-
Notifications
You must be signed in to change notification settings - Fork 0
/
calibrate_simulated_data.m
205 lines (180 loc) · 7.97 KB
/
calibrate_simulated_data.m
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
%%This function generates calibration data to match simulated test data.
%%Many inputs are similar to simulate_data_basic.m, but some differ:
%%seed_base = a small integer (between approximately 0 and 400) used for
%%randomization
%%chromosome = number of chromosome to omit, for jackknife purposes; if
%%desired to make calibration for all chromosomes, enter 0 or 23
%%cal_values = values of mu for which to make calibration curves, in
%%units of 10^-8 per base per generation (e.g., [1 2 4])
%%dnum_sim, dden_sim, het_rate_sim = output of simulate_data_basic.m
%%theta_base = per-base value of theta for msHOT (e.g., 20000/30000000)
%%history = inferred pop size history for msHOT
%%chr, phys, map = base map variables
%%cal_genomes = number of genomes' worth of data to generate per
%%calibration curve
%%cal_chr, cal_phys, cal_map = map variables to use for calibration
%%(usually the cal_map will be a perturbed version of the base map)
%%cal_blocks_left, cal_blocks_right = regions for calibration; typically
%%the same as blocks_left and blocks_right
function [mu_cal,cal,het_rate_cal] = calibrate_simulated_data(seed_base,chromosome,cal_values,mincount,maxcount,ms_path,dnum_sim,dden_sim,het_rate_sim,theta_base,history,chr,phys,map,block_starts,blocks_left,blocks_right,cal_genomes,cal_chr,cal_phys,cal_map,cal_blocks_left,cal_blocks_right)
%setup
max_d = 0.1; %max value of d for plotting
nbins = 60; %number of bins for plot
dgrid = 0:max_d/nbins:max_d;
%compute total physical length of map
total_phys = 0;
for n = 2:size(phys,1)
if chr(n) == chr(n-1)
total_phys = total_phys + phys(n) - phys(n-1);
end
end
%compute total genetic length of map
total_cM_cal = 0;
for n = 2:size(cal_map,1)
if cal_chr(n) == cal_chr(n-1)
total_cM_cal = total_cM_cal + cal_map(n) - cal_map(n-1);
end
end
r = total_cM_cal/total_phys/100;
num_curves = size(cal_values,2);
cal = zeros(1,size(dgrid,2),num_curves);
%%Adjust the pop size history to account for multiple sites per PSMC bin
psmc_intervals = 26;
old_hist_times = zeros(psmc_intervals,1);
new_hist_times = zeros(psmc_intervals,1);
old_hist_sizes = zeros(psmc_intervals,1);
new_hist_sizes = zeros(psmc_intervals,1);
histvec = sscanf(history,'%s %f %f %f');
for m = 1:psmc_intervals
old_hist_times(m) = histvec(6*(m-1)+4);
old_hist_sizes(m) = histvec(6*m);
end
new_hist_times(1) = 2*(1-(1-(theta_base)*old_hist_times(1)/2*200)^0.01)/(2*theta_base);
new_hist_sizes(1) = old_hist_sizes(1)*new_hist_times(1)/old_hist_times(1);
for m = 2:psmc_intervals
new_hist_times(m) = new_hist_times(m-1)+2*((1-(1-(theta_base)*(old_hist_times(m)+old_hist_times(m-1))/2*200)^0.01)/(2*theta_base)-new_hist_times(m-1));
new_hist_sizes(m) = old_hist_sizes(m)*(new_hist_times(m)-new_hist_times(m-1))/(old_hist_times(m)-old_hist_times(m-1));
end
history = '';
for m = 1:psmc_intervals
history = sprintf('%s-eN %f %f ',history,new_hist_times(m),new_hist_sizes(m));
end
%run the simulation subfunction
for z = 1:num_curves
cal(:,:,z) = simulate(cal_values(z)*10^-8,z);
end
%function to do the simulations
function curve = simulate(mu_input,z)
%setup
dnum_cal = zeros(1,size(dgrid,2));
dden_cal = zeros(1,size(dgrid,2));
tot_segsites_cal = 0;
tot_sites_cal = 0;
%simulation loop
for i = 1:size(blocks_left,1) %loop over regions
if chromosome ~= chr(block_starts(i)) %for calibrating jackknife replicates
len = phys(blocks_right(i))-phys(blocks_left(i)); %physical length of region
num_spots = cal_blocks_right(i)-cal_blocks_left(i);
%setup
midp_phys = 50000+phys(block_starts(i));
