/*************************************************************************
* Converts the motif frequency matrix into a odds matrix: taken from old ama-scan.c
*************************************************************************/
void convert_to_odds_matrix(MOTIF_T* motif, ARRAY_T* bg_freqs){
const int asize = alph_size(get_motif_alph(motif), ALPH_SIZE);
int motif_position_index,alph_index;
MATRIX_T *freqs;
freqs = get_motif_freqs(motif);
const int num_motif_positions = get_num_rows(freqs);
for (alph_index=0;alph_index<asize;++alph_index){
double bg_likelihood = get_array_item(alph_index, bg_freqs);
for (motif_position_index=0;motif_position_index<num_motif_positions;++motif_position_index){
freqs->rows[motif_position_index]->items[alph_index] /= bg_likelihood;
}
}
}
/*************************************************************************
* Copies the motif frequency matrix and converts it into a odds matrix
*************************************************************************/
MATRIX_T* create_odds_matrix(MOTIF_T *motif, ARRAY_T* bg_freqs){
const int asize = alph_size(get_motif_alph(motif), ALPH_SIZE);
int pos, aidx;
MATRIX_T *odds;
odds = duplicate_matrix(get_motif_freqs(motif));
const int num_pos = get_num_rows(odds);
for (aidx = 0; aidx < asize; ++aidx) {
double bg_likelihood = get_array_item(aidx, bg_freqs);
for (pos = 0; pos < num_pos; ++pos) {
odds->rows[pos]->items[aidx] /= bg_likelihood;
}
}
return odds;
}
/*************************************************************************
* Output JSON data for a motif
*************************************************************************/
static void output_motif_json(JSONWR_T* json, MOTIF_STATS_T* stats,
SITE_COUNTS_T* counts) {
//vars
MOTIF_T *motif;
MATRIX_T *freqs;
int i, j, mlen, asize, end;
motif = stats->motif;
freqs = get_motif_freqs(motif);
asize = alph_size(get_motif_alph(motif), ALPH_SIZE);
jsonwr_start_object_value(json);
jsonwr_lng_prop(json, "db", stats->db->id);
jsonwr_str_prop(json, "id", get_motif_id(motif));
if (*(get_motif_id2(motif))) {
jsonwr_str_prop(json, "alt", get_motif_id2(motif));
}
mlen = get_motif_length(motif);
jsonwr_lng_prop(json, "len", mlen);
jsonwr_dbl_prop(json, "motif_evalue", get_motif_evalue(motif));
jsonwr_dbl_prop(json, "motif_nsites", get_motif_nsites(motif));
if (get_motif_url(motif) && *get_motif_url(motif)) {
jsonwr_str_prop(json, "url", get_motif_url(motif));
}
jsonwr_property(json, "pwm");
jsonwr_start_array_value(json);
for (i = 0; i < mlen; i++) {
jsonwr_start_array_value(json);
for (j = 0; j < asize; j++) {
jsonwr_dbl_value(json, get_matrix_cell(i, j, freqs));
}
jsonwr_end_array_value(json);
}
jsonwr_end_array_value(json);
jsonwr_lng_prop(json, "bin_width", stats->central_window+1);
jsonwr_dbl_prop(json, "bin_sites", stats->central_sites);
jsonwr_lng_prop(json, "total_sites", counts->total_sites);
jsonwr_dbl_prop(json, "log_pvalue", stats->log_adj_pvalue);
jsonwr_dbl_prop(json, "max_prob", stats->max_prob);
jsonwr_property(json, "sites");
jsonwr_start_array_value(json);
end = counts->allocated - (mlen - 1);
for (i = (mlen - 1); i < end; i += 2) {
jsonwr_dbl_value(json, counts->sites[i]);
}
jsonwr_end_array_value(json);
jsonwr_end_object_value(json);
}
/*************************************************************************
* Entry point for pmp_bf
*************************************************************************/
int main(int argc, char *argv[]) {
char* bg_filename = NULL;
char* motif_name = "motif"; // Use this motif name in the output.
STRING_LIST_T* selected_motifs = NULL;
double fg_rate = 1.0;
double bg_rate = 1.0;
double purine_pyrimidine = 1.0; // r
double transition_transversion = 0.5; // R
double pseudocount = 0.1;
GAP_SUPPORT_T gap_support = SKIP_GAPS;
MODEL_TYPE_T model_type = F81_MODEL;
BOOLEAN_T use_halpern_bruno = FALSE;
char* ustar_label = NULL; // TLB; create uniform star tree
int i;
program_name = "pmp_bf";
/**********************************************
* COMMAND LINE PROCESSING
**********************************************/
// Define command line options. (FIXME: Repeated code)
// FIXME: Note that if you add or remove options you
// must change n_options.
