def parse_sample(qc_sample):
    """Parse out relevant information from sample data."""
    data = {}
    for key, value in qc_sample.items():
        if 'lanes' in key:
            hs_metrics = value['CalculateHsMetrics']['Header']['Data']
            mult_metrics = value['CollectMultipleMetrics']['Header']['Pair']
            data['strand_balance'] = mult_metrics['STRAND_BALANCE']
            data['sex_predicted'] = value['ChanjoSexCheck']['gender']
            data['coverage_target'] = hs_metrics['MEAN_TARGET_COVERAGE']
            data['completeness_target_10'] = hs_metrics['PCT_TARGET_BASES_10X']
            data['completeness_target_20'] = hs_metrics['PCT_TARGET_BASES_20X']
            data['completeness_target_50'] = hs_metrics['PCT_TARGET_BASES_50X']
            data['completeness_target_100'] = hs_metrics[
                'PCT_TARGET_BASES_100X']
            comp_overlap = value['VariantEval_All']['CompOverlap_header'][
                'CompOverlap_data_all']
            variant_sum = value['VariantEval_All']['VariantSummary_header'][
                'VariantSummary_data_all']
            variant_count = value['VariantEval_All']['CountVariants_header'][
                'CountVariants_data_all']
            data['variants'] = comp_overlap['nEvalVariants']
            data['indels'] = variant_sum['nIndels']
            data['snps'] = variant_sum['nSNPs']
            data['titv_ratio'] = variant_sum['TiTvRatio']
            data['novel_sites'] = comp_overlap['novelSites']
            data['concordant_rate'] = comp_overlap['concordantRate'] / 100
            data['hethom_ratio'] = variant_count['hetHomRatio']
    data['reads'] = qc_sample['TotalReads']
    data['mapped_percent'] = qc_sample['MappedRate']
    data['duplicates_percent'] = qc_sample['Duplicates']
    return data
