off apply indel filters to non HP indels [off]\n");
// position-bias filter
printf("\nPosition bias variant filtering:\n");
printf(" --use-position-bias on/off enable the position bias filter [off]\n");
printf(" --position-bias FLOAT filter out variants with position bias relative to soft clip ends in reads > position-bias [0.75]\n");
printf(" --position-bias-pval FLOAT filter out if position bias above position-bias given pval < position-bias-pval [0.05]\n");
printf(" --position-bias-ref-fraction FLOAT skip position bias filter if (reference read count)/(reference + alt allele read count) <= to this [0.05]\n");
// These filters depend on scoring
printf("\nFilters that depend on scoring across alleles:\n");
printf(" --data-quality-stringency FLOAT minimum mean log-likelihood delta per read [4.0]\n");
printf(" --read-rejection-threshold FLOAT filter variants where large numbers of reads are rejected as outliers [0.5]\n");
printf(" --filter-unusual-predictions FLOAT posterior log likelihood threshold for accepting bias estimate [0.3]\n");
printf(" --filter-deletion-predictions FLOAT check post-evaluation systematic bias in deletions; a high value like 100 effectively turns off this filter [100.0]\n");
printf(" --filter-insertion-predictions FLOAT check post-evaluation systematic bias in insertions; a high value like 100 effectively turns off this filter [100.0]\n");
printf("\n");
printf(" --heal-snps on/off suppress in/dels not participating in diploid variant genotypes if the genotype contains a SNP or MNP [on].\n");
printf("\n");
printf("Debugging:\n");
printf(" -d,--debug INT (0/1/2) display extra debug messages [0]\n");
printf(" --do-json-diagnostic on/off (devel) dump internal state to json file (uses much more time/memory/disk) [off]\n");
printf(" --postprocessed-bam FILE (devel) save tvc-processed reads to an (unsorted) BAM file [optional]\n");
printf(" --do-minimal-diagnostic on/off (devel) provide minimal read information for called variants [off]\n");
printf(" --override-limits on/off (devel) disable limit-check on input parameters [off].\n");
printf("\n");
}
ControlCallAndFilters::ControlCallAndFilters() {
// all defaults handled by sub-filters
data_quality_stringency = 4.0f; // phred-score for this variant per read
read_rejection_threshold = 0.5f; // half the reads gone, filter this
use_position_bias = false;
position_bias_ref_fraction = 0.05; // FRO/(FRO+FAO)
position_bias = 0.75f; // position bias
position_bias_pval = 0.05f; // pval for observed > threshold
//xbias_tune = 0.005f;
sbias_tune = 0.5f;
downSampleCoverage = 2000;
RandSeed = 631;
// wanted by downstream
suppress_reference_genotypes = true;
suppress_nocall_genotypes = true;
suppress_no_calls = true;
heal_snps = true;
}
ProgramControlSettings::ProgramControlSettings() {
nVariantsPerThread = 1000;
nThreads = 1;
DEBUG = 0;
#ifdef __SSE3__
use_SSE_basecaller = true;
#else
use_SSE_basecaller = false;
#endif
rich_json_diagnostic = false;
minimal_diagnostic = false;
json_plot_dir = "./json_diagnostic/";
inputPositionsOnly = false;
suppress_recalibration = true;
resolve_clipped_bases = false;
}
int GetParamsInt(Json::Value& json, const string& key, int default_value) {
if (not json.isMember(key))
return default_value;
if (json[key].isString())
return atoi(json[key].asCString());
return json[key].asInt();
}
double GetParamsDbl(Json::Value& json, const string& key, double default_value) {
if (not json.isMember(key))
return default_value;
if (json[key].isString())
return atof(json[key].asCString());
return json[key].asDouble();
}
int RetrieveParameterInt(OptArgs &opts, Json::Value& json, char short_name, const string& long_name_hyphens, int default_value)
{
string long_name_underscores = long_name_hyphens;
for (unsigned int i = 0; i < long_name_underscores.size(); ++i)
if (long_name_underscores[i] == '-')
