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ChIP-seq data analysis with a Java program based on genexplain-api

The Java code below implements the tutorial workflow. The described steps are indicated in code comments for reference.

Compiling and executing the tutorial

The Java code is provided with the tutorial material as GenexplainTutorialChipseqAnalysis.java. Please note that some parts require editing before running the program, including username, password, project name.

Assuming the source file is stored as GenexplainTutorialChipseqAnalysis.java and the genexplain-api package is located in the same subfolder, the Java class can be compiled as follows.

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javac -cp .:genexplain-api.jar GenexplainTutorialChipseqAnalysis.java

Similarly, the class file can then be executed as

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java -cp .:genexplain-api.jar GenexplainTutorialChipseqAnalysis

Java code for the tutorial workflow

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import com.eclipsesource.json.JsonArray;
import com.eclipsesource.json.JsonValue;
import com.eclipsesource.json.JsonObject;
import com.eclipsesource.json.PrettyPrint;

import com.genexplain.api.core.GxHttpClient;
import com.genexplain.api.core.GxHttpClientImpl;
import com.genexplain.api.core.GxHttpConnection;
import com.genexplain.api.core.GxHttpConnectionImpl;

import java.io.FileOutputStream;
import java.io.FileWriter;
import java.io.StringWriter;
import java.io.Writer;

import java.util.HashMap;
import java.util.Map;



public class GenexplainTutorialChipseqAnalysis {
    public static void main(String[] args) throws Exception {

        // The GxHttpConnectionImpl holds the connection to the specified
        // platform server. Username and password need to correspond to a
        // valid account on that server.
        //
        GxHttpConnectionImpl con = new GxHttpConnectionImpl();
        con.setServer("https://platform.genexplain.com");
        con.setUsername("someuser@email.io");
        con.setPassword("12345");
        con.setVerbose(true);
        con.login();

        // The connection is given to a client object. The client is the 
        // main component to interact with the connected platform server.
        //
        GxHttpClientImpl client = new GxHttpClientImpl();
        client.setConnection(con);

        // The createProject method creates a new project in the user
        // workspace. The project name must be new and unique on the 
        // platform instance. The platform path of the new project is 
        // "data/Projects/<project name>".
        //
        Map<String, String> projectParams = new HashMap<>();
        projectParams.put("user", "someuser@email.io");
        projectParams.put("pass", "12345");
        projectParams.put("project", "api2022_tutorial");
        projectParams.put("description", "API 2022 tutorial project");
        client.createProject(projectParams)

        String folderPath = "data/Projects/api2022_tutorial/Data/chipseq_analysis_workflow_java";
        String species    = "Human (Homo sapiens)";

        // The createFolder function creates the folder if it does not 
        // already exist. Within a project, folders for data elements 
        // have to be created within the *Data* folder or its subfolders.
        //
        client.createFolder("data/Projects/api2022_tutorial/Data", "chipseq_analysis_workflow_java");



        //
        // Step 1. Import and mapping of TAL1-bound genomic regions
        //

        JsonObject params = new JsonObject().add("dbSelector", "Ensembl 52.36n Human (hg18)");

        // Import the BED file with TAL1-bound regions into the destination folder
        client.imPort("../data/GSM614003_jurkat.tal1.bed", folderPath, "BED format (*.bed)", params);

        // Sometimes a short interruption is required to allow processes
        // on the server complete their work
        Thread.sleep(1000);

        String bedPath      = folderPath + "/GSM614003_jurkat.tal1";
        String mappedPath   = folderPath + "/jurkat_chipseq_hg38";
        String unmappedPath = folderPath + "/jurkat_chipseq_hg38_unmapped";
        String mapping      = "hg18->hg38";
        params = new JsonObject()
              .add("input", bedPath)
              .add("mapping", mapping)
              .add("minMatch", 0.95)
              .add("out_file1", mappedPath)
              .add("out_file2", unmappedPath);

        // Run Liftover to map hg18 coordinates to hg38
        client.analyze("liftOver1", params, false, true, true);



