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comparison pyPRADA_1.2/tools/samtools-0.1.16/errmod.c @ 0:acc2ca1a3ba4

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author siyuan
date Thu, 20 Feb 2014 00:44:58 -0500
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1 #include <math.h>
2 #include "errmod.h"
3 #include "ksort.h"
4 KSORT_INIT_GENERIC(uint16_t)
5
6 typedef struct __errmod_coef_t {
7 double *fk, *beta, *lhet;
8 } errmod_coef_t;
9
10 typedef struct {
11 double fsum[16], bsum[16];
12 uint32_t c[16];
13 } call_aux_t;
14
15 static errmod_coef_t *cal_coef(double depcorr, double eta)
16 {
17 int k, n, q;
18 long double sum, sum1;
19 double *lC;
20 errmod_coef_t *ec;
21
22 ec = calloc(1, sizeof(errmod_coef_t));
23 // initialize ->fk
24 ec->fk = (double*)calloc(256, sizeof(double));
25 ec->fk[0] = 1.0;
26 for (n = 1; n != 256; ++n)
27 ec->fk[n] = pow(1. - depcorr, n) * (1.0 - eta) + eta;
28 // initialize ->coef
29 ec->beta = (double*)calloc(256 * 256 * 64, sizeof(double));
30 lC = (double*)calloc(256 * 256, sizeof(double));
31 for (n = 1; n != 256; ++n) {
32 double lgn = lgamma(n+1);
33 for (k = 1; k <= n; ++k)
34 lC[n<<8|k] = lgn - lgamma(k+1) - lgamma(n-k+1);
35 }
36 for (q = 1; q != 64; ++q) {
37 double e = pow(10.0, -q/10.0);
38 double le = log(e);
39 double le1 = log(1.0 - e);
40 for (n = 1; n <= 255; ++n) {
41 double *beta = ec->beta + (q<<16|n<<8);
42 sum1 = sum = 0.0;
43 for (k = n; k >= 0; --k, sum1 = sum) {
44 sum = sum1 + expl(lC[n<<8|k] + k*le + (n-k)*le1);
45 beta[k] = -10. / M_LN10 * logl(sum1 / sum);
46 }
47 }
48 }
49 // initialize ->lhet
50 ec->lhet = (double*)calloc(256 * 256, sizeof(double));
51 for (n = 0; n < 256; ++n)
52 for (k = 0; k < 256; ++k)
53 ec->lhet[n<<8|k] = lC[n<<8|k] - M_LN2 * n;
54 free(lC);
55 return ec;
56 }
57
58 errmod_t *errmod_init(float depcorr)
59 {
60 errmod_t *em;
61 em = (errmod_t*)calloc(1, sizeof(errmod_t));
62 em->depcorr = depcorr;
63 em->coef = cal_coef(depcorr, 0.03);
64 return em;
65 }
66
67 void errmod_destroy(errmod_t *em)
68 {
69 if (em == 0) return;
70 free(em->coef->lhet); free(em->coef->fk); free(em->coef->beta);
71 free(em->coef); free(em);
72 }
73 // qual:6, strand:1, base:4
74 int errmod_cal(const errmod_t *em, int n, int m, uint16_t *bases, float *q)
75 {
76 call_aux_t aux;
77 int i, j, k, w[32];
78
79 if (m > m) return -1;
80 memset(q, 0, m * m * sizeof(float));
81 if (n == 0) return 0;
82 // calculate aux.esum and aux.fsum
83 if (n > 255) { // then sample 255 bases
84 ks_shuffle(uint16_t, n, bases);
85 n = 255;
86 }
87 ks_introsort(uint16_t, n, bases);
88 memset(w, 0, 32 * sizeof(int));
89 memset(&aux, 0, sizeof(call_aux_t));
90 for (j = n - 1; j >= 0; --j) { // calculate esum and fsum
91 uint16_t b = bases[j];
92 int q = b>>5 < 4? 4 : b>>5;
93 if (q > 63) q = 63;
94 k = b&0x1f;
95 aux.fsum[k&0xf] += em->coef->fk[w[k]];
96 aux.bsum[k&0xf] += em->coef->fk[w[k]] * em->coef->beta[q<<16|n<<8|aux.c[k&0xf]];
97 ++aux.c[k&0xf];
98 ++w[k];
99 }
100 // generate likelihood
101 for (j = 0; j != m; ++j) {
102 float tmp1, tmp3;
103 int tmp2, bar_e;
104 // homozygous
105 for (k = 0, tmp1 = tmp3 = 0.0, tmp2 = 0; k != m; ++k) {
106 if (k == j) continue;
107 tmp1 += aux.bsum[k]; tmp2 += aux.c[k]; tmp3 += aux.fsum[k];
108 }
109 if (tmp2) {
110 bar_e = (int)(tmp1 / tmp3 + 0.499);
111 if (bar_e > 63) bar_e = 63;
112 q[j*m+j] = tmp1;
113 }
114 // heterozygous
115 for (k = j + 1; k < m; ++k) {
116 int cjk = aux.c[j] + aux.c[k];
117 for (i = 0, tmp2 = 0, tmp1 = tmp3 = 0.0; i < m; ++i) {
118 if (i == j || i == k) continue;
119 tmp1 += aux.bsum[i]; tmp2 += aux.c[i]; tmp3 += aux.fsum[i];
120 }
121 if (tmp2) {
122 bar_e = (int)(tmp1 / tmp3 + 0.499);
123 if (bar_e > 63) bar_e = 63;
124 q[j*m+k] = q[k*m+j] = -4.343 * em->coef->lhet[cjk<<8|aux.c[k]] + tmp1;
125 } 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
126 }
127 for (k = 0; k != m; ++k) if (q[j*m+k] < 0.0) q[j*m+k] = 0.0;
128 }
129 return 0;
130 }