long_name_underscores[i] = '_';
int value = default_value;
string source = "builtin default";
if (json.isMember(long_name_underscores)) {
if (json[long_name_underscores].isString())
value = atoi(json[long_name_underscores].asCString());
else
value = json[long_name_underscores].asInt();
source = "parameters json file";
}
if (opts.HasOption(short_name, long_name_hyphens)) {
value = opts.GetFirstInt(short_name, long_name_hyphens, value);
source = "command line option";
}
cout << setw(35) << long_name_hyphens << " = " << setw(10) << value << " (integer, " << source << ")" << endl;
return value;
}
double RetrieveParameterDouble(OptArgs &opts, Json::Value& json, char short_name, const string& long_name_hyphens, double default_value)
{
string long_name_underscores = long_name_hyphens;
for (unsigned int i = 0; i < long_name_underscores.size(); ++i)
if (long_name_underscores[i] == '-')
long_name_underscores[i] = '_';
double value = default_value;
string source = "builtin default";
if (json.isMember(long_name_underscores)) {
if (json[long_name_underscores].isString())
value = atof(json[long_name_underscores].asCString());
else
value = json[long_name_underscores].asDouble();
source = "parameters json file";
}
if (opts.HasOption(short_name, long_name_hyphens)) {
value = opts.GetFirstDouble(short_name, long_name_hyphens, value);
source = "command line option";
}
cout << setw(35) << long_name_hyphens << " = " << setw(10) << value << " (double, " << source << ")" << endl;
return value;
}
bool RetrieveParameterBool(OptArgs &opts, Json::Value& json, char short_name, const string& long_name_hyphens, bool default_value)
{
string long_name_underscores = long_name_hyphens;
for (unsigned int i = 0; i < long_name_underscores.size(); ++i)
if (long_name_underscores[i] == '-')
long_name_underscores[i] = '_';
bool value = default_value;
string source = "builtin default";
if (json.isMember(long_name_underscores)) {
if (json[long_name_underscores].isString())
value = atoi(json[long_name_underscores].asCString());
else
value = json[long_name_underscores].asInt();
source = "parameters json file";
}
if (opts.HasOption(short_name, long_name_hyphens)) {
value = opts.GetFirstBoolean(short_name, long_name_hyphens, value);
source = "command line option";
}
cout << setw(35) << long_name_hyphens << " = " << setw(10) << (value ? "true" : "false") << " (boolean, " << source << ")" << endl;
return value;
}
// =============================================================================
void EnsembleEvalTuningParameters::SetOpts(OptArgs &opts, Json::Value& tvc_params) {
max_flows_to_test = RetrieveParameterInt (opts, tvc_params, '-', "max-flows-to-test", 10);
min_delta_for_flow = RetrieveParameterDouble(opts, tvc_params, '-', "min-delta-for-flow", 0.1);
prediction_precision = RetrieveParameterDouble(opts, tvc_params, '-', "prediction-precision", 30.0);
outlier_prob = RetrieveParameterDouble(opts, tvc_params, '-', "outlier-probability", 0.01);
germline_prior_strength = RetrieveParameterDouble(opts, tvc_params, '-', "germline-prior-strength", 0.0f);
heavy_tailed = RetrieveParameterInt (opts, tvc_params, '-', "heavy-tailed", 3);
filter_unusual_predictions = RetrieveParameterDouble(opts, tvc_params, '-', "filter-unusual-predictions", 0.3f);
soft_clip_bias_checker = RetrieveParameterDouble(opts, tvc_params, '-', "soft-clip-bias-checker", 0.1f);
filter_deletion_bias = RetrieveParameterDouble(opts, tvc_params, '-', "filter-deletion-predictions", 100.0f);
filter_insertion_bias = RetrieveParameterDouble(opts, tvc_params, '-', "filter-insertion-predictions", 100.0f);
max_detail_level = RetrieveParameterInt(opts, tvc_params, '-', "max-detail-level", 0);
// shouldn't majorly affect anything, but still expose parameters for completeness
pseudo_sigma_base = RetrieveParameterDouble(opts, tvc_params, '-', "shift-likelihood-penalty", 0.3f);