        //
        // Step 2. Mapping TAL1-bound genomic regions to nearby genes
        //

        String mappedGenePath = mappedPath + " Genes";
        JsonArray sourcePaths = new JsonArray().add(mappedPath);
        params = new JsonObject()
              .add("sourcePaths", sourcePaths)
              .add("species", species)
              .add("from", -5000)
              .add("to", 2000)
              .add("destPath", mappedGenePath);

        // Run "Track to gene set" tool to map genomic coordinates to genes
        client.analyze("Track to gene set", params, false, true, true);



        //
        // Step 3. Functional enrichment analysis of genes near TAL1-bound
        // regions
        //

        String funclassResultPath = mappedGenePath + " GO";
        params = new JsonObject()
              .add("sourcePath", mappedGenePath)
              .add("species", species)
              .add("bioHub", "Full gene ontology classification")
              .add("minHits", 1)
              .add("pvalueThreshold", 1)
              .add("outputTable", funclassResultPath);

        // Enrichment of genes associated with Gene Ontology terms using
        // "Functional classification"
        client.analyze("Functional classification", params, false, true, true);

        FileOutputStream fileExport = new FileOutputStream("functional_classification_result_GO.tsv");

        // Export analysis result to local file
        client.export(funclassResultPath, "Tab-separated text (*.txt)", fileExport, new JsonObject());

        // The output stream is not closed by the platform client.
        fileExport.close();

        funclassResultPath = mappedGenePath + " Reactome";
        params.add("bioHub", "Reactome pathways (74)").add("outputTable", funclassResultPath);

        // Enrichment of genes associated with Reactome pathways
        client.analyze("Functional classification", params, false, true, true);

        fileExport = new FileOutputStream("functional_classification_result_Reactome.tsv");

        // Export analysis result to local file
        client.export(funclassResultPath, "Tab-separated text (*.txt)", fileExport, new JsonObject());

        fileExport.close();

        funclassResultPath = mappedGenePath + " Human disease biomarkers";
        params.add("bioHub", "HumanPSD(TM) disease (2022.1)").add("outputTable", funclassResultPath);

        // Enrichment of genes associated with human diseases based on
        // HumanPSD disease biomarker annotation
        client.analyze("Functional classification", params, false, true, true);

        fileExport = new FileOutputStream("functional_classification_result_HumanPSD.tsv");

        // Export analysis result to local file
        client.export(funclassResultPath, "Tab-separated text (*.txt)", fileExport, new JsonObject());

        fileExport.close();



        //
        // Step 4. Sampling genomic regions not bound by TAL1
        //

        String mealrBackgroundTrack = mappedPath + " random 1000";
        params = new JsonObject()
              .add("inputTrackPath", mappedPath)
              .add("dbSelector", "Ensembl 104.38 Human (hg38)")
              .add("species", species)
              .add("standardChromosomes", true)
              .add("seqNumber", 1000)
              .add("seqLength", 0)
              .add("from", 0)
              .add("to", 0)
              .add("withOverlap", false)
              .add("randomShift", false)
              .add("outputTrackPath", mealrBackgroundTrack)
              .add("randSeed", 123);

        // Create random track not overlapping with TAL1-bound regions
        client.analyze("Create random track", params, false, true, true);



        //
        // Step 5. Import and mapping of TAL1 binding site subset
        //

        // Data upload and lifting as in Step 1 for 1000 TAL1 sites sampled
        // from the original BED file

        params = new JsonObject().add("dbSelector", "Ensembl 52.36n Human (hg18)");

        // Import sampled TAL1 ChIP-seq sites
        client.imPort("../data/GSM614003_jurkat.tal1_1000.bed", folderPath, "BED format (*.bed)", params);

        // Sometimes a short interruption is required to allow processes
        // on the server complete their work
        Thread.sleep(1000);

        bedPath      = folderPath + "/GSM614003_jurkat.tal1_1000";
        mappedPath   = folderPath + "/jurkat_chipseq_hg38_1000";
        unmappedPath = folderPath + "/jurkat_chipseq_hg38_1000_unmapped";
        params = new JsonObject()
              .add("input", bedPath)
              .add("mapping", mapping)
              .add("minMatch", 0.95)
              .add("out_file1", mappedPath)
              .add("out_file2", unmappedPath);

