Abstract
Next-generation sequencing produces high-throughput data, albeit with greater error and shorter reads than traditional Sanger sequencing methods. This complicates the detection of genomic variations, especially, small insertions and deletions. Here we describe ParMap, a statistical algorithm for the identification of complex genetic variants using partially mapped reads in nextgen sequencing data. We also report ParMap’s successful application to the mutation analysis of chromosome X exome-captured leukemia DNA samples.
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Khiabanian, H., Van Vlierberghe, P., Palomero, T. et al. ParMap, an Algorithm for the Identification of Complex Genomic Variations in Nextgen Sequencing Data. Nat Prec (2010). https://doi.org/10.1038/npre.2010.4145.1
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DOI: https://doi.org/10.1038/npre.2010.4145.1