magic_sigma_base = RetrieveParameterDouble(opts, tvc_params, '-', "minimum-sigma-prior", 0.085f);
magic_sigma_slope = RetrieveParameterDouble(opts, tvc_params, '-', "slope-sigma-prior", 0.0084f);
sigma_prior_weight = RetrieveParameterDouble(opts, tvc_params, '-', "sigma-prior-weight", 1.0f);
k_zero = RetrieveParameterDouble(opts, tvc_params, '-', "k-zero", 3.0f); // add variance from cluster shifts
}
void EnsembleEvalTuningParameters::CheckParameterLimits() {
CheckParameterLowerUpperBound<int> ("max-flows-to-test", max_flows_to_test, 1, 100);
CheckParameterLowerUpperBound<float>("min-delta-for-flow", min_delta_for_flow, 0.01f, 0.5f);
CheckParameterLowerBound<float> ("prediction-precision", prediction_precision, 0.1f);
CheckParameterLowerUpperBound<float>("outlier-probability", outlier_prob, 0.0f, 1.0f);
CheckParameterLowerUpperBound<float>("germline-prior-strength", germline_prior_strength, 0.0f, 1000.0f);
CheckParameterLowerBound<int> ("heavy-tailed", heavy_tailed, 1);
CheckParameterLowerBound<float> ("filter-unusual-predictions", filter_unusual_predictions, 0.0f);
CheckParameterLowerUpperBound<float>("soft-clip-bias-checker", soft_clip_bias_checker, 0.0f, 1.0f);
CheckParameterLowerBound<float> ("filter-deletion-predictions", filter_deletion_bias, 0.0f);
CheckParameterLowerBound<float> ("filter-insertion-predictions", filter_insertion_bias, 0.0f);
CheckParameterLowerUpperBound<int> ("max-detail-level", max_detail_level, 0, 10000);
CheckParameterLowerBound<float> ("shift-likelihood-penalty", pseudo_sigma_base, 0.01f);
CheckParameterLowerBound<float> ("minimum-sigma-prior", magic_sigma_base, 0.01f);
CheckParameterLowerBound<float> ("slope-sigma-prior", magic_sigma_slope, 0.0f);
CheckParameterLowerBound<float> ("sigma-prior-weight", sigma_prior_weight, 0.01f);
CheckParameterLowerBound<float> ("k-zero", k_zero, 0.0f);
}
// ============================================================================
void ClassifyFilters::SetOpts(OptArgs &opts, Json::Value & tvc_params) {
hp_max_length = RetrieveParameterInt (opts, tvc_params, 'L', "hp-max-length", 8);
sseProbThreshold = RetrieveParameterDouble(opts, tvc_params, '-', "sse-prob-threshold", 0.2);
minRatioReadsOnNonErrorStrand = RetrieveParameterDouble(opts, tvc_params, '-', "min-ratio-reads-non-sse-strand", 0.2);
sse_relative_safety_level = RetrieveParameterDouble(opts, tvc_params, '-', "sse-relative-safety-level", 0.025);
// min ratio of reads supporting variant on non-sse strand for variant to be called
do_snp_realignment = RetrieveParameterBool (opts, tvc_params, '-', "do-snp-realignment", true);
do_mnp_realignment = RetrieveParameterBool (opts, tvc_params, '-', "do-mnp-realignment", do_snp_realignment);
realignment_threshold = RetrieveParameterDouble(opts, tvc_params, '-', "realignment-threshold", 1.0);
indel_as_hpindel = RetrieveParameterBool (opts, tvc_params, '-', "indel-as-hpindel", false);
}
void ClassifyFilters::CheckParameterLimits() {
CheckParameterLowerBound<int> ("hp-max-length", hp_max_length, 1);
CheckParameterLowerUpperBound<float>("sse-prob-threshold", sseProbThreshold, 0.0f, 1.0f);
CheckParameterLowerUpperBound<float>("min-ratio-reads-non-sse-strand", minRatioReadsOnNonErrorStrand, 0.0f, 1.0f);
CheckParameterLowerUpperBound<float>("sse-relative-safety-level", sse_relative_safety_level, 0.0f, 1.0f);
CheckParameterLowerUpperBound<float>("realignment-threshold", realignment_threshold, 0.0f, 1.0f);
}
// ===========================================================================
void ControlCallAndFilters::CheckParameterLimits() {
filter_variant.CheckParameterLimits();
CheckParameterLowerBound<float> ("data-quality-stringency", data_quality_stringency, 0.0f);
CheckParameterLowerUpperBound<float>("read-rejection-threshold", read_rejection_threshold, 0.0f, 1.0f);