        // Coordinate mapping to hg38
        client.analyze("liftOver1", params, false, true, true);



        //
        // Step 6. Selection of important PWM models using MEALR
        //

        String mealrOutputPath = mappedPath + " MEALR";
        String transfacProfile = "databases/TRANSFAC(R) 2022.1/Data/profiles/vertebrate_human_p0.05_non3d";
        params = new JsonObject()
              .add("yesSetPath", mappedPath)
              .add("noSetPath",  mealrBackgroundTrack)
              .add("dbSelector", "Ensembl 104.38 Human (hg38)")
              .add("profilePath", transfacProfile)
              .add("maxPosCoef", 150)
              .add("maxComplexity", 0.5)
              .add("complexityInc", 0.02)
              .add("maxUnimproved", 20)
              .add("scoresWithNoSet", false)
              .add("output", mealrOutputPath);

        // Analyze target and background genomic regions using MEALR
        client.analyze("MEALR (tracks)", params, false, true, true);



        //
        // Step 7. Extraction of binding transcription factors
        //

        String mealrMotifPath = mealrOutputPath + "/MEALR_positive_coefficients";
        String mealrTopPath   = mealrMotifPath + " Top 50";
        params = new JsonObject()
              .add("inputTable", mealrMotifPath)
              .add("column", "Coefficient")
              .add("types", new JsonArray().add("Top"))
              .add("topPercent", 100.0)
              .add("topCount", 50)
              .add("topMinCount", 50)
              .add("topTable", mealrTopPath);

        // Extract top 50 PWMs ranked by logistic regression coefficient
        client.analyze("Select top rows", params, false, true, true);

        String mealrTopGenePath = mealrTopPath + " Genes";
        params = new JsonObject()
              .add("sitesCollection", mealrTopPath)
              .add("siteModelsCollection", transfacProfile)
              .add("species", species)
              .add("targetType", "Genes: Ensembl")
              .add("outputTable", mealrTopGenePath);

        // Convert PWMs to factor genes
        client.analyze("Matrices to molecules", params, false, true, true);



        //
        // Step 8. Intersection of potentially TAL1-regulated genes and 
        // MEALR TFs
        //

        String mappedNearbyGenePath = folderPath + "/jurkat_chipseq_hg38 Genes";
        String mealrTopVennPath     = mealrTopPath + " Venn";
        params = new JsonObject()
              .add("table1Path", mappedNearbyGenePath)
              .add("table1Name", "Genes near TAL1 sites")
              .add("table2Path", mealrTopGenePath)
              .add("table2Name", "MEALR transcription factors")
              .add("simple", true)
              .add("output", mealrTopVennPath);

        // Intersect factors identified by MEALR and genes with nearby
        // TAL1 ChIP-seq sites
        client.analyze("Venn diagrams", params, false, true, true);



        //
        // Step 9. Prediction of binding sites of identified TFs in 
        // TAL1-bound genomic regions
        //

        String grnFactorPath = mealrTopVennPath + "/Rows present in both tables";

        // Load table with potential GRN factors
        JsonObject tableData = client.getTable(grnFactorPath);

        // The JSON object contains the table data under property
        // "data"
        JsonArray topPwms  = tableData.get("data").asArray().get(3).asArray();
        JsonArray topCoefs = tableData.get("data").asArray().get(4).asArray();
        String tpwms;
        String[] pwmids;
        double tcoef;
        Map<String, Double> topPwmData = new HashMap<>();

        // Extract PWM ids and coefficients
        for (int t = 0; t < topPwms.size(); ++t) {
            tpwms = topPwms.get(t).asString();
            tcoef = topCoefs.get(t).asDouble();
            pwmids = tpwms.split(",");
            for (String id : pwmids) {
                if (topPwmData.containsKey(id)) {
                    topPwmData.put(id, Math.max(topPwmData.get(id), tcoef));
                } else {
                    topPwmData.put(id, tcoef);
                }
            }
        }

