/* bam2bcf.c -- variant calling. Copyright (C) 2010-2012 Broad Institute. Copyright (C) 2012-2022 Genome Research Ltd. Author: Heng Li Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ #include #include #include #include #include #include #include #include #include "bam2bcf.h" extern void ks_introsort_uint32_t(size_t n, uint32_t a[]); #define CALL_DEFTHETA 0.83 #define DEF_MAPQ 20 #define CAP_DIST 25 bcf_callaux_t *bcf_call_init(double theta, int min_baseQ, int max_baseQ, int delta_baseQ) { bcf_callaux_t *bca; if (theta <= 0.) theta = CALL_DEFTHETA; bca = (bcf_callaux_t*) calloc(1, sizeof(bcf_callaux_t)); bca->capQ = 60; bca->openQ = 40; bca->extQ = 20; bca->tandemQ = 100; bca->min_baseQ = min_baseQ; bca->max_baseQ = max_baseQ; bca->delta_baseQ = delta_baseQ; bca->e = errmod_init(1. - theta); bca->min_frac = 0.002; bca->min_support = 1; bca->per_sample_flt = 0; bca->npos = 100; bca->ref_pos = (int*) malloc(bca->npos*sizeof(int)); bca->alt_pos = (int*) malloc(bca->npos*sizeof(int)); bca->iref_pos= (int*) malloc(bca->npos*sizeof(int)); bca->ialt_pos= (int*) malloc(bca->npos*sizeof(int)); bca->nqual = 60; bca->ref_mq = (int*) malloc(bca->nqual*sizeof(int)); bca->alt_mq = (int*) malloc(bca->nqual*sizeof(int)); bca->iref_mq = (int*) malloc(bca->nqual*sizeof(int)); bca->ialt_mq = (int*) malloc(bca->nqual*sizeof(int)); bca->ref_bq = (int*) malloc(bca->nqual*sizeof(int)); bca->alt_bq = (int*) malloc(bca->nqual*sizeof(int)); bca->fwd_mqs = (int*) malloc(bca->nqual*sizeof(int)); bca->rev_mqs = (int*) malloc(bca->nqual*sizeof(int)); return bca; } void bcf_iaux_destroy(bcf_callaux_t *bca); void bcf_call_destroy(bcf_callaux_t *bca) { if (bca == 0) return; bcf_iaux_destroy(bca); errmod_destroy(bca->e); if (bca->npos) { free(bca->ref_pos); free(bca->alt_pos); free(bca->iref_pos); free(bca->ialt_pos); bca->npos = 0; } free(bca->ref_mq); free(bca->alt_mq); free(bca->iref_mq); free(bca->ialt_mq); free(bca->ref_bq); free(bca->alt_bq); free(bca->fwd_mqs); free(bca->rev_mqs); bca->nqual = 0; free(bca->bases); free(bca->inscns); free(bca); } static int get_aux_nm(const bam_pileup1_t *p, int32_t qpos, int is_ref) { int64_t nm; const bam_pileup_cd *cd = &p->cd; if ( PLP_NM(cd) == -1 ) return -1; if ( PLP_NM(cd) == PLP_NM_UNSET ) { // todo: make this localized to be useful for long reads as well bam1_t *rec = p->b; uint8_t *nm_tag = bam_aux_get(rec, "NM"); if ( !nm_tag ) { PLP_NM(cd) = -1; return -1; } nm = bam_aux2i(nm_tag); // Count indels as single events, not as the number of inserted/deleted // bases (which is what NM does). Add soft clips as mismatches. int i; for (i=0; i < rec->core.n_cigar; i++) { int val = bam_get_cigar(rec)[i] & BAM_CIGAR_MASK; if ( val==BAM_CSOFT_CLIP ) { nm += bam_get_cigar(rec)[i] >> BAM_CIGAR_SHIFT; } else if ( val==BAM_CINS || val==BAM_CDEL ) { val = bam_get_cigar(rec)[i] >> BAM_CIGAR_SHIFT; if ( val > 1 ) nm -= val - 1; } } PLP_NM(cd) = nm; } else nm = PLP_NM(cd); // Take into account MNPs, 2% of de novo SNVs appear within 20bp of another de novo SNV // http://www.genome.org/cgi/doi/10.1101/gr.239756.118 nm -= is_ref ? 1 : 2; if ( nm < 0 ) nm = 0; if ( nm >= B2B_N_NM ) nm = B2B_N_NM - 1; return nm; } // position in the sequence with respect to the aligned part of the read static int get_position(const bam_pileup1_t *p, int *len, int *sc_len, int *sc_dist) { int i, j, edist = p->qpos + 1; int sc_left = 0, sc_right = 0; int sc_left_dist = -1, sc_right_dist = -1; // left end for (i = 0; i < p->b->core.n_cigar; i++) { int cig = bam_get_cigar(p->b)[i] & BAM_CIGAR_MASK; if (cig == BAM_CHARD_CLIP) continue; else if (cig == BAM_CSOFT_CLIP) sc_left += bam_get_cigar(p->b)[i] >> BAM_CIGAR_SHIFT; else break; } if (sc_left) sc_left_dist = p->qpos+1 - sc_left; edist -= sc_left; // right end for (j = p->b->core.n_cigar-1; j >= i; j--) { int cig = bam_get_cigar(p->b)[j] & BAM_CIGAR_MASK; if (cig == BAM_CHARD_CLIP) continue; else if (cig == BAM_CSOFT_CLIP) sc_right += bam_get_cigar(p->b)[j] >> BAM_CIGAR_SHIFT; else break; } if (sc_right) sc_right_dist = p->b->core.l_qseq - sc_right - p->qpos; // Distance to nearest soft-clips and length of that clip. if (sc_left_dist >= 0) { if (sc_right_dist < 0 || sc_left_dist < sc_right_dist) { *sc_len = sc_left; *sc_dist = sc_left_dist; } } else if (sc_right_dist >= 0) { *sc_len = sc_right; *sc_dist = sc_right_dist; } else { *sc_len = 0; *sc_dist = 0; } *len = p->b->core.l_qseq - sc_left - sc_right; return edist; } void bcf_callaux_clean(bcf_callaux_t *bca, bcf_call_t *call) { memset(bca->ref_pos,0,sizeof(int)*bca->npos); memset(bca->alt_pos,0,sizeof(int)*bca->npos); memset(bca->iref_pos,0,sizeof(int)*bca->npos); memset(bca->ialt_pos,0,sizeof(int)*bca->npos); memset(bca->ref_mq,0,sizeof(int)*bca->nqual); memset(bca->alt_mq,0,sizeof(int)*bca->nqual); memset(bca->iref_mq,0,sizeof(int)*bca->nqual); memset(bca->ialt_mq,0,sizeof(int)*bca->nqual); memset(bca->ref_bq,0,sizeof(int)*bca->nqual); memset(bca->alt_bq,0,sizeof(int)*bca->nqual); memset(bca->fwd_mqs,0,sizeof(int)*bca->nqual); memset(bca->rev_mqs,0,sizeof(int)*bca->nqual); if ( call->ADF ) memset(call->ADF,0,sizeof(int32_t)*(call->n+1)*B2B_MAX_ALLELES); if ( call->ADR ) memset(call->ADR,0,sizeof(int32_t)*(call->n+1)*B2B_MAX_ALLELES); if ( call->SCR ) memset(call->SCR,0,sizeof(*call->SCR)*(call->n+1)); if ( call->SCR ) memset(call->SCR,0,sizeof(*call->SCR)*(call->n+1)); if ( bca->fmt_flag&B2B_FMT_NMBZ ) { memset(call->ref_nm,0,sizeof(*call->ref_nm)*(call->n+1)*B2B_N_NM); memset(call->alt_nm,0,sizeof(*call->alt_nm)*(call->n+1)*B2B_N_NM); } else { memset(call->ref_nm,0,sizeof(*call->ref_nm)*B2B_N_NM); memset(call->alt_nm,0,sizeof(*call->alt_nm)*B2B_N_NM); } memset(call->QS,0,sizeof(*call->QS)*call->n*B2B_MAX_ALLELES); memset(bca->ref_scl, 0, 100*sizeof(int)); memset(bca->alt_scl, 0, 100*sizeof(int)); memset(bca->iref_scl, 0, 100*sizeof(int)); memset(bca->ialt_scl, 0, 100*sizeof(int)); int i; for (i=0; i<2; i++) bca->nnm[i] = 0; for (i=0; i<2; i++) bca->nm[i] = 0; } /* Notes: - Called from bam_plcmd.c by mpileup. Amongst other things, sets the bcf_callret1_t.QS frequencies which are carried over via bcf_call_combine and bcf_call2bcf to the output BCF as the INFO/QS and FMT/QS annotations. Later it's used for multiallelic calling by `call -m`, `call -mG` and `+trio-dnm`. - ref_base is the 4-bit representation of the reference base. It is negative if we are looking at an indel. */ /* * This function is called once for each sample. * _n is number of pilesups pl contributing reads to this sample * pl is pointer to array of _n pileups (one pileup per read) * ref_base is the 4-bit representation of the reference base. It is negative if we are looking at an indel. * bca is the settings to perform calls across all samples * r is the returned value of the call */ int bcf_call_glfgen(int _n, const bam_pileup1_t *pl, int ref_base, bcf_callaux_t *bca, bcf_callret1_t *r) { int i, n, ref4, is_indel, ori_depth = 0; // clean from previous run r->ori_depth = 0; r->mq0 = 0; memset(r->anno,0,sizeof(double)*16); memset(r->p,0,sizeof(float)*25); r->SCR = 0; if (ref_base >= 0) { ref4 = seq_nt16_int[ref_base]; is_indel = 0; } else ref4 = 4, is_indel = 1; if (_n == 0) return -1; // enlarge the bases array if necessary if (bca->max_bases < _n) { bca->max_bases = _n; kroundup32(bca->max_bases); bca->bases = (uint16_t*)realloc(bca->bases, 2 * bca->max_bases); } // fill the bases array double nqual_over_60 = bca->nqual / 60.0; int ADR_ref_missed[4] = {0}; int ADF_ref_missed[4] = {0}; for (i = n = 0; i < _n; ++i) { const bam_pileup1_t *p = pl + i; int b; // the base or indel type int q; // the base or indel quality used to calculate PL int seqQ; // used to cap the indel quality given the sequence context int mapQ; // to cap the quality for low MQ reads int baseQ; // used only for supporting INFO annotations int is_diff; // is this base or indel type different from the reference int min_dist; // distance from the end, used for tail distance bias if ( bca->fmt_flag&(B2B_INFO_SCR|B2B_FMT_SCR) && PLP_HAS_SOFT_CLIP(&p->cd) ) r->SCR++; if (p->is_refskip || (p->b->core.flag&BAM_FUNMAP)) continue; // The meaning of the indel related variables: // is_indel .. is this position currently tested for an indel // p->is_del .. is the current base a deletion in this read (unrelated to the tested indel) // p->indel .. is there an indel starting after this position (i.e. does this read have the tested indel) if (p->is_del && !is_indel) continue; // not testing an indel and the read has a spanning deletion int inm = -1; ++ori_depth; if (is_indel) // testing an indel position { b = p->aux>>16&0x3f; // indel type seqQ = q = (p->aux & 0xff); // mp2 + builtin indel-bias if ( !bca->indels_v20 ) { /* This heuristics was introduced by e4e161068 and claims to fix #1446. However, we obtain correct result on the provided test case even when this code is commented out, so this may not be needed anymore. Leaving it in only for backward compatibility for now. See mpileup-tests homdel-issue-1446 and CHM1_CHM13_2.45x-1-1701408 which work only when this code is disabled. */ if (p->indel == 0 && (q < _n/2 || _n > 20)) { // high quality indel calls without p->indel set aren't // particularly indicative of being a good REF match either, // at least not in low coverage. So require solid coverage // before we start utilising such quals. b = 0; q = (int)bam_get_qual(p->b)[p->qpos]; seqQ = (3*seqQ + 2*q)/8; } if (_n > 20 && seqQ > 40) seqQ = 40; } is_diff = b ? 1 : 0; if ( bca->fmt_flag&(B2B_FMT_NMBZ|B2B_INFO_NMBZ|B2B_INFO_NM) ) { inm = get_aux_nm(p,p->qpos,is_diff?0:1); if ( inm>=0 ) { bca->nnm[is_diff]++; bca->nm[is_diff] += inm; } } if (q < bca->min_baseQ) { if (!p->indel && b < 4) // not an indel read { if (bam_is_rev(p->b)) ADR_ref_missed[b]++; else ADF_ref_missed[b]++; } continue; } baseQ = p->aux>>8&0xff; } else { b = bam_seqi(bam_get_seq(p->b), p->qpos); // base b = seq_nt16_int[b? b : ref_base]; // b is the 2-bit base // Lowest of this and neighbour quality values uint8_t *qual = bam_get_qual(p->b); q = qual[p->qpos]; if (p->qpos > 0 && q > qual[p->qpos-1]+bca->delta_baseQ) q = qual[p->qpos-1]+bca->delta_baseQ; if (p->qpos+1 < p->b->core.l_qseq && q > qual[p->qpos+1]+bca->delta_baseQ) q = qual[p->qpos+1]+bca->delta_baseQ; if (q < bca->min_baseQ) continue; if (q > bca->max_baseQ) q = bca->max_baseQ; baseQ = q; seqQ = 99; is_diff = (ref4 < 4 && b == ref4)? 0 : 1; if ( bca->fmt_flag&(B2B_FMT_NMBZ|B2B_INFO_NMBZ|B2B_INFO_NM) ) { inm = get_aux_nm(p,p->qpos,is_diff?0:1); if ( inm>=0 ) { bca->nnm[is_diff]++; bca->nm[is_diff] += inm; } } } mapQ = p->b->core.qual < 255? p->b->core.qual : DEF_MAPQ; // special case for mapQ==255 if ( !mapQ ) r->mq0++; if (q > seqQ) q = seqQ; mapQ = mapQ < bca->capQ? mapQ : bca->capQ; if (q > mapQ) q = mapQ; if (q > 63) q = 63; if (q < 4) q = 4; // MQ=0 reads count as BQ=4 bca->bases[n++] = q<<5 | (int)bam_is_rev(p->b)<<4 | b; //if (is_indel) fprintf(stderr,"xx:base,q,strand\t%d\t%d\t%d\n",b,q,bam_is_rev(p->b)?0:1); // collect annotations if (b < 4) { r->QS[b] += q; if ( r->ADF ) { if ( bam_is_rev(p->b) ) r->ADR[b]++; else r->ADF[b]++; } } ++r->anno[0<<2|is_diff<<1|bam_is_rev(p->b)]; min_dist = p->b->core.l_qseq - 1 - p->qpos; if (min_dist > p->qpos) min_dist = p->qpos; if (min_dist > CAP_DIST) min_dist = CAP_DIST; r->anno[1<<2|is_diff<<1|0] += baseQ; r->anno[1<<2|is_diff<<1|1] += baseQ * baseQ; r->anno[2<<2|is_diff<<1|0] += mapQ; r->anno[2<<2|is_diff<<1|1] += mapQ * mapQ; r->anno[3<<2|is_diff<<1|0] += min_dist; r->anno[3<<2|is_diff<<1|1] += min_dist * min_dist; // collect for bias tests if ( baseQ > 59 ) baseQ = 59; if ( mapQ > 59 ) mapQ = 59; int len, epos = 0, sc_len = 0, sc_dist = 0; if ( bca->fmt_flag & (B2B_INFO_RPBZ|B2B_INFO_VDB|B2B_INFO_SCBZ) ) { int pos = get_position(p, &len, &sc_len, &sc_dist); epos = (double)pos/(len+1) * (bca->npos - 1); if (sc_len) { sc_len = 15.0*sc_len / (sc_dist+1); if (sc_len > 99) sc_len = 99; } assert( epos>=0 && eposnpos ); assert( sc_len>=0 && sc_lennpos ); } int imq = mapQ * nqual_over_60; int ibq = baseQ * nqual_over_60; if ( bam_is_rev(p->b) ) bca->rev_mqs[imq]++; else bca->fwd_mqs[imq]++; if ( !is_diff ) { bca->ref_pos[epos]++; bca->ref_bq[ibq]++; bca->ref_mq[imq]++; bca->ref_scl[sc_len]++; if ( inm>=0 ) { bca->ref_nm[inm]++; if ( r->ref_nm ) r->ref_nm[inm]++; } } else { bca->alt_pos[epos]++; bca->alt_bq[ibq]++; bca->alt_mq[imq]++; bca->alt_scl[sc_len]++; if ( inm>=0 ) { bca->alt_nm[inm]++; if ( r->alt_nm ) r->alt_nm[inm]++; } } } // Compensate for AD not being counted on low quality REF indel matches. if ( r->ADF && bca->ambig_reads==B2B_INC_AD0 ) { for (i=0; i<4; i++) { r->ADR[0] += ADR_ref_missed[i]; r->ADF[0] += ADF_ref_missed[i]; } } else if ( r->ADF && bca->ambig_reads==B2B_INC_AD ) { int dp = 0, dp_ambig = 0; for (i=0; i<4; i++) dp += r->ADR[i]; for (i=0; i<4; i++) dp_ambig += ADR_ref_missed[i]; if ( dp ) for (i=0; i<4; i++) r->ADR[i] += lroundf((float)dp_ambig * r->ADR[i]/dp); dp = 0, dp_ambig = 0; for (i=0; i<4; i++) dp += r->ADF[i]; for (i=0; i<4; i++) dp_ambig += ADF_ref_missed[i]; if ( dp ) for (i=0; i<4; i++) r->ADF[i] += lroundf((float)dp_ambig * r->ADF[i]/dp); } r->ori_depth = ori_depth; // glfgen errmod_cal(bca->e, n, 5, bca->bases, r->p); // calculate PL of each genotype return n; } /* * calc_vdb() - returns value between zero (most biased) and one (no bias) * on success, or HUGE_VAL when VDB cannot be calculated because * of insufficient depth (<2x) * * Variant Distance Bias tests if the variant bases are positioned within the * reads with sufficient randomness. Unlike other tests, it looks only at * variant reads and therefore gives different kind of information than Read * Position Bias for instance. VDB was developed for detecting artefacts in * RNA-seq calls where reads from spliced transcripts span splice site * boundaries. The current implementation differs somewhat from the original * version described in supplementary material of PMID:22524474, but the idea * remains the same. (Here the random variable tested is the average distance * from the averaged position, not the average pairwise distance.) * * For coverage of 2x, the calculation is exact but is approximated for the * rest. The result is most accurate between 4-200x. For 3x or >200x, the * reported values are slightly more favourable than those of a true random * distribution. */ double calc_vdb(int *pos, int npos) { // Note well: the parameters were obtained by fitting to simulated data of // 100bp reads. This assumes rescaling to 100bp in bcf_call_glfgen(). const int readlen = 100; assert( npos==readlen ); #define nparam 15 const float param[nparam][3] = { {3,0.079,18}, {4,0.09,19.8}, {5,0.1,20.5}, {6,0.11,21.5}, {7,0.125,21.6}, {8,0.135,22}, {9,0.14,22.2}, {10,0.153,22.3}, {15,0.19,22.8}, {20,0.22,23.2}, {30,0.26,23.4}, {40,0.29,23.5}, {50,0.35,23.65}, {100,0.5,23.7}, {200,0.7,23.7} }; int i, dp = 0; float mean_pos = 0, mean_diff = 0; for (i=0; i=200 ) i = nparam; // shortcut for big depths else { for (i=0; i=dp ) break; } float pshift, pscale; if ( i==nparam ) { // the depth is too high, go with 200x pscale = param[nparam-1][1]; pshift = param[nparam-1][2]; } else if ( i>0 && param[i][0]!=dp ) { // linear interpolation of parameters pscale = (param[i-1][1] + param[i][1])*0.5; pshift = (param[i-1][2] + param[i][2])*0.5; } else { pscale = param[i][1]; pshift = param[i][2]; } return 0.5*kf_erfc(-(mean_diff-pshift)*pscale); } double calc_chisq_bias(int *a, int *b, int n) { int na = 0, nb = 0, i, ndf = n; for (i=0; i= 2 && m >= 2); return (n < 8 && m < 8 && U < 50) ? mw[n-2][m-2][U] : mann_whitney_1947_(n,m,U); } double mann_whitney_1947_cdf(int n, int m, int U) { int i; double sum = 0; for (i=0; i<=U; i++) sum += mann_whitney_1947(n,m,i); return sum; } double calc_mwu_bias_cdf(int *a, int *b, int n) { int na = 0, nb = 0, i; double U = 0; //double ties = 0; for (i=0; i=8 && nb>=8 and reasonable if na<8 or nb<8 if ( na>=8 || nb>=8 ) { double mean = ((double)na*nb)*0.5; // Correction for ties: // double N = na+nb; // double var2 = (N*N-1)*N-ties; // if ( var2==0 ) return 1.0; // var2 *= ((double)na*nb)/N/(N-1)/12.0; // No correction for ties: double var2 = ((double)na*nb)*(na+nb+1)/12.0; double z = (U_min - mean)/sqrt(2*var2); // z is N(0,1) return 2.0 - kf_erfc(z); // which is 1 + erf(z) } // Exact calculation double pval = 2*mann_whitney_1947_cdf(na,nb,U_min); return pval>1 ? 1 : pval; } double calc_mwu_bias(int *a, int *b, int n, int left) { int na = 0, nb = 0, i; double U = 0; // double ties = 0; for (i=0; i mean) return 1; // for MQB which is asymmetrical if ( na==2 || nb==2 ) { // Linear approximation return U>mean ? (2.0*mean-U)/mean : U/mean; } // Correction for ties: // double N = na+nb; // double var2 = (N*N-1)*N-ties; // if ( var2==0 ) return 1.0; // var2 *= ((double)na*nb)/N/(N-1)/12.0; // No correction for ties: double var2 = ((double)na*nb)*(na+nb+1)/12.0; if ( na>=8 || nb>=8 ) { // Normal approximation, very good for na>=8 && nb>=8 and reasonable if na<8 or nb<8 return exp(-0.5*(U-mean)*(U-mean)/var2); } // Exact calculation return mann_whitney_1947(na,nb,U) * sqrt(2*M_PI*var2); } // A Z-score version of the above function. // // See "Normal approximation and tie correction" at // https://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U_test // // The Z score is the number of standard deviations above or below the mean // with 0 being equality of the two distributions and +ve/-ve from there. // // This is a more robust score to filter on. double calc_mwu_biasZ(int *a, int *b, int n, int left_only, int do_Z) { int i; int64_t t; // Optimisation for (i = 0; i < n; i++) if (b[i]) break; int b_empty = (i == n); // Count equal (e), less-than (l) and greater-than (g) permutations. int e = 0, l = 0, na = 0, nb = 0; if (b_empty) { for (t = 0, i = n-1; i >= 0; i--) { na += a[i]; t += (a[i]*a[i]-1)*a[i]; // adjustment score for ties } } else { for (t = 0, i = n-1; i >= 0; i--) { // Combinations of a[i] and b[j] for i==j e += a[i]*b[i]; // nb is running total of b[i+1]..b[n-1]. // Therefore a[i]*nb is the number of combinations of a[i] and b[j] // for all i < j. l += a[i]*nb; // a= 0 ? 0.5 : -0.5)) / sd; // gatk method? return (U - m) / sqrt(var2); } // Else U score, which can be asymmetric for some data types. if (left_only && U > m) return HUGE_VAL; // one-sided, +ve bias is OK, -ve is not. if (na >= 8 || nb >= 8) { // Normal approximation, very good for na>=8 && nb>=8 and // reasonable if na<8 or nb<8 return exp(-0.5*(U-m)*(U-m)/var2); } // Exact calculation if (na==1 || nb == 1) return mann_whitney_1947_(na, nb, U) * sqrt(2*M_PI*var2); else return mann_whitney_1947(na, nb, U) * sqrt(2*M_PI*var2); } static inline double logsumexp2(double a, double b) { if ( a>b ) return log(1 + exp(b-a)) + a; else return log(1 + exp(a-b)) + b; } void calc_SegBias(const bcf_callret1_t *bcr, bcf_call_t *call) { call->seg_bias = HUGE_VAL; if ( !bcr ) return; int nr = call->anno[2] + call->anno[3]; // number of observed non-reference reads if ( !nr ) return; int avg_dp = (call->anno[0] + call->anno[1] + nr) / call->n; // average depth double M = floor((double)nr / avg_dp + 0.5); // an approximate number of variants samples in the population if ( M>call->n ) M = call->n; // clamp M at the number of samples else if ( M==0 ) M = 1; double f = M / 2. / call->n; // allele frequency double p = (double) nr / call->n; // number of variant reads per sample expected if variant not real (poisson) double q = (double) nr / M; // number of variant reads per sample expected if variant is real (poisson) double sum = 0; const double log2 = log(2.0); // fprintf(stderr,"M=%.1f p=%e q=%e f=%f dp=%d\n",M,p,q,f,avg_dp); int i; for (i=0; in; i++) { int oi = bcr[i].anno[2] + bcr[i].anno[3]; // observed number of non-ref reads double tmp; if ( oi ) { // tmp = log(f) + oi*log(q/p) - q + log(2*(1-f) + f*pow(2,oi)*exp(-q)) + p; // this can under/overflow tmp = logsumexp2(log(2*(1-f)), log(f) + oi*log2 - q); tmp += log(f) + oi*log(q/p) - q + p; } else tmp = log(2*f*(1-f)*exp(-q) + f*f*exp(-2*q) + (1-f)*(1-f)) + p; sum += tmp; // fprintf(stderr,"oi=%d %e\n", oi,tmp); } call->seg_bias = sum; } /** * bcf_call_combine() - sets the PL array and VDB, RPB annotations, finds the top two alleles * @n: number of samples * @calls: each sample's calls * @bca: auxiliary data structure for holding temporary values * @ref_base: the reference base * @call: filled with the annotations * * Combines calls across the various samples being studied * 1. For each allele at each base across all samples the quality is summed so * you end up with a set of quality sums for each allele present 2. The quality * sums are sorted. * 3. Using the sorted quality sums we now create the allele ordering array * A\subN. This is done by doing the following: * a) If the reference allele is known it always comes first, otherwise N * comes first. * b) Then the rest of the alleles are output in descending order of quality * sum (which we already know the qsum array was sorted). Any allelles with * qsum 0 will be excluded. * 4. Using the allele ordering array we create the genotype ordering array. * In the worst case with an unknown reference this will be: A0/A0 A1/A0 A1/A1 * A2/A0 A2/A1 A2/A2 A3/A0 A3/A1 A3/A2 A3/A3 A4/A0 A4/A1 A4/A2 A4/A3 A4/A4 * 5. The genotype ordering array is then used to extract data from the error * model 5*5 matrix and is used to produce a Phread likelihood array for each * sample. */ int bcf_call_combine(int n, const bcf_callret1_t *calls, bcf_callaux_t *bca, int ref_base /*4-bit*/, bcf_call_t *call) { int ref4, i, j; float