CheckParameterLowerUpperBound<int> ("downsample-to-coverage", downSampleCoverage, 20, 100000);
CheckParameterLowerUpperBound<float>("position-bias-ref-fraction",position_bias_ref_fraction, 0.0f, 1.0f);
CheckParameterLowerUpperBound<float>("position-bias", position_bias, 0.0f, 1.0f);
CheckParameterLowerUpperBound<float>("position-bias-pval", position_bias_pval, 0.0f, 1.0f);
// CheckParameterLowerUpperBound<float>("tune-xbias", xbias_tune, 0.001f, 1000.0f);
CheckParameterLowerUpperBound<float>("tune-sbias", sbias_tune, 0.001f, 1000.0f);
CheckParameterLowerBound<int> ("snp-min-cov-each-strand", filter_snps.min_cov_each_strand, 0);
CheckParameterLowerBound<float> ("snp-min-variant-score", filter_snps.min_quality_score, 0.0f);
CheckParameterLowerUpperBound<float>("snp-min-allele-freq", filter_snps.min_allele_freq, 0.0f, 1.0f);
CheckParameterLowerBound<int> ("snp-min-coverage", filter_snps.min_cov, 0);
CheckParameterLowerUpperBound<float>("snp-strand-bias", filter_snps.strand_bias_threshold, 0.5f, 1.0f);
CheckParameterLowerUpperBound<float>("snp-strand-bias-pval", filter_snps.strand_bias_pval_threshold, 0.0f, 1.0f);
// CheckParameterLowerBound<float> ("snp-beta-bias", filter_snps.beta_bias_filter, 0.0f);
CheckParameterLowerBound<int> ("mnp-min-cov-each-strand", filter_mnp.min_cov_each_strand, 0);
CheckParameterLowerBound<float> ("mnp-min-variant-score", filter_mnp.min_quality_score, 0.0f);
CheckParameterLowerUpperBound<float>("mnp-min-allele-freq", filter_mnp.min_allele_freq, 0.0f, 1.0f);
CheckParameterLowerBound<int> ("mnp-min-coverage", filter_mnp.min_cov, 0);
CheckParameterLowerUpperBound<float>("mnp-strand-bias", filter_mnp.strand_bias_threshold, 0.5f, 1.0f);
CheckParameterLowerUpperBound<float>("mnp-strand-bias-pval", filter_mnp.strand_bias_pval_threshold, 0.0f, 1.0f);
CheckParameterLowerBound<int> ("indel-min-cov-each-strand", filter_hp_indel.min_cov_each_strand, 0);
CheckParameterLowerBound<float> ("indel-min-variant-score", filter_hp_indel.min_quality_score, 0.0f);
CheckParameterLowerUpperBound<float>("indel-min-allele-freq", filter_hp_indel.min_allele_freq, 0.0f, 1.0f);
CheckParameterLowerBound<int> ("indel-min-coverage", filter_hp_indel.min_cov, 0);
CheckParameterLowerUpperBound<float>("indel-strand-bias", filter_hp_indel.strand_bias_threshold, 0.5f, 1.0f);
CheckParameterLowerUpperBound<float>("indel-strand-bias-pval", filter_hp_indel.strand_bias_pval_threshold, 0.0f, 1.0f);
// CheckParameterLowerBound<float> ("indel-beta-bias", filter_hp_indel.beta_bias_filter, 0.0f);
CheckParameterLowerBound<int> ("hotspot-min-cov-each-strand", filter_hotspot.min_cov_each_strand, 0);
CheckParameterLowerBound<float> ("hotspot-min-variant-score", filter_hotspot.min_quality_score, 0.0f);
CheckParameterLowerUpperBound<float>("hotspot-min-allele-freq", filter_hotspot.min_allele_freq, 0.0f, 1.0f);
CheckParameterLowerBound<int> ("hotspot-min-coverage", filter_hotspot.min_cov, 0);
CheckParameterLowerUpperBound<float>("hotspot-strand-bias", filter_hotspot.strand_bias_threshold, 0.5f, 1.0f);
CheckParameterLowerUpperBound<float>("hotspot-strand-bias-pval", filter_hotspot.strand_bias_pval_threshold, 0.0f, 1.0f);
// CheckParameterLowerBound<float> ("hotspot-beta-bias", filter_hotspot.beta_bias_filter, 0.0f);
}
// ------------------------------------------------------
void ControlCallAndFilters::SetOpts(OptArgs &opts, Json::Value& tvc_params) {
filter_variant.SetOpts(opts, tvc_params);
RandSeed = 631; // Not exposed to user at this point
// catchall filter parameter to be used to filter any generic predictive model of quality
data_quality_stringency = RetrieveParameterDouble(opts, tvc_params, '-', "data-quality-stringency",4.0f);
// if we reject half the reads from evaluator, something badly wrong with this position
read_rejection_threshold = RetrieveParameterDouble(opts, tvc_params, '-', "read-rejection-threshold",0.5f);
