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Chunk #8 — Introduction — Detection of translocations and inversions

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Detection of structural DNA variation from next generation sequencing data: a review of informatic approaches.
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generated, tend to occur in regions with repetitive elements, such as tandem duplications and transposons (26). Thus, true positives exist in these regions and are difficult to discern from the many false positives. The Hydra and VariationHunter software packages attempt to detect structural variations occurring in such repetitive regions by considering multiple possible high scoring mappings per read, rather than just the unique, best mapping. Most paired-read methods for detection of structural variation rely on heuristic cutoffs to filter out false positives, such as the number of supporting read pairs. One recently described algorithm, however, GASVPro, combines paired-end and subtle coverage depth signals into a probabilistic model to achieve greatly improved specificity in detection of structural variation (28).