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Pay Giesselmann

Nanopype: processing and quantification of short tandem repeats

About Pay Giesselmann

Pay received his MSc in Electrical Engineering from the Kiel University of Applied Sciences with a focus on embedded systems and hardware accelerated signal processing. He is currently a PhD student in Alex Meissner's lab at the Max-Planck-Institute for Molecular Genetics in Berlin. Pay is interested in the epigenetic regulation of the genome, direct base modification detection and developing tools and pipelines to process third generation sequencing data.

Abstract

The availability of substantially longer reads with the Oxford Nanopore approach opens new possibilities in many fields and explains the increasing use of the nanopore technology. To facilitate access and match storage as well as processing routines to the higher demand, we assembled Nanopype a modular, parallelized and easy-to-use pipeline to process the sequencing data from the raw signal output into standardized formats. Specifically, Nanopype facilitates the essential steps of base calling, quality control, and alignments, as well as various downstream applications by incorporating field-specific tools and complemented by custom utility scripts. To illustrate its application, we apply it to the assessment of short tandem repeats that have been implicated in neuropsychiatric disorders. Combined with a Cas12a-based enrichment strategy and the STRique package we show efficient targeting and quantification on raw signal level, as well as determination of the associated methylation status.

Pay Giesselmann

Pay Giesselmann

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