use_position_bias = RetrieveParameterBool(opts, tvc_params, '-', "use-position-bias", false);
position_bias_ref_fraction = RetrieveParameterDouble(opts, tvc_params, '-', "position-bias-ref-fraction",0.05f);
position_bias = RetrieveParameterDouble(opts, tvc_params, '-', "position-bias",0.75f);
position_bias_pval = RetrieveParameterDouble(opts, tvc_params, '-', "position-bias-pval",0.05f);
downSampleCoverage = RetrieveParameterInt (opts, tvc_params, '-', "downsample-to-coverage", 2000);
//xbias_tune = RetrieveParameterDouble(opts, tvc_params, '-', "tune-xbias", 0.005f);
sbias_tune = RetrieveParameterDouble(opts, tvc_params, '-', "tune-sbias", 0.01f);
suppress_reference_genotypes = RetrieveParameterBool (opts, tvc_params, '-', "suppress-reference-genotypes", true);
suppress_nocall_genotypes = RetrieveParameterBool (opts, tvc_params, '-', "suppress-nocall-genotypes", true);
suppress_no_calls = RetrieveParameterBool (opts, tvc_params, '-', "suppress-no-calls", true);
heal_snps = RetrieveParameterBool (opts, tvc_params, '-', "heal-snps", true);
// SNPS are my usual variants
filter_snps.min_cov_each_strand = RetrieveParameterInt (opts, tvc_params, 'C', "snp-min-cov-each-strand", 0);
filter_snps.min_quality_score = RetrieveParameterDouble(opts, tvc_params, 'B', "snp-min-variant-score", 10.0);
filter_snps.min_allele_freq = RetrieveParameterDouble(opts, tvc_params, 'A', "snp-min-allele-freq", 0.2);
filter_snps.min_cov = RetrieveParameterInt (opts, tvc_params, 'k', "snp-min-coverage", 6);
filter_snps.strand_bias_threshold = RetrieveParameterDouble(opts, tvc_params, 's', "snp-strand-bias", 0.95);
filter_snps.strand_bias_pval_threshold= RetrieveParameterDouble(opts, tvc_params, 's', "snp-strand-bias-pval", 1.0);
filter_mnp.min_cov_each_strand = RetrieveParameterInt (opts, tvc_params, '-', "mnp-min-cov-each-strand", filter_snps.min_cov_each_strand);
filter_mnp.min_quality_score = RetrieveParameterDouble(opts, tvc_params, '-', "mnp-min-variant-score", filter_snps.min_quality_score);
filter_mnp.min_allele_freq = RetrieveParameterDouble(opts, tvc_params, 'H', "mnp-min-allele-freq", filter_snps.min_allele_freq);
filter_mnp.min_cov = RetrieveParameterInt (opts, tvc_params, '-', "mnp-min-coverage", filter_snps.min_cov);
filter_mnp.strand_bias_threshold = RetrieveParameterDouble(opts, tvc_params, '-', "mnp-strand-bias", filter_snps.strand_bias_threshold);
filter_mnp.strand_bias_pval_threshold= RetrieveParameterDouble(opts, tvc_params, 's', "mnp-strand-bias-pval", filter_snps.strand_bias_pval_threshold);
// hp_indels are more complex
filter_hp_indel.min_cov_each_strand = RetrieveParameterInt (opts, tvc_params, '-', "indel-min-cov-each-strand", 1);
filter_hp_indel.min_quality_score = RetrieveParameterDouble(opts, tvc_params, '-', "indel-min-variant-score", 10.0);
filter_hp_indel.min_allele_freq = RetrieveParameterDouble(opts, tvc_params, '-', "indel-min-allele-freq", 0.2);
filter_hp_indel.min_cov = RetrieveParameterInt (opts, tvc_params, '-', "indel-min-coverage", 15);
filter_hp_indel.strand_bias_threshold = RetrieveParameterDouble(opts, tvc_params, 'S', "indel-strand-bias", 0.85);
filter_hp_indel.strand_bias_pval_threshold= RetrieveParameterDouble(opts, tvc_params, 's', "indel-strand-bias-pval", 1.0);
// derive hotspots by default from SNPs
// override from command line or json
filter_hotspot.min_cov_each_strand = RetrieveParameterInt (opts, tvc_params, '-', "hotspot-min-cov-each-strand", filter_snps.min_cov_each_strand);
filter_hotspot.min_quality_score = RetrieveParameterDouble(opts, tvc_params, '-', "hotspot-min-variant-score", filter_snps.min_quality_score);
filter_hotspot.min_allele_freq = RetrieveParameterDouble(opts, tvc_params, 'H', "hotspot-min-allele-freq", filter_snps.min_allele_freq);
filter_hotspot.min_cov = RetrieveParameterInt (opts, tvc_params, '-', "hotspot-min-coverage", filter_snps.min_cov);
