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-rw-r--r--src/c/quikr_train.c203
1 files changed, 136 insertions, 67 deletions
diff --git a/src/c/quikr_train.c b/src/c/quikr_train.c
index 1cf6be9..4d66b9d 100644
--- a/src/c/quikr_train.c
+++ b/src/c/quikr_train.c
@@ -8,30 +8,38 @@
#include <unistd.h>
#include <zlib.h>
+#include "kmer_utils.h"
#include "quikr_functions.h"
#define USAGE "Usage:\n\tquikr_train [OPTION...] - train a database for use with quikr.\n\nOptions:\n\n-i, --input\n\tthe database of sequences to create the sensing matrix (fasta format)\n\n-k, --kmer\n\tspecify what size of kmer to use. (default value is 6)\n\n-o, --output\n\tthe sensing matrix. (a gzip'd text file)\n\n-v, --verbose\n\tverbose mode.\n\n-V, --version\n\tprint version."
int main(int argc, char **argv) {
- char probabilities_command[512];
+ // getline variables
char *line = NULL;
- char *val;
size_t len = 0;
+ ssize_t read;
int c;
- int kmer = 6;
- char *fasta_file = NULL;
- char *output_file = NULL;
+ // k-mer is 6 by default
+ int kmer = 6;
- int x = 0;
- int y = 0;
+ // revision number
+ int revision = 0;
+ // iterators
+ long long i = 0;
+ long long position = 0;
int verbose = 0;
+
+ char *fasta_filename = NULL;
+ char *output_file = NULL;
+
gzFile output = NULL;
+ FILE *input = NULL;
while (1) {
static struct option long_options[] = {
@@ -53,7 +61,7 @@ int main(int argc, char **argv) {
switch (c) {
case 'i':
- fasta_file = optarg;
+ fasta_filename = optarg;
break;
case 'k':
kmer = atoi(optarg);
@@ -80,8 +88,7 @@ int main(int argc, char **argv) {
}
}
-
- if(fasta_file == NULL) {
+ if(fasta_filename == NULL) {
fprintf(stderr, "Error: input fasta file (-i) must be specified\n\n");
fprintf(stderr, "%s\n", USAGE);
exit(EXIT_FAILURE);
@@ -95,15 +102,20 @@ int main(int argc, char **argv) {
if(verbose) {
printf("kmer size: %d\n", kmer);
- printf("fasta file: %s\n", fasta_file);
+ printf("fasta file: %s\n", fasta_filename);
printf("output file: %s\n", output_file);
}
- if(access (fasta_file, F_OK) == -1) {
- fprintf(stderr, "Error: could not find %s\n", fasta_file);
+ if(access (fasta_filename, F_OK) == -1) {
+ fprintf(stderr, "Error: could not find %s\n", fasta_filename);
exit(EXIT_FAILURE);
}
+ if(kmer == 0) {
+ fprintf(stderr, "Error: zero is not a valid kmer\n");
+ exit(EXIT_FAILURE);
+ }
+
if(strcmp(&output_file[strlen(output_file) - 3], ".gz") != 0) {
char *temp = malloc(strlen(output_file) + 4);
if(temp == NULL) {
@@ -115,74 +127,131 @@ int main(int argc, char **argv) {
printf("appending a .gz to our output file: %s\n", output_file);
}
- // 4 ^ Kmer gives us the width, or the number of permutations of ACTG with kmer length
- int width = pow(4, kmer);
- int sequences = count_sequences(fasta_file);
+ // 4 ^ Kmer gives us the width, or the number of permutations of ACTG with
+ // kmer length
+ long width = pow(4, kmer);
+ unsigned long sequences = count_sequences(fasta_filename);
if(sequences == 0) {
- fprintf(stderr, "Error: %s contains 0 fasta sequences\n", fasta_file);
+ fprintf(stderr, "Error: %s contains 0 fasta sequences\n", fasta_filename);
}
- if(verbose)
- printf("sequences: %d\nwidth: %d\n", sequences, width);
-
- // Allocate our matrix with the appropriate size, just one row
- double *trained_matrix = malloc(width*sizeof(double));
- if(trained_matrix == NULL) {
- fprintf(stderr, "Could not allocate enough memory\n");
- exit(EXIT_FAILURE);
- }
+ if(verbose) {
+ printf("sequences: %ld\nwidth: %ld\n", sequences, width);
+ printf("Writing our sensing matrix to %s\n", output_file);
+ }
- // call the probabilities-by-read command
- sprintf(probabilities_command, "generate_kmers %d | probabilities-by-read %d %s /dev/stdin", kmer, kmer, fasta_file);
- FILE *probabilities_output = popen(probabilities_command, "r");
- if(probabilities_output == NULL) {
