| 1 | /* RAxML-VI-HPC (version 2.2) a program for sequential and parallel estimation of phylogenetic trees |
|---|
| 2 | * Copyright August 2006 by Alexandros Stamatakis |
|---|
| 3 | * |
|---|
| 4 | * Partially derived from |
|---|
| 5 | * fastDNAml, a program for estimation of phylogenetic trees from sequences by Gary J. Olsen |
|---|
| 6 | * |
|---|
| 7 | * and |
|---|
| 8 | * |
|---|
| 9 | * Programs of the PHYLIP package by Joe Felsenstein. |
|---|
| 10 | * |
|---|
| 11 | * This program is free software; you may redistribute it and/or modify its |
|---|
| 12 | * under the terms of the GNU General Public License as published by the Free |
|---|
| 13 | * Software Foundation; either version 2 of the License, or (at your option) |
|---|
| 14 | * any later version. |
|---|
| 15 | * |
|---|
| 16 | * This program is distributed in the hope that it will be useful, but |
|---|
| 17 | * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY |
|---|
| 18 | * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
|---|
| 19 | * for more details. |
|---|
| 20 | * |
|---|
| 21 | * |
|---|
| 22 | * For any other enquiries send an Email to Alexandros Stamatakis |
|---|
| 23 | * Alexandros.Stamatakis@epfl.ch |
|---|
| 24 | * |
|---|
| 25 | * When publishing work that is based on the results from RAxML-VI-HPC please cite: |
|---|
| 26 | * |
|---|
| 27 | * Alexandros Stamatakis:"RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands |
|---|
| 28 | * of taxa and mixed models". |
|---|
| 29 | * Bioinformatics 2006; doi: 10.1093/bioinformatics/btl446 |
|---|
| 30 | */ |
|---|
| 31 | |
|---|
| 32 | #ifndef WIN32 |
|---|
| 33 | #include <unistd.h> |
|---|
| 34 | #endif |
|---|
| 35 | |
|---|
| 36 | #include <math.h> |
|---|
| 37 | #include <time.h> |
|---|
| 38 | #include <stdlib.h> |
|---|
| 39 | #include <stdio.h> |
|---|
| 40 | #include <ctype.h> |
|---|
| 41 | #include <string.h> |
|---|
| 42 | #include "axml.h" |
|---|
| 43 | |
|---|
| 44 | extern char run_id[128]; |
|---|
| 45 | extern char workdir[1024]; |
|---|
| 46 | extern double masterTime; |
|---|
| 47 | |
|---|
| 48 | /* |
|---|
| 49 | function below not very interesting, standard RAxML stuff |
|---|
| 50 | */ |
|---|
| 51 | |
|---|
| 52 | static double testInsertThorough(tree *tr, nodeptr r, nodeptr q, boolean useVector) |
|---|
| 53 | { |
|---|
| 54 | double |
|---|
| 55 | result, |
|---|
| 56 | qz[NUM_BRANCHES], |
|---|
| 57 | z[NUM_BRANCHES]; |
|---|
| 58 | |
|---|
| 59 | nodeptr |
|---|
| 60 | x = q->back, |
|---|
| 61 | s = r->back; |
|---|
| 62 | |
|---|
| 63 | int |
|---|
| 64 | j; |
|---|
| 65 | |
|---|
| 66 | for(j = 0; j < tr->numBranches; j++) |
|---|
| 67 | { |
|---|
| 68 | qz[j] = q->z[j]; |
|---|
| 69 | z[j] = sqrt(qz[j]); |
|---|
| 70 | |
|---|
| 71 | if(z[j] < zmin) |
|---|
| 72 | z[j] = zmin; |
|---|
| 73 | |
|---|
| 74 | if(z[j] > zmax) |
|---|
| 75 | z[j] = zmax; |
|---|
| 76 | } |
|---|
| 77 | |
|---|
| 78 | hookup(r->next, q, z, tr->numBranches); |
|---|
| 79 | hookup(r->next->next, x, z, tr->numBranches); |
|---|
| 80 | hookupDefault(r, s, tr->numBranches); |