int n_options = 12;
cmdoption const pmp_options[] = {
{"hb", NO_VALUE},
{"ustar", REQUIRED_VALUE},
{"model", REQUIRED_VALUE},
{"pur-pyr", REQUIRED_VALUE},
{"transition-transversion", REQUIRED_VALUE},
{"bg", REQUIRED_VALUE},
{"fg", REQUIRED_VALUE},
{"motif", REQUIRED_VALUE},
{"motif-name", REQUIRED_VALUE},
{"bgfile", REQUIRED_VALUE},
{"pseudocount", REQUIRED_VALUE},
{"verbosity", REQUIRED_VALUE}
};
int option_index = 0;
// Define the usage message.
char usage[1000] = "";
strcat(usage, "USAGE: pmp [options] <tree file> <MEME file>\n");
strcat(usage, "\n");
strcat(usage, " Options:\n");
// Evolutionary model parameters.
strcat(usage, " --hb\n");
strcat(usage, " --model single|average|jc|k2|f81|f84|hky|tn");
strcat(usage, " (default=f81)\n");
strcat(usage, " --pur-pyr <float> (default=1.0)\n");
strcat(usage, " --transition-transversion <float> (default=0.5)\n");
strcat(usage, " --bg <float> (default=1.0)\n");
strcat(usage, " --fg <float> (default=1.0)\n");
// Motif parameters.
strcat(usage, " --motif <id> (default=all)\n");
strcat(usage, " --motif-name <string> (default from motif file)\n");
// Miscellaneous parameters
strcat(usage, " --bgfile <background> (default from motif file)\n");
strcat(usage, " --pseudocount <float> (default=0.1)\n");
strcat(usage, " --ustar <label>\n"); // TLB; create uniform star tree
strcat(usage, " --verbosity [1|2|3|4] (default 2)\n");
strcat(usage, "\n Prints the FP and FN rate at each of 10000 score values.\n");
strcat(usage, "\n Output format: [<motif_id> score <score> FPR <fpr> TPR <tpr>]+\n");
// Parse the command line.
if (simple_setopt(argc, argv, n_options, pmp_options) != NO_ERROR) {
die("Error processing command line options: option name too long.\n");
}
while (TRUE) {
int c = 0;
char* option_name = NULL;
char* option_value = NULL;
const char * message = NULL;
// Read the next option, and break if we're done.
c = simple_getopt(&option_name, &option_value, &option_index);
if (c == 0) {
break;
} else if (c < 0) {
(void) simple_getopterror(&message);
die("Error processing command line options (%s)\n", message);
}
if (strcmp(option_name, "model") == 0) {
if (strcmp(option_value, "jc") == 0) {
model_type = JC_MODEL;
} else if (strcmp(option_value, "k2") == 0) {
model_type = K2_MODEL;
} else if (strcmp(option_value, "f81") == 0) {
model_type = F81_MODEL;
} else if (strcmp(option_value, "f84") == 0) {
model_type = F84_MODEL;
} else if (strcmp(option_value, "hky") == 0) {
model_type = HKY_MODEL;
} else if (strcmp(option_value, "tn") == 0) {
model_type = TAMURA_NEI_MODEL;
} else if (strcmp(option_value, "single") == 0) {
model_type = SINGLE_MODEL;
} else if (strcmp(option_value, "average") == 0) {
model_type = AVERAGE_MODEL;
} else {
die("Unknown model: %s\n", option_value);
}
} else if (strcmp(option_name, "hb") == 0){
use_halpern_bruno = TRUE;
} else if (strcmp(option_name, "ustar") == 0){ // TLB; create uniform star tree
ustar_label = option_value;
} else if (strcmp(option_name, "pur-pyr") == 0){
purine_pyrimidine = atof(option_value);
} else if (strcmp(option_name, "transition-transversion") == 0){
transition_transversion = atof(option_value);
} else if (strcmp(option_name, "bg") == 0){
bg_rate = atof(option_value);
} else if (strcmp(option_name, "fg") == 0){
fg_rate = atof(option_value);
} else if (strcmp(option_name, "motif") == 0){
if (selected_motifs == NULL) {
selected_motifs = new_string_list();
}
add_string(option_value, selected_motifs);
} else if (strcmp(option_name, "motif-name") == 0){
motif_name = option_value;
} else if (strcmp(option_name, "bgfile") == 0){
bg_filename = option_value;
} else if (strcmp(option_name, "pseudocount") == 0){
pseudocount = atof(option_value);
} else if (strcmp(option_name, "verbosity") == 0){
verbosity = atoi(option_value);
}
}
// Must have tree and motif file names
if (argc != option_index + 2) {
fprintf(stderr, "%s", usage);
exit(EXIT_FAILURE);
}
/**********************************************
* Read the phylogenetic tree.
