1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
|
//////////////////////////////////////////////////////////////////
// //
// PLINK (c) 2005-2008 Shaun Purcell //
// //
// This file is distributed under the GNU General Public //
// License, Version 2. Please see the file COPYING for more //
// details //
// //
//////////////////////////////////////////////////////////////////
#include <iostream>
#include <iomanip>
#include <fstream>
#include <sstream>
#include <cmath>
#include <vector>
#include <map>
#include "plink.h"
#include "options.h"
#include "phase.h"
#include "helper.h"
#include "stats.h"
//////////////////////////////
// Unweighted tests
void HaploPhase::haplotypicTDT(map<int,int> & tests, int nt, bool display)
{
// No implementation of TDT omnibus test yet
if ( nt != 2 )
{
result = -9;
pvalue = -9;
odds = -9;
return;
}
// This might be a haplotype-specific test (i.e. of a single
// haplotype) or of a group of haplotypes versus the rest
// When rescoring the T and U counts, we will have supplied a 'downcoding'
// map, which is the same as the 'tests' map, i.e. mapping each haplotype
// onto a 0/1 space (i.e. nt==2)
// Find test haplotype(s), if we are in display mode (i.e. here we
// know it is not a group of haplotypes, but a specific haplotype, and
// we want the name of it, --hap-tdt; for all other instances, we
// can not assume that we will be testing a specific haplotype; so
// we do not bother about the name (it might be a group). We
// can assume a binary test though (nt==2), so always set hh to 0.
int hh=0;
double tr = 0;
double un = 0;
// This test is always of 1 haplotype/group versus all others --
// i.e. the downcoding will have been performed previously, with the
// transmissions being appropriately rescored before hand (and so
// trans[]/untrans[] will already be downcoded.
if ( display )
{
map<int,int>::iterator i1 = tests.begin();
while ( i1 != tests.end() )
{
if ( i1->second == 0 )
{
hh = i1->first;
break;
}
i1++;
}
}
tr += trans[hh];
un += untrans[hh];
///////////////////////////////////////////////////////
// 'result' visible outside this class,
// Either use McNemar's chi-square (b-c)^2/(b+c)
// or normal approximation for test of transmission
// ratio equals 0.5 (with the empirical variance added
// here)
odds = tr/un;
// if ( true || useEmpiricalVariance )
// {
result = tr - un;
result *= result;
result /= tr + un;
pvalue = chiprobP(result,1);
case_freq = tr;
control_freq = un;
// }
// else
// {
// // Calculate empirical variance of transmissions: the
// // relevant quantities will have been stored during the
// // transmission scoring routine
// double transmissionProportion = tr / ( tr + un );
// double transmissionCount = tr + un;
// // double eHH = transmissionX2[hh] / ( transmissionTotal-1);
// // double eH = transmissionX[hh] / ( transmissionTotal-1);
// double eHH = transmissionX2[hh] / ( transmissionCount );
// double eH = transmissionX[hh] / ( transmissionCount );
// empiricalVariance = eHH - ( eH * eH );
// empiricalVariance /= transmissionCount - 1 ;
// double Z = ( transmissionProportion - 0.5 )
// / ( sqrt( empiricalVariance * ( 1 / transmissionCount ) ) );
// result = Z * Z;
// pvalue = chiprobP( result , 1 );
// }
if ( display )
HTEST << setw(10) << hname << " "
<< setw(12) << haplotypeName(hh) << " "
<< setw(10) << trans[hh] << " "
<< setw(10) << untrans[hh] << " ";
if ( display )
{
if ( realnum(result) )
{
HTEST << setw(10) << result << " "
<< setw(10) << pvalue << " ";
}
else
{
HTEST << setw(10) << "NA" << " "
<< setw(10) << "NA" << " ";
}
for (int snps=0; snps<ns-1; snps++)
HTEST << P.locus[S[snps]]->name << "|";
HTEST << P.locus[S[ns-1]]->name << "\n";
}
return;
}
void HaploPhase::haplotypicWeightedTDT()
{
vector_t weights;
for (int i=0; i<nh; i++)
{
map<string,double>::iterator
whap = new_pred_weighted_allele[current].find( haplotypeName(i) );
if ( whap != new_pred_weighted_allele[current].end() )
{
weights.push_back( whap->second );
}
else
{
weights.push_back( 0 );
}
}
double T = 0;
double U = 0;
for (int h=0; h<nh; h++)
{
T += trans[h] * weights[h];
U += untrans[h] * weights[h];
}
double chisq = ( (T-U)*(T-U) ) / ( T+U ) ;
HTEST << setw(10) << hname << " "
<< setw(12) << new_map[current]->allele1 << " "
<< setw(10) << T << " "
<< setw(10) << U << " ";
if ( realnum(chisq) )
{
HTEST << setw(10) << chisq << " "
<< setw(10) << chiprobP(chisq,1) << " ";
}
else
{
HTEST << setw(10) << "NA" << " "
<< setw(10) << "NA" << " ";
}
for (int snps=0; snps<ns-1; snps++)
HTEST << P.locus[S[snps]]->name << "|";
HTEST << P.locus[S[ns-1]]->name << "\n";
return;
}
|