|---|
| 81 | |
|---|
| 82 | newviewGeneric(tr, r); |
|---|
| 83 | |
|---|
| 84 | localSmooth(tr, r, smoothings); |
|---|
| 85 | |
|---|
| 86 | if(useVector) |
|---|
| 87 | result = evaluateGenericVector(tr, r); |
|---|
| 88 | else |
|---|
| 89 | result = evaluateGeneric(tr, r); |
|---|
| 90 | |
|---|
| 91 | hookup(q, x, qz, tr->numBranches); |
|---|
| 92 | |
|---|
| 93 | r->next->next->back = r->next->back = (nodeptr) NULL; |
|---|
| 94 | |
|---|
| 95 | return result; |
|---|
| 96 | } |
|---|
| 97 | |
|---|
| 98 | |
|---|
| 99 | /* |
|---|
| 100 | structure to store likelihood and insertion node |
|---|
| 101 | for each window position |
|---|
| 102 | */ |
|---|
| 103 | |
|---|
| 104 | typedef struct |
|---|
| 105 | { |
|---|
| 106 | double lh; |
|---|
| 107 | nodeptr p; |
|---|
| 108 | } positionData; |
|---|
| 109 | |
|---|
| 110 | |
|---|
| 111 | /* |
|---|
| 112 | traverse the tree recursively and insert taxon into each position |
|---|
| 113 | */ |
|---|
| 114 | |
|---|
| 115 | static void traverseBias(nodeptr p, nodeptr q, tree *tr, int *branchCounter, positionData *pd, int windowSize) |
|---|
| 116 | { |
|---|
| 117 | double |
|---|
| 118 | sum = 0.0, |
|---|
| 119 | result = 0.0; |
|---|
| 120 | |
|---|
| 121 | int |
|---|
| 122 | i; |
|---|
| 123 | |
|---|
| 124 | |
|---|
| 125 | /* |
|---|
| 126 | compute the likelihood of inserting the tip attached to |
|---|
| 127 | p between q and q->back |
|---|
| 128 | |
|---|
| 129 | Actually in testInsertThorough() we compute the per site |
|---|
| 130 | log likes which are then stored in an array tr->perSiteLL[i] |
|---|
| 131 | */ |
|---|
| 132 | |
|---|
| 133 | result = testInsertThorough(tr, p, q, TRUE); |
|---|
| 134 | |
|---|
| 135 | |
|---|
| 136 | /* |
|---|
| 137 | stuff below can be removed at some point |
|---|
| 138 | it just makes me feel better |
|---|
| 139 | */ |
|---|
| 140 | |
|---|
| 141 | for(i = 0; i < tr->cdta->endsite; i++) |
|---|
| 142 | sum += tr->perSiteLL[i]; |
|---|
| 143 | |
|---|
| 144 | assert(ABS(sum - result) < 0.001); |
|---|
| 145 | |
|---|
| 146 | /*************************************/ |
|---|
| 147 | |
|---|
| 148 | /* |
|---|
| 149 | for each window position just compute the likelihood over |
|---|
| 150 | the window. |
|---|
| 151 | |
|---|
| 152 | If its is better than the current best one, store the likelihood |
|---|
| 153 | and the insertion node in the data structure |
|---|
| 154 | */ |
|---|
| 155 | |
|---|
| 156 | for(i = 0; i < tr->cdta->endsite - windowSize; i++) |
|---|
| 157 | { |
|---|
| 158 | int |
|---|
| 159 | j; |
|---|
| 160 | |
|---|
| 161 | for(j = i, sum = 0.0; j < i + windowSize; j++) |
|---|
| 162 | sum += tr->perSiteLL[j]; |
|---|
| 163 | |
|---|
| 164 | if(sum > pd[i].lh) |
|---|
| 165 | { |
|---|
| 166 | pd[i].lh = sum; |
|---|
| 167 | pd[i].p = q; |
|---|
| 168 | } |
|---|
| 169 | } |
|---|
| 170 | |
|---|
| 171 | *branchCounter = *branchCounter + 1; |
|---|
| 172 | |
|---|
| 173 | |
|---|
| 174 | /* and here comes the recursion */ |
|---|
| 175 | |
|---|
| 176 | if(!isTip(q->number, tr->rdta->numsp)) |
|---|
| 177 | { |
|---|
| 178 | traverseBias(p, q->next->back, tr, branchCounter, pd, windowSize); |
|---|
| 179 | traverseBias(p, q->next->next->back, tr, branchCounter, pd, windowSize); |
|---|
| 180 | } |
|---|
| 181 | } |
|---|
| 182 | |
|---|
| 183 | |
|---|
| 184 | /* |
|---|
| 185 | functions to compute the node distances between inferred and true |
|---|
| 186 | placement positions. I think that they are correct. |
|---|
| 187 | */ |
|---|
| 188 | |
|---|
| 189 | static int findRec(nodeptr ref, nodeptr best, int mxtips, int value) |
|---|
| 190 | { |
|---|
| 191 | if(isTip(ref->number, mxtips)) |
|---|
| 192 | { |
|---|
| 193 | if(ref == best || ref->back == best) |
|---|
| 194 | return value; |
|---|
| 195 | else |
|---|
| 196 | return 0; |
|---|
| 197 | } |
|---|
| 198 | else |
|---|
| 199 | { |
|---|
| 200 | int |
|---|
| 201 | d1, |
|---|
| 202 | d2; |
|---|
| 203 | |
|---|
| 204 | if(ref == best || ref->back == best) |
|---|
| 205 | return value; |
|---|
| 206 | |
|---|
| 207 | d1 = findRec(ref->next->back, best, mxtips, value + 1); |
|---|
| 208 | d2 = findRec(ref->next->next->back, best, mxtips, value + 1); |
|---|
| 209 | |
|---|
| 210 | assert((d1 > 0 && d2 == 0) || (d2 > 0 && d1 == 0) || (d1 == 0 && d2 == 0)); |
|---|
| 211 | |
|---|
| 212 | return (d1 + d2); |
|---|
| 213 | } |
|---|
| 214 | } |
|---|
| 215 | |
|---|
| 216 | static double getNodeDistance(nodeptr ref, nodeptr best, int mxtips) |
|---|
| 217 | { |
|---|
| 218 | int |
|---|
| 219 | d1 = findRec(ref, best, mxtips, 0), |
|---|
| 220 | d2 = findRec(ref->back, best, mxtips, 0); |
|---|
| 221 | |
|---|
| 222 | assert((d1 > 0 && d2 == 0) || (d2 > 0 && d1 == 0) || (d1 == 0 && d2 == 0)); |
|---|
| 223 | |
|---|
| 224 | return ((double)(d1 + d2)); |
|---|
| 225 | } |
|---|
| 226 | |
|---|
| 227 | void computePlacementBias(tree *tr, analdef *adef) |
|---|
| 228 | { |
|---|
| 229 | int |
|---|
| 230 | windowSize = adef->slidingWindowSize, |
|---|
| 231 | k, |
|---|
| 232 | i, |
|---|
| 233 | tips, |
|---|
| 234 | numTraversalBranches = (2 * (tr->mxtips - 1)) - 3; /* compute number of branches into which we need to insert once we have removed a taxon */ |
|---|
| 235 | |
|---|
| 236 | char |
|---|
| 237 | fileName[1024]; |
|---|
| 238 | |
|---|
| 239 | FILE |
|---|
| 240 | *outFile; |
|---|
| 241 | |
|---|
| 242 | /* data for each sliding window starting position */ |
|---|
| 243 | |
|---|
| 244 | positionData |
|---|
| 245 | *pd = (positionData *)rax_malloc(sizeof(positionData) * (tr->cdta->endsite - windowSize)); |
|---|
| 246 | |
|---|
| 247 | double |
|---|
| 248 | *nodeDistances = (double*)rax_calloc(tr->cdta->endsite - windowSize, sizeof(double)), /* array to store node distnces ND for every sliding window position */ |
|---|
| 249 | *distances = (double*)rax_calloc(tr->cdta->endsite, sizeof(double)); /* array to store avg distances for every site */ |
|---|
| 250 | |
|---|
| 251 | strcpy(fileName, workdir); |
|---|
| 252 | strcat(fileName, "RAxML_SiteSpecificPlacementBias."); |
|---|
| 253 | strcat(fileName, run_id); |
|---|
| 254 | |
|---|
| 255 | outFile = myfopen(fileName, "w"); |