**********************************************/
char* tree_filename = NULL;
TREE_T* tree = NULL;
tree_filename = argv[option_index];
option_index++;
tree = read_tree_from_file(tree_filename);
// get the species names
STRING_LIST_T* alignment_species = make_leaf_list(tree);
char *root_label = get_label(tree); // in case target in center
if (strlen(root_label)>0) add_string(root_label, alignment_species);
//write_string_list(" ", alignment_species, stderr);
// TLB; Convert the tree to a uniform star tree with
// the target sequence at its center.
if (ustar_label != NULL) {
tree = convert_to_uniform_star_tree(tree, ustar_label);
if (tree == NULL)
die("Tree or alignment missing target %s\n", ustar_label);
if (verbosity >= NORMAL_VERBOSE) {
fprintf(stderr,
"Target %s placed at center of uniform (d=%.3f) star tree:\n",
ustar_label, get_total_length(tree) / get_num_children(tree)
);
write_tree(tree, stderr);
}
}
/**********************************************
* Read the motifs.
**********************************************/
char* meme_filename = argv[option_index];
option_index++;
int num_motifs = 0;
MREAD_T *mread;
ALPH_T alph;
ARRAYLST_T *motifs;
ARRAY_T *bg_freqs;
mread = mread_create(meme_filename, OPEN_MFILE);
mread_set_bg_source(mread, bg_filename);
mread_set_pseudocount(mread, pseudocount);
// read motifs
motifs = mread_load(mread, NULL);
alph = mread_get_alphabet(mread);
bg_freqs = mread_get_background(mread);
// check
if (arraylst_size(motifs) == 0) die("No motifs in %s.", meme_filename);
// TLB; need to resize bg_freqs array to ALPH_SIZE items
// or copy array breaks in HB mode. This throws away
// the freqs for the ambiguous characters;
int asize = alph_size(alph, ALPH_SIZE);
resize_array(bg_freqs, asize);
/**************************************************************
* Compute probability distributions for each of the selected motifs.
**************************************************************/
int motif_index;
for (motif_index = 0; motif_index < arraylst_size(motifs); motif_index++) {
MOTIF_T* motif = (MOTIF_T*)arraylst_get(motif_index, motifs);
char* motif_id = get_motif_id(motif);
char* bare_motif_id = motif_id;
// We may have specified on the command line that
// only certain motifs were to be used.
if (selected_motifs != NULL) {
if (*bare_motif_id == '+' || *bare_motif_id == '-') {
// The selected motif id won't included a strand indicator.
bare_motif_id++;
}
if (have_string(bare_motif_id, selected_motifs) == FALSE) {
continue;
}
}
if (verbosity >= NORMAL_VERBOSE) {
fprintf(
stderr,
"Using motif %s of width %d.\n",
motif_id, get_motif_length(motif)
);
}
// Build an array of evolutionary models for each position in the motif.
EVOMODEL_T** models = make_motif_models(
motif,
bg_freqs,
model_type,
fg_rate,
bg_rate,
purine_pyrimidine,
transition_transversion,
use_halpern_bruno
);
// Get the frequencies under the background model (row 0)
// and position-dependent scores (rows 1..w)
// for each possible alignment column.
MATRIX_T* pssm_matrix = build_alignment_pssm_matrix(
alph,
alignment_species,
get_motif_length(motif) + 1,
models,
tree,
gap_support
);
ARRAY_T* alignment_col_freqs = allocate_array(get_num_cols(pssm_matrix));
copy_array(get_matrix_row(0, pssm_matrix), alignment_col_freqs);
remove_matrix_row(0, pssm_matrix); // throw away first row
//print_col_frequencies(alph, alignment_col_freqs);
//
// Get the position-dependent null model alignment column frequencies
//
int w = get_motif_length(motif);
int ncols = get_num_cols(pssm_matrix);
MATRIX_T* pos_dep_bkg = allocate_matrix(w, ncols);
for (i=0; i<w; i++) {
// get the evo model corresponding to this column of the motif
// and store it as the first evolutionary model.
myfree(models[0]);
// Use motif PSFM for equilibrium freqs. for model.
ARRAY_T* site_specific_freqs = allocate_array(asize);
int j = 0;
for(j = 0; j < asize; j++) {
double value = get_matrix_cell(i, j, get_motif_freqs(motif));
set_array_item(j, value, site_specific_freqs);
}
if (use_halpern_bruno == FALSE) {
models[0] = make_model(
model_type,
fg_rate,
transition_transversion,
purine_pyrimidine,
site_specific_freqs,
NULL
);
} else {
models[0] = make_model(
model_type,
fg_rate,
transition_transversion,
purine_pyrimidine,
bg_freqs,
site_specific_freqs
);
}
// get the alignment column frequencies using this model
MATRIX_T* tmp_pssm_matrix = build_alignment_pssm_matrix(
alph,
alignment_species,
2, // only interested in freqs under bkg
models,
tree,
gap_support
);
// assemble the position-dependent background alignment column freqs.
set_matrix_row(i, get_matrix_row(0, tmp_pssm_matrix), pos_dep_bkg);
// chuck the pssm (not his real name)
free_matrix(tmp_pssm_matrix);
}
//
// Compute and print the score distribution under the background model
// and under the (position-dependent) motif model.