qsum[B2B_MAX_ALLELES] = {0,0,0,0,0}; if (ref_base >= 0) { call->ori_ref = ref4 = seq_nt16_int[ref_base]; if (ref4 > 4) ref4 = 4; } else call->ori_ref = -1, ref4 = 0; // calculate qsum, this is done by summing normalized qsum across all samples, // to account for differences in coverage for (i = 0; i < n; ++i) { float sum = 0; for (j = 0; j < 4; ++j) sum += calls[i].QS[j]; if ( sum ) for (j = 0; j < 4; j++) qsum[j] += (float)calls[i].QS[j] / sum; } // sort qsum in ascending order (insertion sort) float *ptr[5], *tmp; for (i=0; i<5; i++) ptr[i] = &qsum[i]; for (i=1; i<4; i++) for (j=i; j>0 && *ptr[j] < *ptr[j-1]; j--) tmp = ptr[j], ptr[j] = ptr[j-1], ptr[j-1] = tmp; // Set the reference allele and alternative allele(s) for (i=0; i<5; i++) call->a[i] = -1; for (i=0; iqsum[i] = 0; call->unseen = -1; call->a[0] = ref4; for (i=3, j=1; i>=0; i--) // i: alleles sorted by QS; j, a[j]: output allele ordering { int ipos = ptr[i] - qsum; // position in sorted qsum array if ( ipos==ref4 ) call->qsum[0] = qsum[ipos]; // REF's qsum else { if ( !qsum[ipos] ) break; // qsum is 0, this and consequent alleles are not seen in the pileup call->qsum[j] = qsum[ipos]; call->a[j++] = ipos; } } if (ref_base >= 0) { // for SNPs, find the "unseen" base if (((ref4 < 4 && j < 4) || (ref4 == 4 && j < 5)) && i >= 0) call->unseen = j, call->a[j++] = ptr[i] - qsum; call->n_alleles = j; } else { call->n_alleles = j; if (call->n_alleles == 1) return -1; // no reliable supporting read. stop doing anything } int has_alt = (call->n_alleles==2 && call->unseen!=-1) ? 0 : 1; /* * Set the phread likelihood array (call->PL) This array is 15 entries long * for each sample because that is size of an upper or lower triangle of a * worst case 5x5 matrix of possible genotypes. This worst case matrix will * occur when all 4 possible alleles are present and the reference allele * is unknown. The sides of the matrix will correspond to the reference * allele (if known) followed by the alleles present in descending order of * quality sum */ { int x, g[15], z; double sum_min = 0.; x = call->n_alleles * (call->n_alleles + 1) / 2; // get the possible genotypes // this is done by creating an ordered list of locations g for call (allele a, allele b) in the genotype likelihood matrix for (i = z = 0; i < call->n_alleles; ++i) { for (j = 0; j <= i; ++j) { g[z++] = call->a[j] * 5 + call->a[i]; } } // for each sample calculate the PL for (i = 0; i < n; ++i) { int32_t *PL = call->PL + x * i; const bcf_callret1_t *r = calls + i; float min = FLT_MAX; for (j = 0; j < x; ++j) { if (min > r->p[g[j]]) min = r->p[g[j]]; } sum_min += min; for (j = 0; j < x; ++j) { int y; y = (int)(r->p[g[j]] - min + .499); if (y > 255) y = 255; PL[j] = y; } } if ( call->DP4 ) { for (i=0; iDP4[4*i] = calls[i].anno[0]; call->DP4[4*i+1] = calls[i].anno[1]; call->DP4[4*i+2] = calls[i].anno[2]; call->DP4[4*i+3] = calls[i].anno[3]; } } if ( call->SCR ) { for (i=0; iSCR[0] += calls[i].SCR; call->SCR[1+i] = calls[i].SCR; } } if ( call->ADF ) { assert( call->n_alleles<=B2B_MAX_ALLELES ); // this is always true for SNPs and so far for indels as well // reorder ADR,ADF to match the allele ordering at this site int32_t tmp[B2B_MAX_ALLELES]; int32_t *adr = call->ADR + B2B_MAX_ALLELES, *adr_out = call->ADR + B2B_MAX_ALLELES; int32_t *adf = call->ADF + B2B_MAX_ALLELES, *adf_out = call->ADF + B2B_MAX_ALLELES; int32_t *adr_tot = call->ADR; // the first bin stores total counts per site int32_t *adf_tot = call->ADF; for (i=0; in_alleles; j++) { tmp[j] = adr[ call->a[j] ]; adr_tot[j] += tmp[j]; } for (j=0; jn_alleles; j++) adr_out[j] = tmp[j]; for (j=0; jn_alleles; j++) { tmp[j] = adf[ call->a[j] ]; adf_tot[j] += tmp[j]; } for (j=0; jn_alleles; j++) adf_out[j] = tmp[j]; adf_out += call->n_alleles; adr_out += call->n_alleles; adr += B2B_MAX_ALLELES; adf += B2B_MAX_ALLELES; } } if ( bca->fmt_flag & B2B_FMT_QS ) { assert( call->n_alleles<=B2B_MAX_ALLELES ); // this is always true for SNPs and so far for indels as well // reorder QS to match the allele ordering at this site int32_t tmp[B2B_MAX_ALLELES]; int32_t *qs = call->QS, *qs_out = call->QS; for (i=0; in_alleles; j++) tmp[j] = qs[ call->a[j] ]; for (j=0; jn_alleles; j++) qs_out[j] = tmp[j] < BCF_MAX_BT_INT32 ? tmp[j] : BCF_MAX_BT_INT32; qs_out += call->n_alleles; qs += B2B_MAX_ALLELES; } } // if (ref_base < 0) fprintf(stderr, "%d,%d,%f,%d\n", call->n_alleles, x, sum_min, call->unseen); // fprintf(stderr,"sum_min=%f\n",sum_min); call->shift = (int)(sum_min + .499); } // combine annotations memset(call->anno, 0, 16 * sizeof(double)); call->ori_depth = 0; call->depth = 0; call->mq0 = 0; for (i = 0; i < n; ++i) { call->depth += calls[i].anno[0] + calls[i].anno[1] + calls[i].anno[2] + calls[i].anno[3]; call->ori_depth += calls[i].ori_depth; call->mq0 += calls[i].mq0; for (j = 0; j < 16; ++j) call->anno[j] += calls[i].anno[j]; } // No need to calculate MWU tests when there is no ALT allele, this should speed up things slightly if ( !has_alt ) return 0; if ( bca->fmt_flag & B2B_INFO_FS ) { double left,right,two; call->strand_bias = kt_fisher_exact(call->anno[0], call->anno[1], call->anno[2], call->anno[3], &left, &right, &two); } if ( bca->fmt_flag & B2B_INFO_SGB ) calc_SegBias(calls, call); // calc_chisq_bias("XPOS", call->bcf_hdr->id[BCF_DT_CTG][call->tid].key, call->pos, bca->ref_pos, bca->alt_pos, bca->npos); // calc_chisq_bias("XMQ", call->bcf_hdr->id[BCF_DT_CTG][call->tid].key, call->pos, bca->ref_mq, bca->alt_mq, bca->nqual); // calc_chisq_bias("XBQ", call->bcf_hdr->id[BCF_DT_CTG][call->tid].key, call->pos, bca->ref_bq, bca->alt_bq, bca->nqual); // U z-normalised as +/- number of standard deviations from mean. if (call->ori_ref < 0) { // indel if ( bca->fmt_flag & B2B_INFO_RPBZ ) call->mwu_pos = calc_mwu_biasZ(bca->iref_pos, bca->ialt_pos, bca->npos, 0, 1); if ( bca->fmt_flag & B2B_INFO_MQBZ ) call->mwu_mq = calc_mwu_biasZ(bca->iref_mq, bca->ialt_mq, bca->nqual,1,1); if ( bca->fmt_flag & B2B_INFO_SCBZ ) call->mwu_sc = calc_mwu_biasZ(bca->iref_scl, bca->ialt_scl, 100, 0,1); } else { if ( bca->fmt_flag & B2B_INFO_RPBZ ) call->mwu_pos = calc_mwu_biasZ(bca->ref_pos, bca->alt_pos, bca->npos, 0, 1); if ( bca->fmt_flag & B2B_INFO_MQBZ ) call->mwu_mq = calc_mwu_biasZ(bca->ref_mq, bca->alt_mq, bca->nqual,1,1); if ( bca->fmt_flag & B2B_INFO_BQBZ ) call->mwu_bq = calc_mwu_biasZ(bca->ref_bq, bca->alt_bq, bca->nqual,0,1); if ( bca->fmt_flag & B2B_INFO_MQSBZ ) call->mwu_mqs = calc_mwu_biasZ(bca->fwd_mqs, bca->rev_mqs, bca->nqual,0,1); if ( bca->fmt_flag & B2B_INFO_SCBZ ) call->mwu_sc = calc_mwu_biasZ(bca->ref_scl, bca->alt_scl, 100, 0,1); } if ( bca->fmt_flag & B2B_INFO_NMBZ ) call->mwu_nm[0] = calc_mwu_biasZ(bca->ref_nm, bca->alt_nm, B2B_N_NM,0,1); if ( bca->fmt_flag & B2B_FMT_NMBZ ) { for (i=0; imwu_nm[i+1] = val!=HUGE_VAL ? val : 0; } } if ( bca->fmt_flag & B2B_INFO_VDB ) call->vdb = calc_vdb(bca->alt_pos, bca->npos); return 0; } int bcf_call2bcf(bcf_call_t *bc, bcf1_t *rec, bcf_callret1_t *bcr, int fmt_flag, const bcf_callaux_t *bca, const char *ref) { extern double kt_fisher_exact(int n11, int n12, int n21, int n22, double *_left, double *_right, double *two); int i, j, nals = 1, has_alt = 0; bcf_hdr_t *hdr = bc->bcf_hdr; rec->rid = bc->tid; rec->pos = bc->pos; rec->qual = 0; bc->tmp.l = 0; if (bc->ori_ref < 0) // indel { // REF kputc(ref[bc->pos], &bc->tmp); for (j = 0; j < bca->indelreg; ++j) kputc(ref[bc->pos+1+j], &bc->tmp); // ALT for (i=1; i<4; i++) { if (bc->a[i] < 0) break; kputc(',', &bc->tmp); kputc(ref[bc->pos], &bc->tmp); if (bca->indel_types[bc->a[i]] < 0) { // deletion for (j = -bca->indel_types[bc->a[i]]; j < bca->indelreg; ++j) kputc(ref[bc->pos+1+j], &bc->tmp); } else { // insertion; cannot be a reference unless a bug char *inscns = &bca->inscns[bc->a[i] * bca->maxins]; for (j = 0; j < bca->indel_types[bc->a[i]]; ++j) kputc("ACGTN"[(int)inscns[j]], &bc->tmp); for (j = 0; j < bca->indelreg; ++j) kputc(ref[bc->pos+1+j], &bc->tmp); } nals++; has_alt = 1; } } else // SNP { kputc("ACGTN"[bc->ori_ref], &bc->tmp); for (i=1; i<5; i++) { if (bc->a[i] < 0) break; kputc(',', &bc->tmp); if ( bc->unseen==i ) kputs("<*>", &bc->tmp); else { kputc("ACGT"[bc->a[i]], &bc->tmp); has_alt = 1; } nals++; } } bcf_update_alleles_str(hdr, rec, bc->tmp.s); bc->tmp.l = 0; // INFO if ( bc->ori_ref < 0 ) { bcf_update_info_flag(hdr, rec, "INDEL", NULL, 1); if ( fmt_flag&B2B_INFO_IDV ) bcf_update_info_int32(hdr, rec, "IDV", &bca->max_support, 1); if ( fmt_flag&B2B_INFO_IMF ) bcf_update_info_float(hdr, rec, "IMF", &bca->max_frac, 1); } bcf_update_info_int32(hdr, rec, "DP", &bc->ori_depth, 1); if ( fmt_flag&B2B_INFO_ADF ) bcf_update_info_int32(hdr, rec, "ADF", bc->ADF, rec->n_allele); if ( fmt_flag&B2B_INFO_ADR ) bcf_update_info_int32(hdr, rec, "ADR", bc->ADR, rec->n_allele); if ( fmt_flag&(B2B_INFO_AD|B2B_INFO_DPR) ) { for (i=0; in_allele; i++) bc->ADF[i] += bc->ADR[i]; if ( fmt_flag&B2B_INFO_AD ) bcf_update_info_int32(hdr, rec, "AD", bc->ADF, rec->n_allele); if ( fmt_flag&B2B_INFO_DPR ) bcf_update_info_int32(hdr, rec, "DPR", bc->ADF, rec->n_allele); } if ( fmt_flag&B2B_INFO_SCR ) bcf_update_info_int32(hdr, rec, "SCR", bc->SCR, 1); float tmpf[16]; for (i=0; i<16; i++) tmpf[i] = bc->anno[i]; bcf_update_info_float(hdr, rec, "I16", tmpf, 16); bcf_update_info_float(hdr, rec, "QS", bc->qsum, nals); if ( has_alt ) { if ( fmt_flag&B2B_INFO_MIN_PL_SUM ) bcf_update_info_int32(hdr, rec, "MIN_PL_SUM", &bc->shift, 1); if ( fmt_flag&B2B_INFO_VDB && bc->vdb != HUGE_VAL ) bcf_update_info_float(hdr, rec, "VDB", &bc->vdb, 1); if ( fmt_flag&B2B_INFO_SGB && bc->seg_bias != HUGE_VAL ) bcf_update_info_float(hdr, rec, "SGB", &bc->seg_bias, 1); if ( fmt_flag&B2B_INFO_NM && (bca->nnm[0] || bca->nnm[1]) ) { for (i=0; i<2; i++) bc->nm[i] = bca->nnm[i] ? bca->nm[i]/bca->nnm[i] : 0; bcf_update_info_float(hdr, rec, "NM", bc->nm, 2); } if ( fmt_flag&B2B_INFO_RPBZ && bc->mwu_pos != HUGE_VAL ) bcf_update_info_float(hdr, rec, "RPBZ", &bc->mwu_pos, 1); if ( fmt_flag&B2B_INFO_MQBZ && bc->mwu_mq != HUGE_VAL ) bcf_update_info_float(hdr, rec, "MQBZ", &bc->mwu_mq, 1); if ( fmt_flag&B2B_INFO_MQSBZ && bc->mwu_mqs != HUGE_VAL ) bcf_update_info_float(hdr, rec, "MQSBZ", &bc->mwu_mqs, 1); if ( fmt_flag&B2B_INFO_BQBZ && bc->mwu_bq != HUGE_VAL ) bcf_update_info_float(hdr, rec, "BQBZ", &bc->mwu_bq, 1); if ( fmt_flag&B2B_INFO_NMBZ && bc->mwu_nm[0] != HUGE_VAL ) bcf_update_info_float(hdr, rec, "NMBZ", bc->mwu_nm, 1); if ( fmt_flag&B2B_INFO_SCBZ && bc->mwu_sc != HUGE_VAL ) bcf_update_info_float(hdr, rec, "SCBZ", &bc->mwu_sc, 1); if ( fmt_flag&B2B_INFO_FS && bc->strand_bias != HUGE_VAL ) bcf_update_info_float(hdr, rec, "FS", &bc->strand_bias, 1); } tmpf[0] = bc->ori_depth ? (float)bc->mq0/bc->ori_depth : 0; if ( fmt_flag&B2B_INFO_MQ0F ) bcf_update_info_float(hdr, rec, "MQ0F", tmpf, 1); // FORMAT rec->n_sample = bc->n; bcf_update_format_int32(hdr, rec, "PL", bc->PL, nals*(nals+1)/2 * rec->n_sample); if ( fmt_flag&B2B_FMT_DP ) { int32_t *ptr = (int32_t*) bc->fmt_arr; for (i=0; in; i++) ptr[i] = bc->DP4[4*i] + bc->DP4[4*i+1] + bc->DP4[4*i+2] + bc->DP4[4*i+3]; bcf_update_format_int32(hdr, rec, "DP", bc->fmt_arr, rec->n_sample); } if ( fmt_flag&B2B_FMT_DV ) { int32_t *ptr = (int32_t*) bc->fmt_arr; for (i=0; in; i++) ptr[i] = bc->DP4[4*i+2] + bc->DP4[4*i+3]; bcf_update_format_int32(hdr, rec, "DV", bc->fmt_arr, rec->n_sample); } if ( fmt_flag&B2B_FMT_SP ) { int32_t *ptr = (int32_t*) bc->fmt_arr; for (i=0; in; i++) { int fwd_ref = bc->DP4[4*i], rev_ref = bc->DP4[4*i+1], fwd_alt = bc->DP4[4*i+2], rev_alt = bc->DP4[4*i+3]; if ( fwd_ref+rev_ref<2 || fwd_alt+rev_alt<2 || fwd_ref+fwd_alt<2 || rev_ref+rev_alt<2 ) ptr[i] = 0; else { double left, right, two; kt_fisher_exact(fwd_ref, rev_ref, fwd_alt, rev_alt, &left, &right, &two); int32_t x = (int)(-4.343 * log(two) + .499); if (x > 255) x = 255; ptr[i] = x; } } bcf_update_format_int32(hdr, rec, "SP", bc->fmt_arr, rec->n_sample); } if ( fmt_flag&B2B_FMT_DP4 ) bcf_update_format_int32(hdr, rec, "DP4", bc->DP4, rec->n_sample*4); if ( fmt_flag&B2B_FMT_ADF ) bcf_update_format_int32(hdr, rec, "ADF", bc->ADF+B2B_MAX_ALLELES, rec->n_sample*rec->n_allele); if ( fmt_flag&B2B_FMT_ADR ) bcf_update_format_int32(hdr, rec, "ADR", bc->ADR+B2B_MAX_ALLELES, rec->n_sample*rec->n_allele); if ( fmt_flag&(B2B_FMT_AD|B2B_FMT_DPR) ) { for (i=0; in_sample*rec->n_allele; i++) bc->ADF[B2B_MAX_ALLELES+i] += bc->ADR[B2B_MAX_ALLELES+i]; if ( fmt_flag&B2B_FMT_AD ) bcf_update_format_int32(hdr, rec, "AD", bc->ADF+B2B_MAX_ALLELES, rec->n_sample*rec->n_allele); if ( fmt_flag&B2B_FMT_DPR ) bcf_update_format_int32(hdr, rec, "DPR", bc->ADF+B2B_MAX_ALLELES, rec->n_sample*rec->n_allele); } if ( fmt_flag&B2B_FMT_SCR ) bcf_update_format_int32(hdr, rec, "SCR", bc->SCR+1, rec->n_sample); if ( fmt_flag&B2B_FMT_QS ) bcf_update_format_int32(hdr, rec, "QS", bc->QS, rec->n_sample*rec->n_allele); if ( has_alt ) { if ( fmt_flag&B2B_FMT_NMBZ ) bcf_update_format_float(hdr, rec, "NMBZ", bc->mwu_nm+1, rec->n_sample); } return 0; }