|---|
| 256 | |
|---|
| 257 | printBothOpen("Likelihood of comprehensive tree %f\n\n", tr->likelihood); |
|---|
| 258 | |
|---|
| 259 | if(windowSize > tr->cdta->endsite) |
|---|
| 260 | { |
|---|
| 261 | printBothOpen("The size of your sliding window is %d while the number of sites in the alignment is %d\n\n", windowSize, tr->cdta->endsite); |
|---|
| 262 | exit(-1); |
|---|
| 263 | } |
|---|
| 264 | |
|---|
| 265 | if(windowSize >= (int)(0.9 * tr->cdta->endsite)) |
|---|
| 266 | printBothOpen("WARNING: your sliding window of size %d is only slightly smaller than you alignment that has %d sites\n\n", windowSize, tr->cdta->endsite); |
|---|
| 267 | |
|---|
| 268 | printBothOpen("Sliding window size: %d\n\n", windowSize); |
|---|
| 269 | |
|---|
| 270 | /* prune and re-insert on tip at a time into all branches of the remaining tree */ |
|---|
| 271 | |
|---|
| 272 | for(tips = 1; tips <= tr->mxtips; tips++) |
|---|
| 273 | { |
|---|
| 274 | nodeptr |
|---|
| 275 | myStart, |
|---|
| 276 | p = tr->nodep[tips]->back, /* this is the node at which we are prunung */ |
|---|
| 277 | p1 = p->next->back, |
|---|
| 278 | p2 = p->next->next->back; |
|---|
| 279 | |
|---|
| 280 | double |
|---|
| 281 | pz[NUM_BRANCHES], |
|---|
| 282 | p1z[NUM_BRANCHES], |
|---|
| 283 | p2z[NUM_BRANCHES]; |
|---|
| 284 | |
|---|
| 285 | int |
|---|
| 286 | branchCounter = 0; |
|---|
| 287 | |
|---|
| 288 | /* reset array values for this tip */ |
|---|
| 289 | |
|---|
| 290 | for(i = 0; i < tr->cdta->endsite; i++) |
|---|
| 291 | { |
|---|
| 292 | pd[i].lh = unlikely; |
|---|
| 293 | pd[i].p = (nodeptr)NULL; |
|---|
| 294 | } |
|---|
| 295 | |
|---|
| 296 | /* store the three branch lengths adjacent to the position at which we prune */ |
|---|
| 297 | |
|---|
| 298 | for(i = 0; i < tr->numBranches; i++) |
|---|
| 299 | { |
|---|
| 300 | p1z[i] = p1->z[i]; |
|---|
| 301 | p2z[i] = p2->z[i]; |
|---|
| 302 | pz[i] = p->z[i]; |
|---|
| 303 | } |
|---|
| 304 | |
|---|
| 305 | /* prune the taxon, optimizing the branch between p1 and p2 */ |
|---|
| 306 | |
|---|
| 307 | removeNodeBIG(tr, p, tr->numBranches); |
|---|
| 308 | |
|---|
| 309 | printBothOpen("Pruning taxon Number %d [%s]\n", tips, tr->nameList[tips]); |
|---|
| 310 | |
|---|
| 311 | /* find any tip to start traversing the tree */ |
|---|
| 312 | |
|---|
| 313 | myStart = findAnyTip(p1, tr->mxtips); |
|---|
| 314 | |
|---|
| 315 | /* insert taxon, compute likelihood and remove taxon again from all branches */ |
|---|
| 316 | |
|---|
| 317 | traverseBias(p, myStart->back, tr, &branchCounter, pd, windowSize); |
|---|
| 318 | |
|---|
| 319 | assert(branchCounter == numTraversalBranches); |
|---|
| 320 | |
|---|
| 321 | /* for every sliding window position calc ND to the true/correct position at p */ |
|---|
| 322 | |
|---|
| 323 | for(i = 0; i < tr->cdta->endsite - windowSize; i++) |
|---|
| 324 | nodeDistances[i] = getNodeDistance(p1, pd[i].p, tr->mxtips); |
|---|
| 325 | |
|---|
| 326 | /* now analyze */ |
|---|
| 327 | |
|---|
| 328 | for(i = 0; i < tr->cdta->endsite; i++) |
|---|