//
int range = 10000; // 10^4 gives same result as 10^5, but 10^3 differs
// under background model
PSSM_T* pssm = build_matrix_pssm(alph, pssm_matrix, alignment_col_freqs, range);
// under position-dependent background (motif) model
PSSM_T* pssm_pos_dep = build_matrix_pssm(alph, pssm_matrix, alignment_col_freqs, range);
get_pv_lookup_pos_dep(
pssm_pos_dep,
pos_dep_bkg,
NULL // no priors used
);
// print FP and FN distributions
int num_items = get_pssm_pv_length(pssm_pos_dep);
for (i=0; i<num_items; i++) {
double pvf = get_pssm_pv(i, pssm);
double pvt = get_pssm_pv(i, pssm_pos_dep);
double fpr = pvf;
double fnr = 1 - pvt;
if (fpr >= 0.99999 || fnr == 0) continue;
printf("%s score %d FPR %.3g FNR %.3g\n", motif_id, i, fpr, fnr);
}
// free stuff
free_pssm(pssm);
free_pssm(pssm_pos_dep);
if (models != NULL) {
int model_index;
int num_models = get_motif_length(motif) + 1;
for (model_index = 0; model_index < num_models; model_index++) {
free_model(models[model_index]);
}
myfree(models);
}
} // motif
arraylst_destroy(destroy_motif, motifs);
/**********************************************
* Clean up.
**********************************************/
// TLB may have encountered a memory corruption bug here
// CEG has not been able to reproduce it. valgrind says all is well.
free_array(bg_freqs);
free_tree(TRUE, tree);
free_string_list(selected_motifs);
return(0);
} // main
/*************************************************************************
* Build a completely connected HMM.
*************************************************************************/
void build_complete_hmm
(ARRAY_T* background,
int spacer_states,
MOTIF_T *motifs,
int nmotifs,
MATRIX_T *transp_freq,
MATRIX_T *spacer_ave,
BOOLEAN_T fim,
MHMM_T **the_hmm)
{
ALPH_T alph;
int motif_states; // Total length of the motifs.
int num_spacers; // Total number of spacer states.
int num_states; // Total number of states in the model.
int i_motif; // Index of the current "from" motif.
int j_motif; // Index of the current "to" motif.
int i_position; // Index within the current motif or spacer.
int i_state = 0; // Index of the current state.
assert(nmotifs > 0);
alph = get_motif_alph(motifs);// get the alphabet from the first motif
// Count the width of the motifs.
for (motif_states = 0, i_motif = 0; i_motif < nmotifs; i_motif++)
motif_states += get_motif_length(motif_at(motifs, i_motif));
// Count the spacer states adjacent to begin and end.
num_spacers = nmotifs * 2;
// Add the spacer states between motifs.
num_spacers += nmotifs * nmotifs;
// Total states = motifs + spacer_states + begin/end
num_states = motif_states + (num_spacers * spacer_states) + 2;
// Allocate the model.
*the_hmm = allocate_mhmm(alph, num_states);
// Record that this is a completely connected model.
(*the_hmm)->type = COMPLETE_HMM;
// Record the number of motifs in the model.
(*the_hmm)->num_motifs = nmotifs;
// Record the number of states in the model.
(*the_hmm)->num_states = num_states;
(*the_hmm)->num_spacers = ((nmotifs + 1) * (nmotifs + 1)) - 1;
(*the_hmm)->spacer_states = spacer_states;
// Put the background distribution into the model.
copy_array(background, (*the_hmm)->background);
// Build the begin state.
build_complete_state(
START_STATE,
i_state,
alph,
0, // expected length
NULL, // Emissions.
0, // Number of sites.
NON_MOTIF_INDEX,
NON_MOTIF_POSITION,
nmotifs,
0, // previous motif
0, // next motif
transp_freq,
spacer_states,
num_spacers,
motifs,
&((*the_hmm)->states[i_state]));
i_state++;
int from_motif_state, to_motif_state;
// Build the spacer states. No transitions from the end state.
for (i_motif = 0; i_motif <= nmotifs; i_motif++) {
// No transitions to the start state.
for (j_motif = 1; j_motif <= nmotifs+1; j_motif++) {
// No transitions from start to end.
if ((i_motif == 0) && (j_motif == nmotifs+1))
continue;
// Allow multi-state spacers.
for (i_position = 0; i_position < spacer_states; i_position++, i_state++) {
build_complete_state(
SPACER_STATE,
i_state,
alph,
get_matrix_cell(i_motif, j_motif, spacer_ave),
background,
SPACER_NUMSITES,
NON_MOTIF_INDEX,
i_position,
nmotifs,
i_motif,
j_motif,
transp_freq,
spacer_states,
num_spacers,
motifs,
&((*the_hmm)->states[i_state]));
}
}
}
// Build the motif states.