filter_hotspot.strand_bias_threshold = RetrieveParameterDouble(opts, tvc_params, '-', "hotspot-strand-bias", filter_snps.strand_bias_threshold);
filter_hotspot.strand_bias_pval_threshold= RetrieveParameterDouble(opts, tvc_params, 's', "hotspot-strand-bias-pval", filter_snps.strand_bias_pval_threshold);
}
// =============================================================================
void ProgramControlSettings::CheckParameterLimits() {
CheckParameterLowerUpperBound<int> ("num-threads", nThreads, 1, 128);
CheckParameterLowerUpperBound<int> ("num-variants-per-thread", nVariantsPerThread, 1, 10000);
}
void ProgramControlSettings::SetOpts(OptArgs &opts, Json::Value &tvc_params) {
DEBUG = opts.GetFirstInt ('d', "debug", 0);
nThreads = RetrieveParameterInt (opts, tvc_params, 'n', "num-threads", 12);
nVariantsPerThread = RetrieveParameterInt (opts, tvc_params, 'N', "num-variants-per-thread", 250);
#ifdef __SSE3__
use_SSE_basecaller = RetrieveParameterBool (opts, tvc_params, '-', "use-sse-basecaller", true);
#else
use_SSE_basecaller = RetrieveParameterBool (opts, tvc_params, '-', "use-sse-basecaller", false);
#endif
// decide diagnostic
rich_json_diagnostic = RetrieveParameterBool (opts, tvc_params, '-', "do-json-diagnostic", false);
minimal_diagnostic = RetrieveParameterBool (opts, tvc_params, '-', "do-minimal-diagnostic", false);
inputPositionsOnly = RetrieveParameterBool (opts, tvc_params, '-', "process-input-positions-only", false);
suppress_recalibration = RetrieveParameterBool (opts, tvc_params, '-', "suppress-recalibration", true);
resolve_clipped_bases = RetrieveParameterBool (opts, tvc_params, '-', "resolve-clipped-bases", false);
}
// ===========================================================================
bool ExtendParameters::ValidateAndCanonicalizePath(string &path)
{
char *real_path = realpath (path.c_str(), NULL);
if (real_path == NULL) {
perror(path.c_str());
exit(EXIT_FAILURE);
}
path = real_path;
free(real_path);
return true;
}
int mkpath(std::string s,mode_t mode)
{
size_t pre=0,pos;
std::string dir;
int mdret = 0;
if(s[s.size()-1]!='/'){
// force trailing / so we can handle everything in loop
s+='/';
}
while((pos=s.find_first_of('/',pre))!=std::string::npos){
dir=s.substr(0,pos++);
pre=pos;
if(dir.size()==0) continue; // if leading / first time is 0 length
if((mdret=mkdir(dir.c_str(),mode)) && errno!=EEXIST){
return mdret;
}
}
return mdret;
}
void ExtendParameters::SetupFileIO(OptArgs &opts) {
// freeBayes slot
fasta = opts.GetFirstString('r', "reference", "");
if (fasta.empty()) {
cerr << "Fatal ERROR: Reference file not specified via -r" << endl;
exit(1);
}
ValidateAndCanonicalizePath(fasta);
// freeBayes slot
variantPriorsFile = opts.GetFirstString('c', "input-vcf", "");
if (variantPriorsFile.empty()) {
cerr << "INFO: No input VCF (Hotspot) file specified via -c,--input-vcf" << endl;
}
else
ValidateAndCanonicalizePath(variantPriorsFile);
sseMotifsFileName = opts.GetFirstString('e', "error-motifs", "");
sseMotifsProvided = true;
if (sseMotifsFileName.empty()) {
sseMotifsProvided = false;
cerr << "INFO: Systematic error motif file not specified via -e" << endl;
}
else
ValidateAndCanonicalizePath(sseMotifsFileName);
opts.GetOption(bams, "", 'b', "input-bam");
if (bams.empty()) {
cerr << "FATAL ERROR: BAM file not specified via -b" << endl;
exit(-1);
}
for (unsigned int i_bam = 0; i_bam < bams.size(); ++i_bam)
ValidateAndCanonicalizePath(bams[i_bam]);
outputDir = opts.GetFirstString('O', "output-dir", ".");
mkpath(outputDir, S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH);
ValidateAndCanonicalizePath(outputDir);
outputFile = opts.GetFirstString('o', "output-vcf", "");
if (outputFile.empty()) {
cerr << "Fatal ERROR: Output VCF filename not specified via -o" << endl;
exit(1);
}
// Are those file names?