| 329 | { |
|---|
| 330 | double |
|---|
| 331 | d = 0.0; |
|---|
| 332 | |
|---|
| 333 | int |
|---|
| 334 | s = 0; |
|---|
| 335 | |
|---|
| 336 | /* |
|---|
| 337 | check site position, i.e., doe we have windowSize data points available |
|---|
| 338 | or fewer because we are at the start or the end of the alignment |
|---|
| 339 | */ |
|---|
| 340 | |
|---|
| 341 | /* |
|---|
| 342 | for each site just accumulate the node distances we have for all |
|---|
| 343 | sliding windows that passed over this site |
|---|
| 344 | */ |
|---|
| 345 | |
|---|
| 346 | if(i < windowSize) |
|---|
| 347 | { |
|---|
| 348 | for(k = 0; k <= i; k++, s++) |
|---|
| 349 | d += nodeDistances[k]; |
|---|
| 350 | } |
|---|
| 351 | else |
|---|
| 352 | { |
|---|
| 353 | if(i < tr->cdta->endsite - windowSize) |
|---|
| 354 | { |
|---|
| 355 | for(k = i - windowSize + 1; k <= i; k++, s++) |
|---|
| 356 | d += nodeDistances[k]; |
|---|
| 357 | } |
|---|
| 358 | else |
|---|
| 359 | { |
|---|
| 360 | for(k = i - windowSize; k < (tr->cdta->endsite - windowSize); k++, s++) |
|---|
| 361 | d += nodeDistances[k]; |
|---|
| 362 | } |
|---|
| 363 | } |
|---|
| 364 | |
|---|
| 365 | |
|---|
| 366 | /* |
|---|
| 367 | now just divide the accumultaed ND distance by |
|---|
| 368 | the number of distances we have for this position and then add it to the acc |
|---|
| 369 | distances over all taxa. |
|---|
| 370 | I just realized that the version on which I did the tests |
|---|
| 371 | I sent to Simon I used |
|---|
| 372 | |
|---|
| 373 | distances[i] = d / ((double)s); |
|---|
| 374 | |
|---|
| 375 | instead of |
|---|
| 376 | |
|---|
| 377 | distances[i] += d / ((double)s); |
|---|
| 378 | |
|---|
| 379 | gamo tin poutana mou |
|---|
| 380 | */ |
|---|
| 381 | |
|---|
| 382 | distances[i] += (d / ((double)s)); |
|---|
| 383 | } |
|---|
| 384 | |
|---|
| 385 | |
|---|
| 386 | |
|---|
| 387 | /* |
|---|
| 388 | re-connect taxon to its original position |
|---|
| 389 | */ |
|---|
| 390 | |
|---|
| 391 | hookup(p->next, p1, p1z, tr->numBranches); |
|---|
| 392 | hookup(p->next->next, p2, p2z, tr->numBranches); |
|---|
| 393 | hookup(p, p->back, pz, tr->numBranches); |
|---|
| 394 | |
|---|
| 395 | /* |
|---|
| 396 | fix likelihood vectors |
|---|
| 397 | */ |
|---|
| 398 | |
|---|
| 399 | newviewGeneric(tr, p); |
|---|
| 400 | } |
|---|
| 401 | |
|---|
| 402 | /* |
|---|
| 403 | now just compute the average ND over all taxa |
|---|
| 404 | */ |
|---|
| 405 | |
|---|
| 406 | |
|---|
| 407 | for(i = 0; i < tr->cdta->endsite; i++) |
|---|
| 408 | { |
|---|
| 409 | double |
|---|
| 410 | avg = distances[i] / ((double)tr->mxtips); |
|---|
| 411 | |
|---|
| 412 | fprintf(outFile, "%d %f\n", i, avg); |
|---|
| 413 | } |
|---|
| 414 | |
|---|
| 415 | printBothOpen("\nTime for EPA-based site-specific placement bias calculation: %f\n", gettime() - masterTime); |
|---|
| 416 | printBothOpen("Site-specific placement bias statistics written to file %s\n", fileName); |
|---|
| 417 | |
|---|
| 418 | fclose(outFile); |
|---|
| 419 | |
|---|
| 420 | exit(0); |
|---|
| 421 | } |
|---|