for (i_motif = 0; i_motif < nmotifs; i_motif++) {
MOTIF_T *this_motif = motif_at(motifs, i_motif);
STATE_T state;
for (i_position = 0; i_position < get_motif_length(this_motif); i_position++, i_state++) {
if (i_position == 0) {
state = START_MOTIF_STATE;
} else if (i_position == (get_motif_length(this_motif) - 1)) {
state = END_MOTIF_STATE;
} else {
state = MID_MOTIF_STATE;
}
build_complete_state(
MID_MOTIF_STATE,
i_state,
alph,
0, // Expected spacer length.
get_matrix_row(i_position, get_motif_freqs(this_motif)),
get_motif_nsites(this_motif),
i_motif,
i_position,
nmotifs,
0, // Previous motif index.
0, // Next motif index.
transp_freq,
spacer_states,
num_spacers,
motifs,
&((*the_hmm)->states[i_state]));
}
}
// Build the end state.
build_complete_state(
END_STATE,
i_state,
alph,
0, // Expected spacer length.
NULL, // Emissions
0, // Number of sites.
NON_MOTIF_INDEX,
NON_MOTIF_POSITION,
nmotifs,
0, // Previous motif index.
0, // Next motif index.
transp_freq,
spacer_states,
num_spacers,
motifs,
&((*the_hmm)->states[i_state]));
i_state++;
// Convert spacers to FIMs if requested.
if (fim) {
convert_to_fims(*the_hmm);
}
// Fill in the transition matrix.
build_transition_matrix(*the_hmm);
}
/*************************************************************************
* Build a linear HMM.
*************************************************************************/
void build_linear_hmm
(ARRAY_T* background,
ORDER_T* order_spacing,
int spacer_states,
RBTREE_T* motifs, // motifs with key as in order_spacing
BOOLEAN_T fim,
MHMM_T** the_hmm)
{
ALPH_T alph;
int model_length; // Total number of states in the model.
int i_state; // Index of the current state.
int i_order; // Index within the order and spacing.
int i_position; // Index within the current motif or spacer.
int motif_i; // motif key in order spacing
MOTIF_T *motif; // motif
RBNODE_T *node;
alph = get_motif_alph((MOTIF_T*)rbtree_value(rbtree_first(motifs)));
// Calculate the total length of the model.
model_length = 2; // start and end state
for (i_order = 0; i_order < get_order_occurs(order_spacing); i_order++) {
motif_i = get_order_motif(order_spacing, i_order);
motif = (MOTIF_T*)rbtree_get(motifs, &motif_i);
model_length += get_motif_length(motif);
}
model_length += (get_order_occurs(order_spacing) + 1) * spacer_states;
// Allocate the model.
*the_hmm = allocate_mhmm(alph, model_length);
check_sq_matrix((*the_hmm)->trans, model_length);
// Record that this is a linear model.
(*the_hmm)->type = LINEAR_HMM;
// Record the number of motifs in the model.
// It doesn't want the distinct count
(*the_hmm)->num_motifs = get_order_occurs(order_spacing);
// Record the number of states in the model.
(*the_hmm)->num_states = model_length;
(*the_hmm)->num_spacers = get_order_occurs(order_spacing) + 1;
(*the_hmm)->spacer_states = spacer_states;
// Put the background distribution into the model.
copy_array(background, (*the_hmm)->background);
// Begin the model with a non-emitting state.
i_state = 0;
check_sq_matrix((*the_hmm)->trans, (*the_hmm)->num_states);
build_linear_state(
alph,
START_STATE,
i_state,
get_spacer_length(order_spacing, 0),
NULL, // Emissions.
0, // Number of sites.
NON_MOTIF_INDEX,
NON_MOTIF_POSITION, // position within state (not relevant to start state)
NULL, // no motif
&((*the_hmm)->states[i_state]));
++i_state;
// Build the first spacer.
for (i_position = 0; i_position < spacer_states; i_position++, i_state++) {
check_sq_matrix((*the_hmm)->trans, (*the_hmm)->num_states);
build_linear_state(
alph,
SPACER_STATE,
i_state,
get_spacer_length(order_spacing, 0),
background,
SPACER_NUMSITES,
NON_MOTIF_INDEX,
i_position, // position within spacer
NULL, // no motif
&((*the_hmm)->states[i_state]));
}
// Build each motif and subsequent spacer.
for (i_order = 0; i_order < get_order_occurs(order_spacing); i_order++) {
STATE_T state;
int spacer_len;
motif_i = get_order_motif(order_spacing, i_order);
motif = (MOTIF_T*)rbtree_get(motifs, &motif_i);
// Build the motif.