postprocessed_bam = opts.GetFirstString('-', "postprocessed-bam", "");
sampleName = opts.GetFirstString('g', "sample-name", "");
force_sample_name = opts.GetFirstString('-', "force-sample-name", "");
}
// ------------------------------------------------------------
void ExtendParameters::SetFreeBayesParameters(OptArgs &opts, Json::Value& fb_params) {
// FreeBayes parameters
// primarily used in candidate generation
targets = opts.GetFirstString('t', "target-file", "");
trim_ampliseq_primers = opts.GetFirstBoolean('-', "trim-ampliseq-primers", false);
if (targets.empty() and trim_ampliseq_primers) {
cerr << "ERROR: --trim-ampliseq-primers enabled but no --target-file provided" << endl;
exit(1);
}
allowIndels = RetrieveParameterBool (opts, fb_params, '-', "allow-indels", true);
allowSNPs = RetrieveParameterBool (opts, fb_params, '-', "allow-snps", true);
allowMNPs = RetrieveParameterBool (opts, fb_params, '-', "allow-mnps", true);
allowComplex = RetrieveParameterBool (opts, fb_params, '-', "allow-complex", false);
// deprecated:
// leftAlignIndels = RetrieveParameterBool (opts, fb_params, '-', "left-align-indels", false);
RetrieveParameterBool (opts, fb_params, '-', "left-align-indels", false);
//useBestNAlleles = 0;
useBestNAlleles = RetrieveParameterInt (opts, fb_params, 'm', "use-best-n-alleles", 2);
onlyUseInputAlleles = RetrieveParameterBool (opts, fb_params, '-', "use-input-allele-only", false);
min_mapping_qv = RetrieveParameterInt (opts, fb_params, 'M', "min-mapping-qv", 4);
read_snp_limit = RetrieveParameterInt (opts, fb_params, 'U', "read-snp-limit", 10);
readMaxMismatchFraction = RetrieveParameterDouble(opts, fb_params, 'z', "read-max-mismatch-fraction", 1.0);
maxComplexGap = RetrieveParameterInt (opts, fb_params, '!', "max-complex-gap", 1);
// read from json or command line, otherwise default to snp frequency
minAltFraction = RetrieveParameterDouble(opts, fb_params, '-', "gen-min-alt-allele-freq", my_controls.filter_snps.min_allele_freq);
minCoverage = RetrieveParameterInt (opts, fb_params, '-', "gen-min-coverage", my_controls.filter_snps.min_cov);
minIndelAltFraction = RetrieveParameterDouble(opts, fb_params, '-', "gen-min-indel-alt-allele-freq", my_controls.filter_hp_indel.min_allele_freq);
//set up debug levels
if (program_flow.DEBUG > 0)
debug = true;
if (program_flow.inputPositionsOnly) {
processInputPositionsOnly = true;
}
if (variantPriorsFile.empty() && (processInputPositionsOnly || onlyUseInputAlleles) ) {
cerr << "ERROR: Parameter error - Process-input-positions-only: " << processInputPositionsOnly << " use-input-allele-only: " << onlyUseInputAlleles << " : Specified without Input VCF File " << endl;
exit(1);
}
}
// ------------------------------------------------------------
void ExtendParameters::ParametersFromJSON(OptArgs &opts, Json::Value &tvc_params, Json::Value &freebayes_params, Json::Value ¶ms_meta) {
string parameters_file = opts.GetFirstString('-', "parameters-file", "");
Json::Value parameters_json(Json::objectValue);
if (not parameters_file.empty()) {
ifstream in(parameters_file.c_str(), ifstream::in);
if (!in.good()) {
fprintf(stderr, "[tvc] FATAL ERROR: cannot open %s\n", parameters_file.c_str());
exit(-1);
}
in >> parameters_json;
in.close();
if (parameters_json.isMember("pluginconfig"))
parameters_json = parameters_json["pluginconfig"];
tvc_params = parameters_json.get("torrent_variant_caller", Json::objectValue);
freebayes_params = parameters_json.get("freebayes", Json::objectValue);
params_meta = parameters_json.get("meta", Json::objectValue);
}
}
// ------------------------------------------------------------
