Package org.broadinstitute.gatk.utils.exceptions

Examples of org.broadinstitute.gatk.utils.exceptions.UserException$ErrorWritingBamFile


        samples.addAll(SampleUtils.getUniqueSamplesFromRods(getToolkit(), inputNames));

        if( TS_FILTER_LEVEL != null ) {
            // if the user specifies both ts_filter_level and lodCutoff then throw a user error
            if( VQSLOD_CUTOFF != null ) {
                throw new UserException("Arguments --ts_filter_level and --lodCutoff are mutually exclusive. Please only specify one option.");
            }

            if( tranches.size() >= 2 ) {
                for( int iii = 0; iii < tranches.size() - 1; iii++ ) {
                    final Tranche t = tranches.get(iii);
                    hInfo.add(new VCFFilterHeaderLine(t.name, String.format("Truth sensitivity tranche level for " + t.model.toString() + " model at VQS Lod: " + t.minVQSLod + " <= x < " + tranches.get(iii+1).minVQSLod)));
                }
            }
            if( tranches.size() >= 1 ) {
                hInfo.add(new VCFFilterHeaderLine(tranches.get(0).name + "+", String.format("Truth sensitivity tranche level for " + tranches.get(0).model.toString() + " model at VQS Lod < " + tranches.get(0).minVQSLod)));
            } else {
                throw new UserException("No tranches were found in the file or were above the truth sensitivity filter level " + TS_FILTER_LEVEL);
            }

            logger.info("Keeping all variants in tranche " + tranches.get(tranches.size()-1));
        } else {
            if( VQSLOD_CUTOFF == null ) {
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            if( VariantDataManager.checkVariationClass( vc, MODE ) && (IGNORE_ALL_FILTERS || vc.isNotFiltered() || ignoreInputFilterSet.containsAll(vc.getFilters())) ) {

                final VariantContext recalDatum = getMatchingRecalVC(vc, recals);
                if( recalDatum == null ) {
                    throw new UserException("Encountered input variant which isn't found in the input recal file. Please make sure VariantRecalibrator and ApplyRecalibration were run on the same set of input variants. First seen at: " + vc );
                }

                final String lodString = recalDatum.getAttributeAsString(VariantRecalibrator.VQS_LOD_KEY, null);
                if( lodString == null ) {
                    throw new UserException("Encountered a malformed record in the input recal file. There is no lod for the record at: " + vc );
                }
                final double lod;
                try {
                    lod = Double.valueOf(lodString);
                } catch (NumberFormatException e) {
                    throw new UserException("Encountered a malformed record in the input recal file. The lod is unreadable for the record at: " + vc );
                }

                VariantContextBuilder builder = new VariantContextBuilder(vc);

                // Annotate the new record with its VQSLOD and the worst performing annotation
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            throw new IllegalStateException("Somehow more than one variant was bound?");

        final VCFHeader header = new ArrayList<>(vcfRods.values()).get(0); // pure laziness

        if ( ! header.hasGenotypingData() ) {
            throw new UserException("VCF has no genotypes");
        }

        if ( header.hasInfoLine(VCFConstants.MLE_ALLELE_COUNT_KEY) ) {
            final VCFInfoHeaderLine mleLine = header.getInfoHeaderLine(VCFConstants.MLE_ALLELE_COUNT_KEY);
            if ( mleLine.getCountType() != VCFHeaderLineCount.A ) {
                throw new UserException("VCF does not have a properly formatted MLEAC field: the count type should be \"A\"");
            }

            if ( mleLine.getType() != VCFHeaderLineType.Integer ) {
                throw new UserException("VCF does not have a properly formatted MLEAC field: the field type should be \"Integer\"");
            }
        }

        // Initialize VCF header
        final Set<VCFHeaderLine> headerLines = VCFUtils.smartMergeHeaders(vcfRods.values(), true);
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        try {
            File csvTmpFile = File.createTempFile("BQSR",".csv");
            csvTmpFile.deleteOnExit();
            csvStream = new PrintStream(csvTmpFile);
        } catch (IOException e) {
            throw new UserException("Could not create temporary csv file", e);
        }

        if ( recalibrated != null )
            writeCSV(csvStream, recalibrated, "RECALIBRATED", requestedCovariates, true);
        writeCSV(csvStream, original, "ORIGINAL", requestedCovariates, recalibrated == null);
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    PriorityQueue<SAMRecord> waitingReads = new PriorityQueue<SAMRecord>(initialCapacity, comparer);

    private SAMRecord remove(PriorityQueue<SAMRecord> queue) {
        SAMRecord first = queue.poll();
        if (first == null)
            throw new UserException("Error caching SAM record -- priority queue is empty, and yet there was an attempt to poll it -- which is usually caused by malformed SAM/BAM files in which multiple identical copies of a read are present.");
        return first;
    }
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    private void writeRead(SAMRecord read) {
        try {
            if ( writer != null )
                writer.addAlignment(read);
        } catch (IllegalArgumentException e) {
            throw new UserException("If the maximum allowable reads in memory is too small, it may cause reads to be written out of order when trying to write the BAM; please see the --maxReadsInMemory argument for details.  " + e.getMessage(), e);
        }
    }
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    @Override
    public void initialize() {
        super.initialize();

        if (getToolkit().getIntervals() == null || getToolkit().getIntervals().isEmpty())
            throw new UserException("This tool only works if you provide one or more intervals (use the -L argument). If you want to run whole genome, use -T DepthOfCoverage instead.");

        intervalMap = new LinkedHashMap<GenomeLoc, IntervalStratification>(INITIAL_HASH_SIZE);
        intervalListIterator = new PeekableIterator<GenomeLoc>(getToolkit().getIntervals().iterator());

        // get all of the unique sample names for the VCF Header
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        for ( double trancheThreshold : trancheThresholds ) {
            Tranche t = findTranche(data, metric, trancheThreshold, model);

            if ( t == null ) {
                if ( tranches.size() == 0 )
                    throw new UserException(String.format("Couldn't find any tranche containing variants with a %s > %.2f. Are you sure the truth files contain unfiltered variants which overlap the input data?", metric.getName(), metric.getThreshold(trancheThreshold)));
                break;
            }

            tranches.add(t);
        }
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        this.accessibleTruthSites = accessibleTruthSites;
        this.callsAtTruthSites = callsAtTruthSites;

        if ( ts < 0.0 || ts > 100.0)
            throw new UserException("Target FDR is unreasonable " + ts);

        if ( numKnown < 0 || numNovel < 0)
            throw new ReviewedGATKException("Invalid tranche - no. variants is < 0 : known " + numKnown + " novel " + numNovel);

        if ( name == null )
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                final Object args[] = new Object[]{UAC,logger};
                final Constructor c = glmClass.getDeclaredConstructor(UnifiedArgumentCollection.class, Logger.class);
                glcm.put(key, (GenotypeLikelihoodsCalculationModel)c.newInstance(args));
            }
            catch (Exception e) {
                throw new UserException("The likelihoods model provided for the -glm argument (" + UAC.GLmodel + ") is not a valid option: " + e.getMessage());
            }
        }

        return glcm;
    }
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