        // Create PWM table for upload
        FileWriter fw = new FileWriter("grn_pwms.tsv");
        fw.write("PWM\tCoefficient\n");
        for (String id :  topPwmData.keySet()) {
            fw.write(id + "\t" + topPwmData.get(id) + "\n");
        }
        fw.close();

        // Import PWM table
        client.importTable("grn_pwms.tsv", mealrOutputPath, 
                           "MEALR_positive_coefficients Top 50 GRN PWMs", 
                           false, GxHttpClient.ColumnDelimiter.Tab, 1, 2, "", "PWM",
                           false, "Matrices: TRANSFAC", species);

        // Sometimes a short interruption is required to allow processes
        // on the server complete their work
        Thread.sleep(1000);

        String grnPwmPath = mealrOutputPath + "/MEALR_positive_coefficients Top 50 GRN PWMs";
        transfacProfile = "databases/TRANSFAC(R) 2022.1/Data/profiles/vertebrate_human_p0.001_non3d";
        String grnPwmProfile = grnPwmPath + " profile";
        params = new JsonObject()
              .add("table", grnPwmPath)
              .add("profile", transfacProfile)
              .add("outputProfile", grnPwmProfile);

        // Create Match(TM) profile for PWMs of potential GRN factors
        client.analyze("Create profile from site model table", params, false, true, true);

        String grnMatchPath = grnPwmProfile + " Match";
        params = new JsonObject()
              .add("sequencePath", folderPath + "/jurkat_chipseq_hg38")
              .add("dbSelector", "Ensembl 104.38 Human (hg38)")
              .add("profilePath", grnPwmProfile)
              .add("withoutDuplicates", true)
              .add("ignoreCore", true)
              .add("output", grnMatchPath);

        // Predict binding sites of GRN factors in TAL1-bound regions
        client.analyze("TRANSFAC(R) Match(TM) for tracks", params, false, true, true);



        //
        // Step 10. Prediction of binding sites of identified TFs around 
        // TAL1 transcription start site
        //

        // Create TAL1 gene table for import        
        fw = new FileWriter("tal1.tsv");
        fw.write("ID\tSymbol\nENSG00000162367\tTAL1\n");
        fw.close();

        // Import TAL1 gene
        client.importTable("tal1.tsv", mealrOutputPath, "TAL1 gene", 
                           false, GxHttpClient.ColumnDelimiter.Tab, 1, 2, "", "ID",
                           false, "Genes: Ensembl", species);

        // Sometimes a short interruption is required to allow processes
        // on the server complete their work
        Thread.sleep(1000);

        String tal1GenePath = mealrOutputPath + "/TAL1 gene";
        String tal1TrackPath = tal1GenePath + " promoter";
        params = new JsonObject()
              .add("sourcePath", tal1GenePath)
              .add("species", species)
              .add("from", 2000)
              .add("to", 1000)
              .add("destPath", tal1TrackPath);

        // Create track of genomic region around TAL1 TSS (promoter)
        client.analyze("Gene set to track", params, false, true, true);

        String tal1MatchPath = grnPwmProfile + " TAL1 Match";
        params = new JsonObject()
              .add("sequencePath", tal1TrackPath)
              .add("dbSelector", "Ensembl 104.38 Human (hg38)")
              .add("profilePath", grnPwmProfile)
              .add("withoutDuplicates", true)
              .add("ignoreCore", true)
              .add("output", tal1MatchPath);

        // Predict binding sites of GRN factors in TAL1 promoter
        client.analyze("TRANSFAC(R) Match(TM) for tracks", params, false, true, true);

        fileExport = new FileOutputStream("TAL1_grn_pwm_sites.bed");

        // Export genomic locations of predicted sites for GRN factors
        // around TAL1 TSS
        client.export(tal1MatchPath, "BED format (*.bed)", fileExport, new JsonObject());

        fileExport.close();

        con.logout();
    }
}