Allow script to be easily modified to support different platforms.

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@955 348d0f76-0448-11de-a6fe-93d51630548a

doc/ReadQualityRecalibrator/README

@@ -66,6 +66,15 @@ To (only) evaluate a given bam file after calibrating:
 
 python RecalQual.py --evaluate <source bam> <recalibrated bam>
 
+Platforms
+---------
+By default, the recalibrator processes only read groups
+originating from Illumina sequencers.  To enable calibration
+for other platforms, edit the 'platforms' array at the
+top of RecalQual.py.  Platforms specified here should
+case-insensitive match the "PL" attribute of the read
+group in the BAM file.
+
 Output
 ------
 The recalibration process keeps many incremental

java/src/org/broadinstitute/sting/playground/gatk/walkers/CovariateCounterWalker.java

@@ -15,6 +15,7 @@ import java.util.ArrayList;
 import java.util.List;
 import java.util.Random;
 import java.util.HashMap;
+import java.util.Collections;
 import java.io.PrintStream;
 import java.io.FileNotFoundException;
 
@@ -44,6 +45,9 @@ public class CovariateCounterWalker extends LocusWalker<Integer, Integer> {
     @Argument(fullName="MAX_READ_GROUPS", shortName="mrg", required=false, doc="Abort if number of read groups in input file exceeeds this count.")
     public int MAX_READ_GROUPS = 100;
 
+    @Argument(fullName="PLATFORM", shortName="pl", required=false, doc="Only calibrate read groups generated from the given platform (default = Illumina)")
+    public List<String> platforms = Collections.singletonList("ILLUMINA");
+
     int NDINUCS = 16;
     ArrayList<RecalData> flattenData = new ArrayList<RecalData>();
     HashMap<String, RecalData[][][]> data = new HashMap<String, RecalData[][][]>();
@@ -101,8 +105,8 @@ public class CovariateCounterWalker extends LocusWalker<Integer, Integer> {
 
         for (SAMReadGroupRecord readGroup : this.getToolkit().getEngine().getSAMHeader().getReadGroups()) {
             if( readGroup.getAttribute("PL") == null )
-                Utils.warnUser(String.format("PL attribute for read group %s is unset; assuming all reads are illumina",readGroup.getReadGroupId()));
+                Utils.warnUser(String.format("PL attribute for read group %s is unset; assuming all reads are supported",readGroup.getReadGroupId()));
-            if( !isIlluminaReadGroup(readGroup) )
+            if( !isSupportedReadGroup(readGroup) )
                 continue;
             data.put(readGroup.getReadGroupId(), new RecalData[MAX_READ_LENGTH+1][MAX_QUAL_SCORE+1][NDINUCS]);
             for ( int i = 0; i < MAX_READ_LENGTH+1; i++) {
@@ -126,7 +130,7 @@ public class CovariateCounterWalker extends LocusWalker<Integer, Integer> {
             for (int i =0; i < reads.size(); i++ ) {
                 SAMRecord read = reads.get(i);
                 SAMReadGroupRecord readGroup = read.getHeader().getReadGroup((String)read.getAttribute("RG"));
-                if ( isIlluminaReadGroup(readGroup) &&
+                if ( isSupportedReadGroup(readGroup) &&
                     !read.getReadNegativeStrandFlag() &&
                     (READ_GROUP.equals("none") || read.getAttribute("RG") != null && read.getAttribute("RG").equals(READ_GROUP)) &&
                     (read.getMappingQuality() >= MIN_MAPPING_QUALITY)) {
@@ -394,7 +398,18 @@ public class CovariateCounterWalker extends LocusWalker<Integer, Integer> {
         random_genrator = new Random(123454321); // keep same random seed while debugging
     }
 
-    private boolean isIlluminaReadGroup( SAMReadGroupRecord readGroup ) {
+    /**
-        return (readGroup.getAttribute("PL") == null || "ILLUMINA".equalsIgnoreCase(readGroup.getAttribute("PL").toString()));
+     * Check to see whether this read group should be processed.
+     * @param readGroup
+     * @return
+     */
+    private boolean isSupportedReadGroup( SAMReadGroupRecord readGroup ) {
+        for( String platform: platforms ) {
+            platform = platform.trim();
+            if( readGroup.getAttribute("PL") == null || readGroup.getAttribute("PL").toString().equalsIgnoreCase(platform) )
+                return true;
+        }
+
+        return false;
     }
 }

python/RecalQual.py

@@ -8,6 +8,9 @@ R_exe="/broad/tools/apps/R-2.6.0/bin/Rscript"
 # Any special site-specific arguments to pass the JVM.
 jvm_args='-ea -Xmx4096m'
 
+# Which platforms should the calibration tool be run over?
+platforms=['illumina']
+
 # Where to put the output created as part of recalibration.  
 # If editing, please end this variable with a trailing slash.
 output_root = './'
@@ -39,6 +42,9 @@ gatk = resources + 'gatk/GenomeAnalysisTK.jar'
 logistic_regression_script = resources + 'logistic_regression.R'
 empirical_vs_reported_grapher = resources + 'plot_q_emp_stated_hst.R'
 
+# Assemble the platform list into command-line arguments.
+platform_args = ' '.join(['-pl %s' % platform for platform in platforms])
+
 def exit(msg,errorcode):
     print msg
     sys.exit(errorcode)
@@ -59,7 +65,7 @@ def recalibrate():
     'Recalibrate the given bam file'
     # generate the covariates
     print 'generating covariates'
-    generate_covariates = ' '.join((gatk_base_cmdline,'-T CountCovariates','-I',bam,'-mqs 40','--OUTPUT_FILEROOT',output_dir+'initial','--CREATE_TRAINING_DATA','--MIN_MAPPING_QUALITY 1'))
+    generate_covariates = ' '.join((gatk_base_cmdline,'-T CountCovariates','-I',bam,'-mqs 40','--OUTPUT_FILEROOT',output_dir+'initial','--CREATE_TRAINING_DATA','--MIN_MAPPING_QUALITY 1',platform_args))
     returncode = os.system(generate_covariates)
     if returncode != 0:
         exit('Unable to generate covariates',1)
@@ -88,7 +94,7 @@ def evaluate():
     'Evaluate recalibration results.'
     print 'Evaluating recalibration results'
     # regenerate the covariates
-    regenerate_covariates = ' '.join((gatk_base_cmdline,'-T CountCovariates','-I',calibrated_bam,'-mqs 40','--OUTPUT_FILEROOT',output_dir+'recalibrated','--CREATE_TRAINING_DATA','--MIN_MAPPING_QUALITY 1'))
+    regenerate_covariates = ' '.join((gatk_base_cmdline,'-T CountCovariates','-I',calibrated_bam,'-mqs 40','--OUTPUT_FILEROOT',output_dir+'recalibrated','--CREATE_TRAINING_DATA','--MIN_MAPPING_QUALITY 1',platform_args))
     print 'regenerating covariates'
     returncode = os.system(regenerate_covariates)
     if returncode != 0: