Examples with EMCreationParameters org.baderlab.csplugins.enrichmentmap.model.EMCreationParameters used on opensource projects

Example 1 with EMCreationParameters

use of org.baderlab.csplugins.enrichmentmap.model.EMCreationParameters in project EnrichmentMapApp by BaderLab.

the class EMBuildCommandTask method buildEnrichmentMap.

/**
	 * buildEnrichmentMap - parses all GSEA input files and creates an enrichment map
	 */
public void buildEnrichmentMap() {
    // Note we must continue to use the old constants from EnrichmentMapParameters for backwards compatibility
    Method method = EnrichmentMapParameters.stringToMethod(analysisType.getSelectedValue());
    SimilarityMetric metric = EnrichmentMapParameters.stringToSimilarityMetric(coeffecients.getSelectedValue());
    //Set Dataset1 Files
    DataSetFiles dataset1files = new DataSetFiles();
    if (gmtFile != null)
        dataset1files.setGMTFileName(gmtFile.getAbsolutePath());
    if (expressionDataset1 != null)
        dataset1files.setExpressionFileName(expressionDataset1.getAbsolutePath());
    if (enrichmentsDataset1 != null)
        dataset1files.setEnrichmentFileName1(enrichmentsDataset1.getAbsolutePath());
    if (enrichments2Dataset1 != null)
        dataset1files.setEnrichmentFileName2(enrichments2Dataset1.getAbsolutePath());
    if (ranksDataset1 != null)
        dataset1files.setRankedFile(ranksDataset1.getAbsolutePath());
    if (classDataset1 != null)
        dataset1files.setClassFile(classDataset1.getAbsolutePath());
    if (phenotype1Dataset1 != null)
        dataset1files.setPhenotype1(phenotype1Dataset1);
    if (phenotype2Dataset1 != null)
        dataset1files.setPhenotype2(phenotype2Dataset1);
    //Set Dataset2 Files
    DataSetFiles dataset2files = new DataSetFiles();
    if (expressionDataset2 != null)
        dataset2files.setExpressionFileName(expressionDataset2.getAbsolutePath());
    if (enrichmentsDataset2 != null)
        dataset2files.setEnrichmentFileName1(enrichmentsDataset2.getAbsolutePath());
    if (enrichments2Dataset2 != null)
        dataset2files.setEnrichmentFileName2(enrichments2Dataset2.getAbsolutePath());
    if (ranksDataset2 != null)
        dataset2files.setRankedFile(ranksDataset2.getAbsolutePath());
    if (classDataset2 != null)
        dataset2files.setClassFile(classDataset2.getAbsolutePath());
    if (phenotype1Dataset2 != null)
        dataset2files.setPhenotype1(phenotype1Dataset2);
    if (phenotype2Dataset2 != null)
        dataset2files.setPhenotype2(phenotype2Dataset2);
    List<DataSetParameters> dataSets = new ArrayList<>(2);
    dataSets.add(new DataSetParameters(LegacySupport.DATASET1, method, dataset1files));
    if (!dataset2files.isEmpty()) {
        dataSets.add(new DataSetParameters(LegacySupport.DATASET2, method, dataset2files));
    }
    String prefix = legacySupport.getNextAttributePrefix();
    EMCreationParameters creationParams = new EMCreationParameters(prefix, pvalue, qvalue, NESFilter.ALL, Optional.empty(), metric, similaritycutoff, propertyManager.getDefaultCombinedConstant());
    if (distinctEdges != null)
        creationParams.setCreateDistinctEdges(distinctEdges);
    else if (!dataset2files.isEmpty())
        creationParams.setCreateDistinctEdges(true);
    CreateEnrichmentMapTaskFactory taskFactory = taskFactoryFactory.create(creationParams, dataSets);
    insertTasksAfterCurrentTask(taskFactory.createTaskIterator());
}

Example 2 with EMCreationParameters

use of org.baderlab.csplugins.enrichmentmap.model.EMCreationParameters in project EnrichmentMapApp by BaderLab.

the class ParseGREATEnrichmentResults method parseLines.

@Override
public void parseLines(List<String> lines, EMDataSet dataset, TaskMonitor taskMonitor) {
    if (taskMonitor == null)
        taskMonitor = new NullTaskMonitor();
    taskMonitor.setTitle("Parsing Enrichment Result file");
    boolean hasBackground = false;
    EMCreationParameters params = dataset.getMap().getParams();
    //Get the type of filter user specified on the GREAT results
    //If it is hyper use column 14 Hypergeometric p-value and 16 FDR for hyper
    //If it is binom use column 5 bionomial p-value and 7 FDR for binom
    //If they specify both use the highest p-value and q-value from the above columns
    GreatFilter filterType = dataset.getMap().getParams().getGreatFilter();
    Map<String, GeneSet> genesets = dataset.getSetOfGeneSets().getGeneSets();
    EnrichmentMap map = dataset.getMap();
    Map<String, EnrichmentResult> results = dataset.getEnrichments().getEnrichments();
    int currentProgress = 0;
    int maxValue = lines.size();
    taskMonitor.setStatusMessage("Parsing Great Results file - " + maxValue + " rows");
    //for great files there is an FDR
    dataset.getMap().getParams().setFDR(true);
    //skip the first l9 which just has the field names (start i=1)
    //check to see how many columns the data has
    //go through each line until we find the header line
    int k = 0;
    String line = lines.get(k);
    String[] tokens = line.split("\t");
    for (; k < lines.size(); k++) {
        line = lines.get(k);
        tokens = line.split("\t");
        int length = tokens.length;
        if ((length == 24) && tokens[3].equalsIgnoreCase("BinomRank")) {
            break;
        } else //There is not binom rank and no binomial data.
        if ((length == 20) && tokens[3].equalsIgnoreCase("Rank")) {
            hasBackground = true;
            break;
        }
    }
    //go through the rest of the lines
    for (int i = k + 1; i < lines.size(); i++) {
        line = lines.get(i);
        tokens = line.split("\t");
        //there are extra lines at the end of the file that should be ignored.
        if (!hasBackground && tokens.length != 24)
            continue;
        if (hasBackground && tokens.length != 20)
            continue;
        double pvalue = 1.0;
        double FDRqvalue = 1.0;
        GenericResult result;
        int gs_size = 0;
        double NES = 1.0;
        //details of export file
        //http://bejerano.stanford.edu/help/display/GREAT/Export
        //The second column of the file is the name of the geneset
        final String name = tokens[1].trim() + "-" + tokens[2].trim();
        //the first column of the file is the description
        final String description = tokens[2].trim();
        //when there are two different species it is possible that the gene set could
        //already exist in the set of genesets.  if it does exist then add the genes
        //in this set to the geneset
        ImmutableSet.Builder<Integer> builder = ImmutableSet.builder();
        if (genesets.containsKey(name))
            builder = builder.addAll(genesets.get(name).getGenes());
        String[] gene_tokens;
        if (!hasBackground)
            gene_tokens = tokens[23].split(",");
        else
            gene_tokens = tokens[18].split(",");
        //All subsequent fields in the list are the geneset associated with this geneset.
        for (int j = 0; j < gene_tokens.length; j++) {
            String gene = gene_tokens[j].toUpperCase();
            //if it is already in the hash then get its associated key and put it into the set of genes
            if (map.containsGene(gene)) {
                builder.add(map.getHashFromGene(gene));
            } else if (!gene.isEmpty()) {
                Integer hash = map.addGene(gene).get();
                builder.add(hash);
            }
        }
        //finished parsing that geneset
        //add the current geneset to the hashmap of genesets
        GeneSet gs = new GeneSet(name, description, builder.build());
        genesets.put(name, gs);
        //There are two tests run by GREAT, the binomial on regions and the hypergeometric based on genes
        //The first pass of results shows only those that are significant both
        //The user can then choose to use either or both together
        //
        //If it is hyper use column 14 Hypergeometric p-value and 16 FDR for hyper
        //If it is binom use column 5 bionomial p-value and 7 FDR for binom
        //If they specify both use the highest p-value and q-value from the above columns
        double hyper_pvalue = 1;
        double hyper_fdr = 1;
        double binom_pvalue = 1;
        double binom_fdr = 1;
        if (!hasBackground) {
            if (!tokens[4].equalsIgnoreCase(""))
                binom_pvalue = Double.parseDouble(tokens[4]);
            if (!tokens[6].equalsIgnoreCase(""))
                binom_fdr = Double.parseDouble(tokens[6]);
            if (!tokens[13].equalsIgnoreCase(""))
                hyper_pvalue = Double.parseDouble(tokens[13]);
            if (!tokens[15].equalsIgnoreCase(""))
                hyper_fdr = Double.parseDouble(tokens[15]);
        } else {
            if (!tokens[4].equalsIgnoreCase(""))
                hyper_pvalue = Double.parseDouble(tokens[4]);
            if (!tokens[6].equalsIgnoreCase(""))
                hyper_fdr = Double.parseDouble(tokens[6]);
        }
        if (filterType == GreatFilter.HYPER) {
            pvalue = hyper_pvalue;
            FDRqvalue = hyper_fdr;
        } else if (filterType == GreatFilter.BINOM) {
            pvalue = binom_pvalue;
            FDRqvalue = binom_fdr;
        } else if (filterType == GreatFilter.BOTH) {
            pvalue = Math.max(hyper_pvalue, binom_pvalue);
            FDRqvalue = Math.max(hyper_fdr, binom_fdr);
        } else if (filterType == GreatFilter.EITHER) {
            pvalue = Math.min(hyper_pvalue, binom_pvalue);
            FDRqvalue = Math.min(hyper_fdr, binom_fdr);
        } else {
            System.out.println("Invalid attribute setting for GREAT p-value specification");
        }
        //Keep track of minimum p-value to better calculate jslider
        if (pvalue < params.getPvalueMin())
            params.setPvalueMin(pvalue);
        if (FDRqvalue < params.getQvalueMin())
            params.setQvalueMin(FDRqvalue);
        //If this is a background set then it is in the 16th column
        if ((!hasBackground) && (!tokens[19].equalsIgnoreCase("")))
            gs_size = Integer.parseInt(tokens[19]);
        else if ((hasBackground) && (!tokens[15].equalsIgnoreCase("")))
            gs_size = Integer.parseInt(tokens[15]);
        result = new GenericResult(name, description, pvalue, gs_size, FDRqvalue);
        // Calculate Percentage.  This must be a value between 0..100.
        int percentComplete = (int) (((double) currentProgress / maxValue) * 100);
        taskMonitor.setProgress(percentComplete);
        currentProgress++;
        //check to see if the gene set has already been entered in the results
        //it is possible that one geneset will be in both phenotypes.
        //if it is already exists then we want to make sure the one retained is the result with the
        //lower p-value.
        //ticket #149
        GenericResult temp = (GenericResult) results.get(name);
        if (temp == null)
            results.put(name, result);
        else {
            if (result.getPvalue() < temp.getPvalue())
                results.put(name, result);
        }
    }
}

Example 3 with EMCreationParameters

use of org.baderlab.csplugins.enrichmentmap.model.EMCreationParameters in project EnrichmentMapApp by BaderLab.

the class LoadBingoResultsTest method testLoad2BingoResult_withoutexpression.

@Test
public void testLoad2BingoResult_withoutexpression() throws Exception {
    //for a dataset we require genesets, an expression file (optional), enrichment results
    String testBingoResultsFileName = "src/test/resources/org/baderlab/csplugins/enrichmentmap/task/bingo_output/12Hr_topgenes.bgo";
    DataSetFiles files = new DataSetFiles();
    files.setEnrichmentFileName1(testBingoResultsFileName);
    //for a dataset we require genesets, an expression file (optional), enrichment results
    String testBingoResultsFileName2 = "src/test/resources/org/baderlab/csplugins/enrichmentmap/task/bingo_output/24Hr_topgenes.bgo";
    DataSetFiles files2 = new DataSetFiles();
    files2.setEnrichmentFileName1(testBingoResultsFileName2);
    //set the method to Bingo
    double pvalue = 0.00005;
    // 5.0 X 10-8
    double qvaule = 0.00000005;
    double similarityCutoff = 0.25;
    EMCreationParameters params = new EMCreationParameters("EM1_", pvalue, qvaule, NESFilter.ALL, Optional.empty(), SimilarityMetric.JACCARD, similarityCutoff, 0.5);
    //create an new enrichment Map
    EnrichmentMap em = new EnrichmentMap(params, serviceRegistrar);
    EMDataSet dataset = em.createDataSet(LegacySupport.DATASET1, Method.Specialized, files);
    ParseBingoEnrichmentResults enrichmentResultsFilesTask = new ParseBingoEnrichmentResults(dataset);
    enrichmentResultsFilesTask.run(taskMonitor);
    //Load second dataset
    //create a dataset
    EMDataSet dataset2 = em.createDataSet(LegacySupport.DATASET2, Method.Specialized, files2);
    //create a DatasetTask
    ParseBingoEnrichmentResults enrichmentResultsFiles2Task = new ParseBingoEnrichmentResults(dataset2);
    enrichmentResultsFiles2Task.run(taskMonitor);
    CreateDummyExpressionTask dummyExpressionTask = new CreateDummyExpressionTask(dataset);
    dummyExpressionTask.run(taskMonitor);
    CreateDummyExpressionTask dummyExpressionTask2 = new CreateDummyExpressionTask(dataset2);
    dummyExpressionTask2.run(taskMonitor);
    //check to see if the two datasets are distinct
    if (!((dataset.getDataSetGenes().containsAll(dataset2.getDataSetGenes())) && (dataset2.getDataSetGenes().containsAll(dataset.getDataSetGenes()))))
        em.setDistinctExpressionSets(true);
    em.filterGenesets();
    InitializeGenesetsOfInterestTask genesets_init = new InitializeGenesetsOfInterestTask(em);
    genesets_init.run(taskMonitor);
    //		ComputeSimilarityTask similarities = new ComputeSimilarityTask(em);
    //		similarities.run(taskMonitor);
    dataset = em.getDataSet(LegacySupport.DATASET1);
    //get the stats for the first dataset		
    //check to see if the dataset loaded - there should be 74 genesets
    assertEquals(74, dataset.getSetOfGeneSets().getGeneSets().size());
    //there should also be 74 enrichments (the genesets are built from the bgo file)
    assertEquals(74, dataset.getEnrichments().getEnrichments().size());
    //there should be 11 genesets in the enrichments of interest
    assertEquals(5, dataset.getGeneSetsOfInterest().getGeneSets().size());
    //there should be 43 genes in the geneset "nucleolus"
    assertEquals(43, dataset.getSetOfGeneSets().getGeneSets().get("NUCLEOLUS").getGenes().size());
    //make sure the dummy expression has values for all the genes
    assertEquals(446, dataset.getExpressionSets().getNumGenes());
    assertEquals(446, dataset.getDataSetGenes().size());
    dataset2 = em.getDataSet(LegacySupport.DATASET2);
    //check the stats for dataset2
    //check to see if the dataset loaded - there should be 74 genesets
    assertEquals(87, dataset2.getSetOfGeneSets().getGeneSets().size());
    //there should also be 74 enrichments (the genesets are built from the bgo file)
    assertEquals(87, dataset2.getEnrichments().getEnrichments().size());
    //there should be 11 genesets in the enrichments of interest
    assertEquals(2, dataset2.getGeneSetsOfInterest().getGeneSets().size());
    //there should be 43 genes in the geneset "nucleolus"
    assertEquals(318, dataset2.getSetOfGeneSets().getGeneSets().get("INTRACELLULAR").getGenes().size());
    //make sure the dummy expression has values for all the genes
    assertEquals(398, dataset2.getExpressionSets().getNumGenes());
    assertEquals(398, dataset2.getDataSetGenes().size());
    //there should be 20 edges (2 edges for every node because of the distinct expresison sets)
    //assertEquals(24,em.getGenesetSimilarity().size());
    //there should be a total of 366 genes
    assertEquals(704, em.getNumberOfGenes());
}

Example 4 with EMCreationParameters

use of org.baderlab.csplugins.enrichmentmap.model.EMCreationParameters in project EnrichmentMapApp by BaderLab.

the class LoadEdbDatasetTest method testEdbLoad.

@Test
public void testEdbLoad() throws Exception {
    //for a dataset we require genesets, an expression file (optional), enrichment results
    String testEdbResultsFileName = "src/test/resources/org/baderlab/csplugins/enrichmentmap/task/LoadDataset/GSEA_example_results/edb/results.edb";
    String testgmtFileName = "src/test/resources/org/baderlab/csplugins/enrichmentmap/task/LoadDataset/GSEA_example_results/edb/gene_sets.gmt";
    String testrnkFileName = "src/test/resources/org/baderlab/csplugins/enrichmentmap/task/LoadDataset/GSEA_example_results/edb/Expressionfile.rnk";
    DataSetFiles files = new DataSetFiles();
    files.setEnrichmentFileName1(testEdbResultsFileName);
    files.setGMTFileName(testgmtFileName);
    files.setRankedFile(testrnkFileName);
    //set the method to gsea
    double similarityCutoff = 0.5;
    double pvalue = 1.0;
    double qvalue = 1.0;
    EMCreationParameters params = new EMCreationParameters("EM1_", pvalue, qvalue, NESFilter.ALL, Optional.empty(), SimilarityMetric.JACCARD, similarityCutoff, 0.5);
    //create an new enrichment Map
    EnrichmentMap em = new EnrichmentMap(params, serviceRegistrar);
    //Load data set
    //create a dataset
    EMDataSet dataset = em.createDataSet(LegacySupport.DATASET1, Method.GSEA, files);
    //create a DatasetTask
    //create a DatasetTask
    //load Data
    GMTFileReaderTask task = new GMTFileReaderTask(dataset);
    task.run(taskMonitor);
    ParseEDBEnrichmentResults enrichmentResultsFilesTask = new ParseEDBEnrichmentResults(dataset);
    enrichmentResultsFilesTask.run(taskMonitor);
    //create dummy expression
    CreateDummyExpressionTask dummyExpressionTask = new CreateDummyExpressionTask(dataset);
    dummyExpressionTask.run(taskMonitor);
    em.filterGenesets();
    InitializeGenesetsOfInterestTask genesets_init = new InitializeGenesetsOfInterestTask(em);
    genesets_init.run(taskMonitor);
    //check to see if the dataset loaded
    //although the original analysis had 193 genesets because this is loaded from
    //edb version it only stores the genesets that overlapped with the dataset analyzed.
    assertEquals(14, dataset.getSetOfGeneSets().getGeneSets().size());
    assertEquals(14, dataset.getEnrichments().getEnrichments().size());
    assertEquals(41, dataset.getDataSetGenes().size());
    assertEquals(41, dataset.getExpressionSets().getNumGenes());
}

