Mercurial > repos > siyuan > prada
view pyPRADA_1.2/tools/samtools-0.1.16/errmod.c @ 3:f17965495ec9 draft default tip
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author | siyuan |
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date | Tue, 11 Mar 2014 12:14:01 -0400 |
parents | acc2ca1a3ba4 |
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#include <math.h> #include "errmod.h" #include "ksort.h" KSORT_INIT_GENERIC(uint16_t) typedef struct __errmod_coef_t { double *fk, *beta, *lhet; } errmod_coef_t; typedef struct { double fsum[16], bsum[16]; uint32_t c[16]; } call_aux_t; static errmod_coef_t *cal_coef(double depcorr, double eta) { int k, n, q; long double sum, sum1; double *lC; errmod_coef_t *ec; ec = calloc(1, sizeof(errmod_coef_t)); // initialize ->fk ec->fk = (double*)calloc(256, sizeof(double)); ec->fk[0] = 1.0; for (n = 1; n != 256; ++n) ec->fk[n] = pow(1. - depcorr, n) * (1.0 - eta) + eta; // initialize ->coef ec->beta = (double*)calloc(256 * 256 * 64, sizeof(double)); lC = (double*)calloc(256 * 256, sizeof(double)); for (n = 1; n != 256; ++n) { double lgn = lgamma(n+1); for (k = 1; k <= n; ++k) lC[n<<8|k] = lgn - lgamma(k+1) - lgamma(n-k+1); } for (q = 1; q != 64; ++q) { double e = pow(10.0, -q/10.0); double le = log(e); double le1 = log(1.0 - e); for (n = 1; n <= 255; ++n) { double *beta = ec->beta + (q<<16|n<<8); sum1 = sum = 0.0; for (k = n; k >= 0; --k, sum1 = sum) { sum = sum1 + expl(lC[n<<8|k] + k*le + (n-k)*le1); beta[k] = -10. / M_LN10 * logl(sum1 / sum); } } } // initialize ->lhet ec->lhet = (double*)calloc(256 * 256, sizeof(double)); for (n = 0; n < 256; ++n) for (k = 0; k < 256; ++k) ec->lhet[n<<8|k] = lC[n<<8|k] - M_LN2 * n; free(lC); return ec; } errmod_t *errmod_init(float depcorr) { errmod_t *em; em = (errmod_t*)calloc(1, sizeof(errmod_t)); em->depcorr = depcorr; em->coef = cal_coef(depcorr, 0.03); return em; } void errmod_destroy(errmod_t *em) { if (em == 0) return; free(em->coef->lhet); free(em->coef->fk); free(em->coef->beta); free(em->coef); free(em); } // qual:6, strand:1, base:4 int errmod_cal(const errmod_t *em, int n, int m, uint16_t *bases, float *q) { call_aux_t aux; int i, j, k, w[32]; if (m > m) return -1; memset(q, 0, m * m * sizeof(float)); if (n == 0) return 0; // calculate aux.esum and aux.fsum if (n > 255) { // then sample 255 bases ks_shuffle(uint16_t, n, bases); n = 255; } ks_introsort(uint16_t, n, bases); memset(w, 0, 32 * sizeof(int)); memset(&aux, 0, sizeof(call_aux_t)); for (j = n - 1; j >= 0; --j) { // calculate esum and fsum uint16_t b = bases[j]; int q = b>>5 < 4? 4 : b>>5; if (q > 63) q = 63; k = b&0x1f; aux.fsum[k&0xf] += em->coef->fk[w[k]]; aux.bsum[k&0xf] += em->coef->fk[w[k]] * em->coef->beta[q<<16|n<<8|aux.c[k&0xf]]; ++aux.c[k&0xf]; ++w[k]; } // generate likelihood for (j = 0; j != m; ++j) { float tmp1, tmp3; int tmp2, bar_e; // homozygous for (k = 0, tmp1 = tmp3 = 0.0, tmp2 = 0; k != m; ++k) { if (k == j) continue; tmp1 += aux.bsum[k]; tmp2 += aux.c[k]; tmp3 += aux.fsum[k]; } if (tmp2) { bar_e = (int)(tmp1 / tmp3 + 0.499); if (bar_e > 63) bar_e = 63; q[j*m+j] = tmp1; } // heterozygous for (k = j + 1; k < m; ++k) { int cjk = aux.c[j] + aux.c[k]; for (i = 0, tmp2 = 0, tmp1 = tmp3 = 0.0; i < m; ++i) { if (i == j || i == k) continue; tmp1 += aux.bsum[i]; tmp2 += aux.c[i]; tmp3 += aux.fsum[i]; } if (tmp2) { bar_e = (int)(tmp1 / tmp3 + 0.499); if (bar_e > 63) bar_e = 63; q[j*m+k] = q[k*m+j] = -4.343 * em->coef->lhet[cjk<<8|aux.c[k]] + tmp1; } else q[j*m+k] = q[k*m+j] = -4.343 * em->coef->lhet[cjk<<8|aux.c[k]]; // all the bases are either j or k } for (k = 0; k != m; ++k) if (q[j*m+k] < 0.0) q[j*m+k] = 0.0; } return 0; }