|
0
|
1 function [MASKS]=get_nonparametric_masks(CFG,reads1,reads2)
|
|
|
2
|
|
|
3 %What fracitons should be choosen for the cutoff
|
|
|
4 cen_arr=0.1:0.1:1;
|
|
|
5
|
|
|
6 % Define the mask which should be used in order to mask high
|
|
|
7 % expresse genes
|
|
|
8 MASKS=zeros(length(cen_arr),size(reads1,2));
|
|
|
9
|
|
|
10 COUNTER=1;
|
|
|
11 for censor_frac= cen_arr
|
|
|
12 temp_reads1=reads1;
|
|
|
13 temp_reads2=reads2;
|
|
|
14 %cut to relvant position
|
|
|
15 read_coverage=sum(reads1,1)+sum(reads2,1);
|
|
|
16 % get positions with a positive coverage
|
|
|
17 nonzero_position=read_coverage>0;
|
|
|
18 %Determine the cutoff values
|
|
|
19 sorted_coverage=sort(read_coverage(nonzero_position));
|
|
|
20 nr_of_nonzero_positions=sum(nonzero_position);
|
|
|
21 relevant_positions=read_coverage<=sorted_coverage(ceil(nr_of_nonzero_positions*censor_frac));
|
|
|
22 MASKS(COUNTER,relevant_positions)=1;
|
|
|
23 COUNTER=COUNTER+1;
|
|
|
24 end
|
