Updating outdated comments.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2595 348d0f76-0448-11de-a6fe-93d51630548a
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@ -52,9 +52,9 @@ import net.sf.samtools.SAMRecord;
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* Since there is a large amount of data one can then calculate an empirical probability of error
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* given the particular covariates seen at this site, where p(error) = num mismatches / num observations
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* The output file is a CSV list of (the several covariate values, num observations, num mismatches, empirical quality score)
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* The first lines of the output file give the name of the covariate classes that were used for this calculation.
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* The first non-comment line of the output file gives the name of the covariates that were used for this calculation.
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*
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* Note: ReadGroupCovariate and QualityScoreCovariate are required covariates and must be at the start of the list.
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* Note: ReadGroupCovariate and QualityScoreCovariate are required covariates and will be added for the user regardless of whether or not they were specified
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* Note: This walker is designed to be used in conjunction with TableRecalibrationWalker.
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*
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* @author rpoplin
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@ -472,7 +472,7 @@ public class CovariateCounterWalker extends LocusWalker<Integer, PrintStream> {
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// Output the RecalDatum entry
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recalTableStream.println( ((RecalDatumOptimized)val).outputToCSV() );
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} else { // Another layer in the nested hash map
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printMappingsSorted( recalTableStream, curPos + 1, key, (Map) val);
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printMappingsSorted( recalTableStream, curPos + 1, key, (Map) val );
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}
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}
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}
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@ -490,7 +490,7 @@ public class CovariateCounterWalker extends LocusWalker<Integer, PrintStream> {
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// Output the RecalDatum entry
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recalTableStream.println( ((RecalDatumOptimized)val).outputToCSV() );
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} else { // Another layer in the nested hash map
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printMappings( recalTableStream, curPos + 1, key, (Map) val);
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printMappings( recalTableStream, curPos + 1, key, (Map) val );
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}
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}
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}
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