for (i_position = 0; i_position < get_motif_length(motif); i_position++, i_state++) {
if (i_position == 0) {
state = START_MOTIF_STATE;
spacer_len = get_spacer_length(order_spacing, i_order);
} else if (i_position == (get_motif_length(motif) - 1)) {
state = END_MOTIF_STATE;
spacer_len = get_spacer_length(order_spacing, i_order+1);
} else {
state = MID_MOTIF_STATE;
spacer_len = 0;
}
check_sq_matrix((*the_hmm)->trans, (*the_hmm)->num_states);
build_linear_state(
alph,
state,
i_state,
spacer_len, // Expected spacer length.
get_matrix_row(i_position, get_motif_freqs(motif)),
get_motif_nsites(motif),
i_order,
i_position, // position within motif (middle)
motif,
&((*the_hmm)->states[i_state]));
}
// Build the following spacer.
for (i_position = 0; i_position < spacer_states; i_position++, i_state++) {
check_sq_matrix((*the_hmm)->trans, (*the_hmm)->num_states);
build_linear_state(
alph,
SPACER_STATE,
i_state,
get_spacer_length(order_spacing, i_order+1),
background,
SPACER_NUMSITES,
NON_MOTIF_INDEX,
i_position, // position within spacer
NULL, // no motif
&((*the_hmm)->states[i_state]));
}
}
check_sq_matrix((*the_hmm)->trans, (*the_hmm)->num_states);
// Finish up the model with a non-emitting end state.
build_linear_state(
alph,
END_STATE,
i_state,
get_spacer_length(order_spacing, i_order),
NULL, // Emissions.
0, // Number of sites.
NON_MOTIF_INDEX,
NON_MOTIF_POSITION, // position within state (not relevant to end state)
NULL, // no motif
&((*the_hmm)->states[i_state]));
++i_state;
assert(i_state == model_length);
check_sq_matrix((*the_hmm)->trans, (*the_hmm)->num_states);
// Convert spacers to FIMs if requested.
if (fim) {
convert_to_fims(*the_hmm);
}
// Fill in the transition matrix.
build_transition_matrix(*the_hmm);
}
/*************************************************************************
* Build a star topology HMM.
*************************************************************************/
void build_star_hmm
(ARRAY_T* background,
int spacer_states,
MOTIF_T* motifs,
int nmotifs,
BOOLEAN_T fim,
MHMM_T** the_hmm)
{
ALPH_T alph;
int motif_states; /* Total length of the motifs. */
int num_spacers; /* Total number of spacer states. */
int num_states; /* Total number of states in the model. */
int i_motif; /* Index of the current "from" motif. */
int i_position; /* Index within the current motif or spacer. */
int i_state = 0; /* Index of the current state. */
alph = get_motif_alph(motif_at(motifs, 0));
/* Count the width of the motifs. */
for (motif_states = 0, i_motif = 0; i_motif < nmotifs; i_motif++)
motif_states += get_motif_length(motif_at(motifs, i_motif));
// Only 1 spacer.
num_spacers = 1;
/* Total states = motifs + spacer_states + begin/end */
num_states = motif_states + (num_spacers * spacer_states) + 2;
/* fprintf(stderr, "motif_states=%d num_spacers=%d num_states=%d\n",
motif_states, num_spacers, num_states); */
/* Allocate the model. */
*the_hmm = allocate_mhmm(alph, num_states);
/* Record that this is a star model. */
(*the_hmm)->type = STAR_HMM;
/* Record the number of motifs in the model. */
(*the_hmm)->num_motifs = nmotifs;
/* Record the number of states in the model. */
(*the_hmm)->num_states = num_states;
(*the_hmm)->num_spacers = 1;
(*the_hmm)->spacer_states = spacer_states;
// Put the background distribution into the model.
copy_array(background, (*the_hmm)->background);
/* Build the begin state. */
build_star_state(
alph,
START_STATE,
i_state,
0, // expected length
NULL,
0, // Number of sites.
NON_MOTIF_INDEX,
NON_MOTIF_POSITION,
nmotifs,
spacer_states,
motifs,
&((*the_hmm)->states[i_state])
);
i_state++;
// Build the spacer state (state 0). Allow multi-state spacers.
for (i_position = 0; i_position < spacer_states; i_position++) {
build_star_state(
alph,
SPACER_STATE,
i_state,
DEFAULT_SPACER_LENGTH,
background,
SPACER_NUMSITES,
NON_MOTIF_INDEX,
i_position,
nmotifs,
spacer_states,
motifs,
&((*the_hmm)->states[i_state])
);
i_state++;
}
/* Build the motif states. */
for (i_motif = 0; i_motif < nmotifs; i_motif++) {
MOTIF_T *this_motif = motif_at(motifs, i_motif);
assert(get_motif_length(this_motif) > 1);
i_position = 0;
build_star_state(
alph,
START_MOTIF_STATE,
i_state,
0, // Expected spacer length.
get_matrix_row(i_position, get_motif_freqs(this_motif)),
get_motif_nsites(this_motif),
i_motif,
i_position,
nmotifs,
spacer_states,
motifs,
&((*the_hmm)->states[i_state])
);
i_state++;
for (i_position = 1; i_position < get_motif_length(this_motif) - 1; i_position++) {
build_star_state(
alph,
MID_MOTIF_STATE,
i_state,
0, // Expected spacer length.
get_matrix_row(i_position, get_motif_freqs(this_motif)),
get_motif_nsites(this_motif),
i_motif,
i_position,
nmotifs,
spacer_states,
motifs,
&((*the_hmm)->states[i_state])
);
i_state++;
}
build_star_state(
alph,
END_MOTIF_STATE,
i_state,
0, // Expected spacer length.
get_matrix_row(i_position, get_motif_freqs(this_motif)),
get_motif_nsites(this_motif),
i_motif,
i_position,
nmotifs,
spacer_states,
motifs,
&((*the_hmm)->states[i_state])
);
i_state++;
}
/* Build the end state. */
build_star_state(
alph,
END_STATE,
i_state,
0, // Expected spacer length.
NULL, // Emissions
0, // Number of sites.
NON_MOTIF_INDEX,
NON_MOTIF_POSITION,
nmotifs,
spacer_states,
motifs,
&((*the_hmm)->states[i_state])
);
i_state++;
/* Convert spacers to FIMs if requested. */
if (fim) {
convert_to_fims(*the_hmm);
}
/* Fill in the transition matrix. */
build_transition_matrix(*the_hmm);
} // build_star_hmm
void ramen_scan_sequences() {
FILE* seq_file = NULL;
MOTIF_T* motif = NULL;
MOTIF_T* rev_motif = NULL;
SEQ_T* sequence = NULL;
SCANNED_SEQUENCE_T* scanned_seq = NULL;
PATTERN_T* pattern;
int i;
int j;
SEQ_T** seq_list;
int num_seqs;
int seq_len;
//For the bdb_bg mode:
ARRAY_T* seq_bg_freqs;
double atcontent;
double roundatcontent;
double avg_seq_length = 0;
//Open the file.
if (open_file(args.sequence_filename, "r", FALSE, "FASTA", "sequences", &seq_file) == 0) {
fprintf(stderr, "Couldn't open the file %s.\n", args.sequence_filename);
ramen_terminate(1);
}
//Start reading in the sequences
read_many_fastas(ramen_alph, seq_file, MAX_SEQ_LENGTH, &num_seqs, &seq_list);
seq_ids = new_string_list();
seq_fscores = allocate_array(num_seqs);
//Allocate the required space for results
results = malloc(sizeof(double*) * motifs.num);
for (i=0;i<motifs.num;i++) {
results[i] = malloc(sizeof(double)*num_seqs);
}
for (j=0;j<num_seqs;j++) {
fprintf(stderr, "\rScanning %i of %i sequences...", j+1, num_seqs);
//copy the pointer into our current object for clarity
sequence = seq_list[j];
//Read the fluorescence data from the description field.
add_string(get_seq_name(sequence),seq_ids);
seq_len = get_seq_length(sequence);
set_array_item(j,atof(get_seq_description(sequence)),seq_fscores);
//Scan with each motif.
for (i=0;i<motifs.num;i++) {
int motifindex = i*2;
results[i][j] = ramen_sequence_scan(sequence, motif_at(motifs.motifs, motifindex),
motif_at(motifs.motifs, motifindex+1),
NULL, NULL, //No need to pass PSSM.
AVG_ODDS, 0, TRUE, 0, motifs.bg_freqs);
if (TRUE == args.linreg_normalise) {
int k;
double maxscore = 1;
motif = motif_at(motifs.motifs,motifindex);
for (k=0;k<get_motif_length(motif);k++) {
double maxprob = 0;
if (maxprob < get_matrix_cell(k, alph_index(ramen_alph, 'A'), get_motif_freqs(motif)))
maxprob = get_matrix_cell(k, alph_index(ramen_alph, 'A'), get_motif_freqs(motif));
if (maxprob < get_matrix_cell(k, alph_index(ramen_alph, 'C'), get_motif_freqs(motif)))
maxprob = get_matrix_cell(k, alph_index(ramen_alph, 'C'), get_motif_freqs(motif));
if (maxprob < get_matrix_cell(k, alph_index(ramen_alph, 'G'), get_motif_freqs(motif)))
maxprob = get_matrix_cell(k, alph_index(ramen_alph, 'G'), get_motif_freqs(motif));
if (maxprob < get_matrix_cell(k, alph_index(ramen_alph, 'T'), get_motif_freqs(motif)))
maxprob = get_matrix_cell(k, alph_index(ramen_alph, 'T'), get_motif_freqs(motif));
maxscore *= maxprob;
}
results[i][j] /= maxscore;
}
}
}
}
/*************************************************************************
* Calculate the odds score for each motif-sized window at each
* site in the sequence using the given nucleotide frequencies.
*
* This function is a lightweight version based on the one contained in
* motiph-scoring. Several calculations that are unnecessary for gomo
* have been removed in order to speed up the process
*************************************************************************/
double score_sequence(
SEQ_T* seq, // sequence to scan (IN)
MOTIF_T* motif, // motif already converted to odds values (IN)
PSSM_T* pssm, // motif pssm
char* feature_type, // motif name (IN)
char* seq_name, // sequence name (IN)
int method, // method used for scoring (IN)
double threshold, // Threshold to use in TOTAL_HITS mode with a PWM
ARRAY_T* bg_freqs //background model
)
{
assert(seq != NULL);
assert(motif != NULL);
// Get data for sequence
if (seq_name == NULL) {
seq_name = get_seq_name(seq);
}
char* raw_seq = get_raw_sequence(seq);
int seq_length = get_seq_length(seq);
// Get the pv lookup table
ARRAY_T* pv_lookup = NULL;
if (NULL != pssm) {
pv_lookup = pssm->pv;
assert(get_array_length(pv_lookup) > 0);
}
// Prepare storage for the string representing the portion
// of the reference sequence within the window.
char* window_seq = (char *) mm_malloc(sizeof(char) * (get_motif_length(motif) + 1));
window_seq[get_motif_length(motif)] = '\0';
// Get a character for the strand.
char strand = 0;
if (get_motif_id(motif)!= NULL) {
get_motif_strand(motif);
} else {
strand = '.';
}
int max_index = seq_length - get_motif_length(motif);
const int asize = alph_size(get_motif_alph(motif), ALPH_SIZE);
double* odds = (double*) mm_malloc(sizeof(double)*max_index);
double* scaled_log_odds = (double*) mm_malloc(sizeof(double)*max_index);
// For each site in the sequence
int seq_index;
for (seq_index = 0; seq_index < max_index; seq_index++) {
BOOLEAN_T skip_window = FALSE;
BOOLEAN_T found_gap = FALSE;
BOOLEAN_T found_ambiguity = FALSE;
double odd = 1.0;
scaled_log_odds[seq_index] = 0;
// For each site in the motif window
int motif_position;
for (motif_position = 0; motif_position < get_motif_length(motif); motif_position++) {
char c = raw_seq[seq_index + motif_position];
window_seq[motif_position] = c;
// Check for gaps at this site
if(c == '-' || c == '.') {
found_gap = TRUE;
skip_window = TRUE;
break;
}
// Check for ambiguity codes at this site
//TODO: This next call is very expensive - it takes up approx. 10% of a
// programme's running time. It should be fixed up somehow.
int aindex = alph_index(get_motif_alph(motif), c);
if (aindex > asize) {
found_ambiguity = TRUE;
skip_window = TRUE;
break;
}
if (method == TOTAL_HITS) {
//If we're in this mode, then we're using LOG ODDS.
//scaled_log_odds[seq_index] += get_matrix_cell(motif_position, aindex, get_motif_freqs(motif));
scaled_log_odds[seq_index] += get_matrix_cell(motif_position, aindex, pssm->matrix);
} else {
odd *= get_matrix_cell(motif_position, aindex, get_motif_freqs(motif));
}
}
odds[seq_index] = odd;
}
// return odds as requested (MAX or AVG scoring)
double requested_odds = 0.0;
if (method == AVG_ODDS){
for (seq_index = 0; seq_index < max_index; seq_index++) {
requested_odds += odds[seq_index];
}
requested_odds /= max_index;
} else if (method == MAX_ODDS){
for (seq_index = 0; seq_index < max_index; seq_index++) {
if (odds[seq_index] > requested_odds){
requested_odds = odds[seq_index];
}
}
} else if (method == SUM_ODDS) {
for (seq_index = 0; seq_index < max_index; seq_index++) {
requested_odds += odds[seq_index];
}
} else if (method == TOTAL_HITS) {
for (seq_index = 0; seq_index < max_index; seq_index++) {
if (scaled_log_odds[seq_index] >= (double)get_array_length(pv_lookup)) {
scaled_log_odds[seq_index] = (double)(get_array_length(pv_lookup) - 1);
}
double pvalue = get_array_item((int) scaled_log_odds[seq_index], pv_lookup);
//Figure out how to calculate the p-value of a hit
//fprintf(stderr, "m: %s pv_l len: %i scaled_log_odds: %g seq index: %i pvalue: %g\n",
// get_motif_id(motif), get_array_length(pv_lookup), scaled_log_odds[seq_index], seq_index, pvalue);
if (pvalue < threshold) {
requested_odds++; //Add another hit.
}
if (verbosity > HIGHER_VERBOSE) {
fprintf(stderr, "Window Data: %s\t%s\t%i\t%g\t%g\t%g\n",
get_seq_name(seq), get_motif_id(motif), seq_index, scaled_log_odds[seq_index], pvalue, threshold);
}
}
}
myfree(odds);
myfree(scaled_log_odds);
myfree(window_seq);
return requested_odds;
}