void ExtendParameters::CheckParameterLimits() {
// Check in the order they were set
my_controls.CheckParameterLimits();
my_eval_control.CheckParameterLimits();
program_flow.CheckParameterLimits();
// Checking FreeBayes parameters
CheckParameterLowerUpperBound<int> ("use-best-n-alleles", useBestNAlleles, 0, 20);
CheckParameterLowerBound<int> ("min-mapping-qv", min_mapping_qv, 0);
CheckParameterLowerBound<int> ("read-snp-limit", read_snp_limit, 0);
CheckParameterLowerUpperBound<float>("read-max-mismatch-fraction", readMaxMismatchFraction, 0.0f, 1.0f);
CheckParameterLowerUpperBound<long double>("gen-min-alt-allele-freq", minAltFraction, 0.0, 1.0);
CheckParameterLowerBound<int> ("gen-min-coverage", minCoverage, 0);
CheckParameterLowerUpperBound<long double>("gen-min-indel-alt-allele-freq", minIndelAltFraction, 0.0, 1.0);
}
// ------------------------------------------------------------
ExtendParameters::ExtendParameters(int argc, char** argv)
{
// i/o parameters:
fasta = ""; // -f --fasta-reference
targets = ""; // -t --targets
outputFile = "";
// operation parameters
trim_ampliseq_primers = false;
useDuplicateReads = false; // -E --use-duplicate-reads
useBestNAlleles = 0; // -n --use-best-n-alleles
allowIndels = true; // -i --no-indels
allowMNPs = true; // -X --no-mnps
allowSNPs = true; // -I --no-snps
allowComplex = false;
maxComplexGap = 3;
onlyUseInputAlleles = false;
min_mapping_qv = 0; // -m --min-mapping-quality
readMaxMismatchFraction = 1.0; // -z --read-max-mismatch-fraction
read_snp_limit = 10000000; // -$ --read-snp-limit
minAltFraction = 0.2; // require 20% of reads from sample to be supporting the same alternate to consider
minIndelAltFraction = 0.2;
minAltCount = 2; // require 2 reads in same sample call
minAltTotal = 1;
minCoverage = 0;
debug = false;
processInputPositionsOnly = false;
//OptArgs opts;
opts.ParseCmdLine(argc, (const char**)argv);
if (argc == 1) {
VariantCallerHelp();
exit(0);
}
if (opts.GetFirstBoolean('v', "version", false)) {
exit(0);
}
if (opts.GetFirstBoolean('h', "help", false)) {
VariantCallerHelp();
exit(0);
}
Json::Value tvc_params(Json::objectValue);
Json::Value freebayes_params(Json::objectValue);
Json::Value params_meta(Json::objectValue);
ParametersFromJSON(opts, tvc_params, freebayes_params, params_meta);
SetupFileIO(opts);
my_controls.SetOpts(opts, tvc_params);
my_eval_control.SetOpts(opts, tvc_params);
program_flow.SetOpts(opts, tvc_params);
// Dummy lines for HP recalibration
recal_model_file_name = opts.GetFirstString ('-', "model-file", "");
recalModelHPThres = opts.GetFirstInt('-', "recal-model-hp-thres", 4);
prefixExclusion = opts.GetFirstInt('-', "prefix-exclude", 6);
cerr << "prefix-exclude = " << prefixExclusion << endl;
SetFreeBayesParameters(opts, freebayes_params);
bool overrideLimits = RetrieveParameterBool (opts, tvc_params, '-', "override-limits", false);
params_meta_name = params_meta.get("name",string()).asString();
params_meta_details = params_meta.get("configuration", string()).asString();
string repository_id = params_meta.get("repository_id",string()).asString();
string ts_version = params_meta.get("ts_version","").asString();
if (not repository_id.empty()) {
if (not params_meta_details.empty())
params_meta_details += ", ";
params_meta_details += repository_id;
}
if (not ts_version.empty()) {
if (not params_meta_details.empty())
params_meta_details += ", ";
params_meta_details += "TS version: ";
params_meta_details += ts_version;
}
opts.CheckNoLeftovers();
// Sanity checks on input variables once all are set.
if (!overrideLimits)
CheckParameterLimits();
}
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