midp_cM = interp1q(phys(blocks_left(i):blocks_right(i)),map(blocks_left(i):blocks_right(i)),midp_phys);
jack_den = 0; %no jackknife here - run separate instances of calibration
jack_ind = 1;
theta = theta_base*len;
rho = theta_base*len*r/mu_input;
%%Simulating one sequence at a time for randomization purposes
for j = 1:cal_genomes
%fixed seed value for each region
if seed_base > 0
rng(500*25000*seed_base+100*25000*z+100*i+j);
end
seeds = randi(1000000,3,1);
command = sprintf('%s 2 1 -seeds %d %d %d -t %f -r %f %d %s -v %d',ms_path,seeds(1),seeds(2),seeds(3),theta,rho,len,history,num_spots);
for s = 1:num_spots
spot_left = cal_phys(cal_blocks_left(i)+s-1)-cal_phys(cal_blocks_left(i))+1;
spot_right = cal_phys(cal_blocks_left(i)+s)-cal_phys(cal_blocks_left(i));
spot_weight = (cal_map(cal_blocks_left(i)+s)-cal_map(cal_blocks_left(i)+s-1))/(cal_phys(cal_blocks_left(i)+s)-cal_phys(cal_blocks_left(i)+s-1))/r/100;
spot = sprintf('%d %d %f',spot_left,spot_right,spot_weight);
command = sprintf('%s %s',command,spot);
end
command = strcat(command,' | egrep ''positions:|segsites: 0''');
%call msHOT
[~, result] = system(command);
ends = strfind(result,char(10));
datarow = sscanf(result(12:ends-1),'%f');
seg_phys = datarow*len+phys(blocks_left(i));
cold_pos = sum((seg_phys-midp_phys < 50000 & seg_phys-midp_phys >= 0));
if isempty(cold_pos) == 1
cold_pos = 0;
end
cold_neg = sum((seg_phys-midp_phys > -50000 & seg_phys-midp_phys < 0));
if isempty(cold_neg) == 1
cold_neg = 0;
end
coldcount = cold_pos + cold_neg;
tot_segsites_cal = tot_segsites_cal + size(datarow,1);
tot_sites_cal = tot_sites_cal + len;
%check whether this region gets used or not in this genome
if cold_pos > 0 && cold_neg > 0 && coldcount >= mincount && coldcount <= maxcount
jack_den(jack_ind) = jack_den(jack_ind) + 1;
%numerator
seg_cM = interp1q(phys(blocks_left(i):blocks_right(i)),map(blocks_left(i):blocks_right(i)),seg_phys);
d = abs(midp_cM-seg_cM);
if size(d,1) > 0
for k = 1:size(d,1)
if d(k) < max_d
dnum_cal(jack_ind,floor(d(k)*nbins/max_d)+1) = dnum_cal(jack_ind,floor(d(k)*nbins/max_d)+1) + 1;
end
end
end
end
end
%denominator
bin_low_phys = zeros(nbins+1,1);
bin_low_phys(1) = midp_phys;
bin_high_phys = zeros(nbins+1,1);
bin_high_phys(1) = midp_phys;
for b = 1:nbins
if midp_cM-map(blocks_left(i)) > max_d*b/nbins
bin_low_phys(b+1) = interp1q(map(blocks_left(i):blocks_right(i)),phys(blocks_left(i):blocks_right(i)),midp_cM-max_d*b/nbins);
dden_cal(:,b) = dden_cal(:,b) + jack_den'*(bin_low_phys(b) - bin_low_phys(b+1));
else
dden_cal(:,b) = dden_cal(:,b) + jack_den'*(bin_low_phys(b) - phys(blocks_left(i)));
break
end
end
for b = 1:nbins
if map(blocks_right(i))-midp_cM > max_d*b/nbins
bin_high_phys(b+1) = interp1q(map(blocks_left(i):blocks_right(i)),phys(blocks_left(i):blocks_right(i)),midp_cM+max_d*b/nbins);
dden_cal(:,b) = dden_cal(:,b) + jack_den'*(bin_high_phys(b+1) - bin_high_phys(b));
else
dden_cal(:,b) = dden_cal(:,b) + jack_den'*(phys(blocks_right(i)) - bin_high_phys(b));
break
end
end
end
end
%%Adjust asymptote and translate to match the first bin
het_rate_cal = tot_segsites_cal/tot_sites_cal;
curve = dnum_cal./dden_cal+(dnum_cal./dden_cal-dnum_cal(1)/dden_cal(1))*(het_rate_sim/het_rate_cal-1);
end
%%Interpolation estimate of mutation rate
x0 = 2.3;
binlen = size(dnum_sim,2)-1;
var = dnum_sim(:,1:end-1)./dden_sim(:,1:end-1).^2;
mu_cal = 0;
for jj = 1:1;
mu_cal(jj) = lsqnonlin(@int_fun,x0);
end
function F = int_fun(x)
F = zeros(binlen,1);
for ii = 1:binlen
interp_vec = zeros(1,num_curves);
for kk = 1:num_curves
interp_vec(kk) = cal(jj,ii,kk);
end
F(ii) = dnum_sim(jj,ii)/dden_sim(jj,ii) - interp1(cal_values,interp_vec,x,'spline');
end
F = F./var(jj,:)'.^0.5;
end
end