- fprintf(stderr, "Error could not execute: %s\n", probabilities_command);
+ input = fopen(fasta_filename, "r" );
+ if(input == NULL) {
+ fprintf(stderr, "Error opening %s - %s\n", fasta_filename, strerror(errno));
exit(EXIT_FAILURE);
}
// open our output file
- output = gzopen(output_file, "w6");
+ output = gzopen(output_file, "w");
if(output == NULL) {
- fprintf(stderr, "Error: could not open output file, error code: %d", errno);
+ fprintf(stderr, "Error: could not open output file, error code: %s\n", strerror(errno));
exit(EXIT_FAILURE);
}
- if(verbose)
- printf("Writing our sensing matrix to %s\n", output_file);
-
- // read normalize and write our matrix in one go
- for(x = 0; x < sequences; x++) {
+ // create our header
+ gzprintf(output, "quikr\n");
+ gzprintf(output, "%ld\n", revision);
+ gzprintf(output, "%ld\n", sequences);
+ gzprintf(output, "%d\n", kmer);
- getline(&line, &len, probabilities_output);
-
- // Read our first element in outside of the loop
- val = strtok(line,"\t\n\r");
- trained_matrix[0] = atof(val);
- // iterate through and load the array
- for (y = 1; y < width; y++) {
- val = strtok (NULL, "\t\n\r");
- trained_matrix[y] = atof(val);
- }
-
- double row_sum = 0;
-
- for( y = 0; y < width; y++) {
- row_sum = row_sum + trained_matrix[y];
- }
-
- for( y = 0; y < width; y++) {
- trained_matrix[y] = trained_matrix[y] / row_sum;
- }
-
- for( y = 0; y < (width - 1); y++) {
- gzprintf(output, "%.10f\t", trained_matrix[y]);
- }
- gzprintf(output, "%.10f\n", trained_matrix[width]);
- }
+ // malloc our return array
+ unsigned long long * counts = malloc((width+ 1) * sizeof(unsigned long long));
+ if(counts == NULL) {
+ fprintf(stderr, strerror(errno));
+ exit(EXIT_FAILURE);
+ }
+
+
+ char *str = malloc(4096);
+ if(str == NULL) {
+ fprintf(stderr, strerror(errno));
+ exit(EXIT_FAILURE);
+ }
+
+ unsigned long long str_size = 4096;
+
+ // seek the first character, and skip over it
+ fseek(input, 1, SEEK_CUR);
+ while ((read = getdelim(&line, &len, '>', input)) != -1) {
+
+ // find first whitespace
+ for(i = 0; i < read; i ++) {
+ if(line[i] == ' ' || line[i] == '\t' || line[i] == '\n')
+ break;
+ }
+
+ // write our header
+ gzprintf(output, ">%.*s\n", i, line);
+
+ // find our first \n, this should be the end of the header
+ char *start = strchr(line, '\n');
+ if(start == NULL)
+ continue;
+
+ size_t start_len = strlen(start);
+
+
+ // if our current str buffer isn't big enough, realloc
+ if(start_len + 1 > str_size + 1) {
+ str = realloc(str, start_len + 1);
+ if(str == NULL) {
+ exit(EXIT_FAILURE);
+ fprintf(stderr, strerror(errno));
+ }
+ }
+
+ // strip out all other newlines to handle multiline sequences
+ str = strnstrip(start, str, '\n',start_len);
+ size_t seq_length = strlen(str);
+
+ // relace A, C, G and T with 0, 1, 2, 3 respectively
+ // everything else is 5
+ for(i = 0; i < seq_length; i++) {
+ str[i] = alpha[(int)str[i]];
+ }
+
+ // set counts to zero
+ memset(counts, 0, width);
+ // loop through our string to process each k-mer
+ for(position = 0; position < (seq_length - kmer + 1); position++) {
+ unsigned long mer = 0;
+ unsigned long multiply = 1;
+
+ // for each char in the k-mer check if it is an error char
+ for(i = position + kmer - 1; i >= position; i--){
+ if(str[i] >> 2) {
+ mer = width;
+ position = i;
+ goto next;
+ }
+
+ // multiply this char in the mer by the multiply
+ // and bitshift the multiply for the next round
+ mer += str[i] * multiply;
+ multiply = multiply << 2;
+ }
+ // use this point to get mer of our loop
+ next:
+ // bump up the mer value in the counts array
+ counts[mer]++;
+ }
+
+ for(i = 0; i < width; i++) {
+ gzprintf(output, "%lld\n", counts[i]);
+ }
+
+ }
+
+ free(counts);
+ free(line);
- free(trained_matrix);
gzclose(output);
- pclose(probabilities_output);
+ fclose(input);
- return 0;
+ return EXIT_SUCCESS;
}