Example 5 with EMCreationParameters

use of org.baderlab.csplugins.enrichmentmap.model.EMCreationParameters in project EnrichmentMapApp by BaderLab.

the class LegacySessionLoadTest method test_1_LoadedLegacyData.

@Test
@SessionFile("em_session_2.2.cys")
public void test_1_LoadedLegacyData() throws Exception {
    EnrichmentMap map = getEnrichmentMap();
    assertEquals("EM1_Enrichment Map", map.getName());
    CyNetwork network = networkManager.getNetwork(map.getNetworkID());
    assertNotNull(network);
    assertEquals(1, map.getDataSetCount());
    assertEquals(14067, map.getNumberOfGenes());
    assertEquals(14067, map.getAllGenes().size());
    // Number of edges: 3339 - that's how many geneset similarity objects there should be!!!
    CyTable edgeTable = network.getDefaultEdgeTable();
    assertEquals(3339, edgeTable.getRowCount());
    EMCreationParameters params = map.getParams();
    String prefix = params.getAttributePrefix();
    assertEquals("EM1_", prefix);
    assertEquals(0.5, params.getCombinedConstant(), 0.0);
    assertFalse(params.isEMgmt());
    assertEquals("Geneset_Overlap", params.getEnrichmentEdgeType());
    assertTrue(params.isFDR());
    assertEquals(GreatFilter.HYPER, params.getGreatFilter());
    assertEquals(0.005, params.getPvalue(), 0.0);
    assertEquals(1.0, params.getPvalueMin(), 0.0);
    assertEquals(0.1, params.getQvalue(), 0.0);
    assertEquals(1.0, params.getQvalueMin(), 0.0);
    assertEquals(0.5, params.getSimilarityCutoff(), 0.0);
    assertEquals(SimilarityMetric.OVERLAP, params.getSimilarityMetric());
    //		assertFalse(params.isDistinctExpressionSets());
    String geneset1 = "RESOLUTION OF SISTER CHROMATID COHESION%REACTOME%REACT_150425.2";
    String geneset2 = "CHROMOSOME, CENTROMERIC REGION%GO%GO:0000775";
    Collection<CyRow> rows = edgeTable.getMatchingRows(CyNetwork.NAME, geneset1 + " (Geneset_Overlap) " + geneset2);
    assertEquals(1, rows.size());
    CyRow row = rows.iterator().next();
    assertEquals("Geneset_Overlap", row.get(CyEdge.INTERACTION, String.class));
    assertEquals(0.6097560975609756, EMStyleBuilder.Columns.EDGE_SIMILARITY_COEFF.get(row, prefix), 0.0);
    EMDataSet dataset = map.getDataSet("Dataset 1");
    assertNotNull(dataset);
    assertSame(map, dataset.getMap());
    assertEquals(Method.GSEA, dataset.getMethod());
    assertEquals(12653, dataset.getDataSetGenes().size());
    assertEquals(389, dataset.getGeneSetsOfInterest().getGeneSets().size());
    //		assertEquals(17259, dataset.getSetofgenesets().getGenesets().size()); // MKTODO why? what is this used for
    assertEndsWith(dataset.getSetOfGeneSets().getFilename(), "Human_GO_AllPathways_no_GO_iea_April_15_2013_symbol.gmt");
    for (long suid : dataset.getNodeSuids()) {
        assertNotNull(network.getNode(suid));
    }
    GeneSet geneset = dataset.getGeneSetsOfInterest().getGeneSets().get("NCRNA PROCESSING%GO%GO:0034470");
    assertEquals(88, geneset.getGenes().size());
    assertEquals("NCRNA PROCESSING%GO%GO:0034470", geneset.getName());
    assertEquals("ncRNA processing", geneset.getDescription());
    assertEquals(Optional.of("GO"), geneset.getSource());
    SetOfEnrichmentResults enrichments = dataset.getEnrichments();
