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#include <ctype.h>
#include <errno.h>
#include <getopt.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
#include "nnls.h"
#include "kmer_utils.h"
#include "quikr_functions.h"
#include "quikr.h"
#define sensing_matrix(i,j) (sensing_matrix[width*i + j])
#define USAGE "Usage:\n\tquikr [OPTION...] - Calculate estimated frequencies of bacteria in a sample.\n\nOptions:\n\n-i, --input\n\tthe sample's fasta file of NGS READS (fasta format)\n\n-f, --sensing-fasta\n\tlocation of the fasta file database used to create the sensing matrix (fasta format)\n\n-s, --sensing-matrix\n\t location of the sensing matrix. (trained from quikr_train)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-l, --lambda\n\tlambda value to use. (default value is 10000)\n\n-o, --output\n\tOTU_FRACTION_PRESENT a vector representing the percentage of database sequence's presence in sample. (csv output)\n\n-v, --verbose\n\tverbose mode.\n\n-V, --version\n\tprint version."
int main(int argc, char **argv) {
int c;
char *input_fasta_filename = NULL;
char *sensing_matrix_filename = NULL;
char *output_filename = NULL;
unsigned long long x = 0;
unsigned long long y = 0;
unsigned long long width = 0;
unsigned int kmer = 6;
unsigned long long lambda = 10000;
int verbose = 0;
while (1) {
static struct option long_options[] = {
{"input", required_argument, 0, 'i'},
{"kmer", required_argument, 0, 'k'},
{"lambda", required_argument, 0, 'l'},
{"output", required_argument, 0, 'o'},
{"sensing-fasta", required_argument, 0, 'f'},
{"sensing-matrix", required_argument, 0, 's'},
{"verbose", no_argument, 0, 'v'},
{"version", no_argument, 0, 'V'},
{"help", no_argument, 0, 'h'},
{"debug", no_argument, 0, 'd'},
{0, 0, 0, 0}
};
int option_index = 0;
c = getopt_long (argc, argv, "k:l:f:s:i:o:hdvV", long_options, &option_index);
if (c == -1)
break;
switch (c) {
case 'k':
kmer = atoi(optarg);
break;
case 'l':
lambda = atoi(optarg);
break;
case 's':
sensing_matrix_filename = optarg;
break;
case 'i':
input_fasta_filename = optarg;
break;
case 'o':
output_filename = optarg;
break;
case 'v':
verbose = 1;
break;
case 'V':
printf("%s\n", VERSION);
exit(EXIT_SUCCESS);
break;
case 'h':
printf("%s\n", USAGE);
exit(EXIT_SUCCESS);
break;
default:
break;
}
}
if(sensing_matrix_filename == NULL) {
fprintf(stderr, "Error: sensing matrix filename (-s) must be specified\n\n");
fprintf(stderr, "%s\n", USAGE);
exit(EXIT_FAILURE);
}
if(output_filename == NULL) {
fprintf(stderr, "Error: output filename (-o) must be specified\n\n");
fprintf(stderr, "%s\n", USAGE);
exit(EXIT_FAILURE);
}
if(input_fasta_filename == NULL) {
fprintf(stderr, "Error: input fasta file (-i) must be specified\n\n");
fprintf(stderr, "%s\n", USAGE);
exit(EXIT_FAILURE);
}
if(verbose) {
printf("kmer: %u\n", kmer);
printf("lambda: %llu\n", lambda);
printf("fasta: %s\n", input_fasta_filename);
printf("sensing matrix: %s\n", sensing_matrix_filename);
printf("output: %s\n", output_filename);
}
if(access (sensing_matrix_filename, F_OK) == -1) {
fprintf(stderr, "Error: could not find %s\n", sensing_matrix_filename);
exit(EXIT_FAILURE);
}
if(access (input_fasta_filename, F_OK) == -1) {
fprintf(stderr, "Error: could not find %s\n", input_fasta_filename);
exit(EXIT_FAILURE);
}
if(kmer == 0) {
fprintf(stderr, "Error: zero is not a valid kmer\n");
exit(EXIT_FAILURE);
}
// 4 "ACGT" ^ Kmer gives us the size of output rows
width = pow(4, kmer);
width = width + 1;
// load counts matrix
unsigned long long *integer_counts = get_kmer_counts_from_file(input_fasta_filename, kmer);
double *count_matrix = malloc(sizeof(double) * width);
if(count_matrix == NULL) {
fprintf(stderr, "Could not allocate memory:\n");
exit(EXIT_FAILURE);
}
count_matrix[0] = 0;
for(x = 1; x < width; x++)
count_matrix[x] = (double)integer_counts[x-1];
free(integer_counts);
// normalize our count_matrix
normalize_matrix(count_matrix, 1, width);
for(x = 0; x < width; x++)
count_matrix[x] = count_matrix[x] * lambda;
// load sensing matrix
struct matrix *sensing_matrix = load_sensing_matrix(sensing_matrix_filename);
if(sensing_matrix->kmer != kmer) {
fprintf(stderr, "The sensing_matrix was trained with a different kmer than your requested kmer\n");
exit(EXIT_FAILURE);
}
// multiply our sensing matrix by lambda
for(x = 1; x < sensing_matrix->sequences; x++) {
for(y = 0; y < width - 1; y++) {
sensing_matrix->matrix[width*x + y] = sensing_matrix->matrix[width*x + y] * lambda;
}
}
// set the first column of our sensing matrix to 0
for(x = 0; x < sensing_matrix->sequences; x++) {
sensing_matrix->matrix[width * x] = 1.0;
}
// run NNLS
double *solution = nnls(sensing_matrix->matrix, count_matrix, sensing_matrix->sequences, width);
// normalize our solution vector
normalize_matrix(solution, 1, sensing_matrix->sequences);
// output our matrix
FILE *output_fh = fopen(output_filename, "w");
if(output_fh == NULL) {
fprintf(stderr, "Could not open %s for writing\n", output_filename);
exit(EXIT_FAILURE);
}
for(x = 0; x < sensing_matrix->sequences; x++) {
fprintf(output_fh, "%.10lf\n", solution[x]);
}
fclose(output_fh);
return EXIT_SUCCESS;
}
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