482d460b09a00806e44c9df3005fad97ce173ec1 kent Tue Jan 12 11:13:48 2021 -0800 Fixing an off by one bug Jonathan spotted during code review. diff --git src/utils/clusterMatrixToBarChartBed/clusterMatrixToBarChartBed.c src/utils/clusterMatrixToBarChartBed/clusterMatrixToBarChartBed.c index 20cfd80..c82d45a 100644 --- src/utils/clusterMatrixToBarChartBed/clusterMatrixToBarChartBed.c +++ src/utils/clusterMatrixToBarChartBed/clusterMatrixToBarChartBed.c @@ -1,325 +1,325 @@ /* clusterMatrixToBarChartBed - Compute a barchart bed file from a gene matrix * and a gene bed file and a way to cluster samples. */ #include "common.h" #include "linefile.h" #include "hash.h" #include "options.h" #include "localmem.h" #include "obscure.h" #include "sqlNum.h" boolean clSimple = FALSE; boolean clMedian = FALSE; char *clName2 = NULL; void usage() /* Explain usage and exit. */ { errAbort( "clusterMatrixToBarChartBed - Compute a barchart bed file from a gene matrix\n" "and a gene bed file and a way to cluster samples.\n" "NOTE: consider using matrixClusterColumns and matrixToBarChartBed instead\n" "usage:\n" " clusterMatrixToBarChartBed sampleClusters.tsv geneMatrix.tsv geneset.bed output.bed\n" "where:\n" " sampleClusters.tsv is a two column tab separated file with sampleId and clusterId\n" " geneMatrix.tsv has a row for each gene. The first row uses the same sampleId as above\n" " geneset.bed has the maps the genes in the matrix (from it's first column) to the genome\n" " geneset.bed needs 6 standard bed fields. Unless name2 is set it also needs a name2\n" " field as the last field\n" " output.bed is the resulting bar chart, with one column per cluster\n" "options:\n" " -simple - don't store the position of gene in geneMatrix.tsv file in output\n" " -median - use median (instead of mean)\n" " -name2=twoColFile.tsv - get name2 from file where first col is same ase geneset.bed's name\n" ); } /* Command line validation table. */ static struct optionSpec options[] = { {"simple", OPTION_BOOLEAN}, {"median", OPTION_BOOLEAN}, {"name2", OPTION_STRING}, {NULL, 0}, }; void hashSamplesAndClusters(char *tsvFile, struct hash **retSampleHash, struct hash **retClusterHash) /* Read two column tsv file into a hash keyed by first column */ { struct hash *sampleHash = hashNew(0); struct hash *clusterHash = hashNew(0); char *row[2]; struct lineFile *lf = lineFileOpen(tsvFile, TRUE); while (lineFileNextRowTab(lf, row, ArraySize(row)) ) { /* Find cluster in cluster hash, if it doesn't exist make it. */ char *clusterName = row[1]; struct hashEl *hel = hashLookup(clusterHash, clusterName); if (hel == NULL) hel = hashAddInt(clusterHash, clusterName, 1); else hel->val = ((char *)hel->val)+1; // Increment hash pointer as per hashIncInt char *clusterStableName = hel->name; // This is allocated in clusterHash hashAdd(sampleHash, row[0], clusterStableName); } lineFileClose(&lf); *retSampleHash = sampleHash; *retClusterHash = clusterHash; } void clusterMatrixToBarChartBed(char *sampleClusters, char *matrixTsv, char *geneBed, char *output) /* clusterMatrixToBarChartBed - Compute a barchart bed file from a gene matrix * and a gene bed file and a way to cluster samples. */ { /* Figure out if we need to do medians etc */ boolean doMedian = clMedian; /* Load up the gene set */ verbose(2, "clusterMatrixToBarChartBed(%s,%s,%s,%s)\n", sampleClusters, matrixTsv, geneBed, output); int bedRowSize = 0; struct hash *geneHash = hashTsvBy(geneBed, 3, &bedRowSize); verbose(2, "%d columns about %d genes in %s\n", bedRowSize, geneHash->elCount, geneBed); /* Deal with external gene hash */ struct hash *nameToName2 = NULL; if (clName2 != NULL) { int colCount = 0; nameToName2 = hashTsvBy(clName2, 0, &colCount); if (colCount != 2) errAbort("Expecting %s to be a two column tab separated file", clName2); } /* Keep track of how many fields gene bed has to have and locate name2 */ -int geneBedMinSize = 6; +int geneBedMinSize = 7; int name2Ix = bedRowSize - 1; // Last field if it is in bed if (clName2 != NULL) geneBedMinSize -= 1; if (bedRowSize < geneBedMinSize) { if (clName2 == NULL) errAbort("%s needs to have at least 6 standard BED fields and a name2 field\n", geneBed); else errAbort("%s needs to have at least 6 standard BED fields\n", geneBed); } /* Load up the sample clustering */ struct hash *sampleHash = NULL, *clusterHash = NULL; hashSamplesAndClusters(sampleClusters, &sampleHash, &clusterHash); int clusterCount = clusterHash->elCount; verbose(1, "%d samples and %d clusters in %s\n", sampleHash->elCount, clusterCount, sampleClusters); if (clusterCount <= 1 || clusterCount >= 10000) errAbort("%d is not a good number of clusters", clusterCount); double clusterTotal[clusterCount]; int clusterElements[clusterCount]; /* Alphabetize cluster names */ char *clusterNames[clusterCount]; struct hashEl *hel; struct hashCookie cookie = hashFirst(clusterHash); int clusterIx = 0; while ((hel = hashNext(&cookie)) != NULL) { clusterNames[clusterIx] = hel->name; ++clusterIx; } sortStrings(clusterNames, clusterCount); verbose(2, "%s to %s\n", clusterNames[0], clusterNames[clusterCount-1]); /* Figure out size of each alphabetized cluster in terms of number of samples in cluster * if we are doing median */ int clusterSize[clusterCount]; double *clusterSamples[clusterCount]; if (doMedian) { for (clusterIx = 0; clusterIx < clusterCount; ++clusterIx) { clusterSize[clusterIx] = hashIntVal(clusterHash, clusterNames[clusterIx]); verbose(2, "clusterSize[%d] = %d\n", clusterIx, clusterSize[clusterIx]); } /* Make up array of doubles for each cluster to hold all samples in that clusters */ for (clusterIx = 0; clusterIx < clusterCount; ++clusterIx) { double *samples; AllocArray(samples, clusterSize[clusterIx]); clusterSamples[clusterIx] = samples; } } /* Make hash that goes from cluster name to cluster index */ struct hash *clusterToClusterIdHash = hashNew(0); for (clusterIx = 0; clusterIx<clusterCount; ++clusterIx) { hashAddInt(clusterToClusterIdHash, clusterNames[clusterIx], clusterIx); } /* Open output */ FILE *f = mustOpen(output, "w"); /* Open up matrix file and read first line into sample labeling */ struct lineFile *lf = lineFileOpen(matrixTsv, TRUE); char *line; lineFileNeedNext(lf, &line, NULL); if (line[0] == '#') // Opening sharp on labels is optional, skip it if there line = skipLeadingSpaces(line+1); int colCount = chopByChar(line, '\t', NULL, 0); int colAlloc = colCount + 1; char **sampleNames; AllocArray(sampleNames, colAlloc); chopByChar(line, '\t', sampleNames, colCount); /* Make array that maps row index to clusterID */ int colToCluster[colCount]; int colIx; for (colIx=1; colIx <colCount; colIx = colIx+1) { char *colName = sampleNames[colIx]; char *clusterName = hashFindVal(sampleHash, colName); colToCluster[colIx] = -1; if (clusterName != NULL) { int clusterId = hashIntValDefault(clusterToClusterIdHash, clusterName, -1); colToCluster[colIx] = clusterId; if (clusterId == -1) warn("%s is in expression matrix but not in sample cluster file", clusterName); } } /* Set up row for reading one row of matrix at a time. */ char **matrixRow; AllocArray(matrixRow, colAlloc); int hitCount = 0, missCount = 0; double sumTotal = 0; dotForUserInit(100); for (;;) { /* Fetch next line and remember how long it is. Just skip over lines that are empty or * start with # character. */ int lineLength = 0; char *line; if (!lineFileNext(lf, &line, &lineLength)) break; char *s = skipLeadingSpaces(line); char c = s[0]; if (c == 0 || c == '#') continue; /* Chop it into tabs */ int rowSize = chopByChar(line, '\t', matrixRow, colAlloc); lineFileExpectWords(lf, colCount, rowSize); char *geneName = matrixRow[0]; struct hashEl *onePos = hashLookup(geneHash, geneName); if (onePos == NULL) { verbose(2, "Can't find gene %s in %s", geneName, geneBed); ++missCount; continue; } else { ++hitCount; } /* A gene may map multiple places. This loop takes care of that */ for (; onePos != NULL; onePos = hashLookupNext(onePos)) { char **geneBedVal = onePos->val; // Get our bed as string array out of hash /* Zero out cluster histogram */ int i; for (i=0; i<clusterCount; ++i) { clusterTotal[i] = 0.0; clusterElements[i] = 0; } /* Loop through rest of row filling in histogram */ for (i=1; i<colCount; ++i) { int clusterIx = colToCluster[i]; char *textVal = matrixRow[i]; // special case so common we parse out "0" inline double val = (textVal[0] == '0' && textVal[1] == 0) ? 0.0 : sqlDouble(textVal); sumTotal += val; int valCount = clusterElements[clusterIx]; clusterElements[clusterIx] = valCount+1; if (doMedian) { if (valCount >= clusterSize[clusterIx]) internalErr(); clusterSamples[clusterIx][valCount] = val; } else clusterTotal[clusterIx] += val; } /* Output info - first six from the bed, then name2, then our barchart */ for (i=0; i<6; ++i) fprintf(f, "%s\t", geneBedVal[i]); char *name = geneBedVal[3]; // By bed definition it's fourth field char *name2 = NULL; if (nameToName2 != NULL) { char **namedRow = hashFindVal(nameToName2, name); if (namedRow != NULL) name2 = namedRow[1]; // [0] is name else warn("Can't find %s in %s", name, clName2); } else name2 = geneBedVal[name2Ix]; if (name2 == NULL) name2 = name; fprintf(f, "%s\t", name2); fprintf(f, "%d\t", clusterCount); for (i=0; i<clusterCount; ++i) { if (i != 0) fprintf(f, ","); if (doMedian) fprintf(f, "%g", doubleMedian(clusterElements[i], clusterSamples[i])); else { fprintf(f, "%g", clusterTotal[i]/clusterElements[i]); } } /* Data file offset info */ if (!clSimple) fprintf(f, "\t%lld\t%lld", (long long)lineFileTell(lf), (long long)lineLength); fprintf(f, "\n"); } dotForUser(); } verbose(1, "\n%d genes found, %d (%0.2f%%) missed\n", hitCount, missCount, 100.0*missCount/(hitCount+missCount)); if (!doMedian) { verbose(1, "matrix total %g, %d clusters, %g ave/cluster\n", sumTotal, clusterCount, sumTotal/clusterCount); } carefulClose(&f); } int main(int argc, char *argv[]) /* Process command line. */ { optionInit(&argc, argv, options); if (argc != 5) usage(); clSimple = optionExists("simple"); clMedian = optionExists("median"); clName2 = optionVal("name2", clName2); clusterMatrixToBarChartBed(argv[1], argv[2], argv[3], argv[4]); return 0; }