    assertEquals(4756, enrichments.getEnrichments().size());
    assertEndsWith(enrichments.getFilename1(), "gsea_report_for_ES12_1473194913081.xls");
    assertEndsWith(enrichments.getFilename2(), "gsea_report_for_NT12_1473194913081.xls");
    assertEquals("ES12", enrichments.getPhenotype1());
    assertEquals("NT12", enrichments.getPhenotype2());
    EnrichmentResult result = enrichments.getEnrichments().get("RIBONUCLEOSIDE TRIPHOSPHATE BIOSYNTHETIC PROCESS%GO%GO:0009201");
    assertTrue(result instanceof GSEAResult);
    GSEAResult gseaResult = (GSEAResult) result;
    assertEquals("RIBONUCLEOSIDE TRIPHOSPHATE BIOSYNTHETIC PROCESS%GO%GO:0009201", gseaResult.getName());
    assertEquals(0.42844063, gseaResult.getES(), 0.0);
    assertEquals(0.45225498, gseaResult.getFdrqvalue(), 0.0);
    assertEquals(1.0, gseaResult.getFwerqvalue(), 0.0);
    assertEquals(23, gseaResult.getGsSize());
    assertEquals(1.1938541, gseaResult.getNES(), 0.0);
    assertEquals(0.2457786, gseaResult.getPvalue(), 0.0);
    assertEquals(4689, gseaResult.getRankAtMax());
    assertEquals(Optional.of("GO"), gseaResult.getSource());
    GeneExpressionMatrix expressions = dataset.getExpressionSets();
    assertEquals(20326, expressions.getExpressionUniverse());
    assertEquals(3.686190609, expressions.getClosesttoZero(), 0.0);
    //		assertEndsWith(expressions.getFilename(), "MCF7_ExprMx_v2_names.gct");
    assertEquals(15380.42388, expressions.getMaxExpression(), 0.0);
    assertEquals(3.686190609, expressions.getMinExpression(), 0.0);
    assertEquals(20, expressions.getNumConditions());
    assertEquals(12653, expressions.getExpressionMatrix().size());
    assertEquals(12653, expressions.getExpressionMatrix_rowNormalized().size());
    GeneExpression expression = expressions.getExpressionMatrix().get(0);
    assertEquals("MOCOS", expression.getName());
    assertEquals("MOCOS (molybdenum cofactor sulfurase)", expression.getDescription());
    assertEquals(18, expression.getExpression().length);
    Ranking ranking = expressions.getRanks().get("GSEARanking");
    assertEquals(12653, ranking.getAllRanks().size());
    assertEquals(12653, ranking.getRanking().size());
    Rank rank = ranking.getRanking().get(0);
    assertEquals("MOCOS", rank.getName());
    assertEquals(1238, rank.getRank().intValue());
    assertEquals(0.54488367, rank.getScore(), 0.0);
    DataSetFiles files = dataset.getDataSetFiles();
    assertEndsWith(files.getClassFile(), "ES_NT.cls");
    assertEndsWith(files.getEnrichmentFileName1(), "gsea_report_for_ES12_1473194913081.xls");
    assertEndsWith(files.getEnrichmentFileName2(), "gsea_report_for_NT12_1473194913081.xls");
    //		assertEndsWith(files.getExpressionFileName(), "MCF7_ExprMx_v2_names.gct");
    assertEndsWith(files.getGMTFileName(), "Human_GO_AllPathways_no_GO_iea_April_15_2013_symbol.gmt");
    assertEndsWith(files.getGseaHtmlReportFile(), "estrogen_treatment_12hr_gsea_enrichment_results.Gsea.1473194913081/index.html");
    assertEndsWith(files.getRankedFile(), "ranked_gene_list_ES12_versus_NT12_1473194913081.xls");
    assertEquals("ES12", files.getPhenotype1());
    assertEquals("NT12", files.getPhenotype2());
}