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Sam Kovaka

Visualization and analysis of nanopore RNA and DNA signal alignments with UNCALLED4

About Sam Kovaka

Sam Kovaka is a Ph.D. candidate in Computer Science at Johns Hopkins University, co-advised by Michael Schatz and Mihaela Pertea. He graduated from Clark University in 2016 with a bachelor's degree in Computer Science and Biology. His primary research interests are nanopore signal-level analysis and transcriptomics. Previous work includes UNCALLED, a rapid nanopore signal aligner which enables adaptive sampling, and StringTie2, a long-read transcriptome assembler.

Abstract

Alignment of nanopore signal to nucleotide references has been used for adaptive sampling, modification detection, polishing, and more. Despite its widespread use, little attention has been given to the comparison and analysis of alignment methods. Here, we present UNCALLED4: a toolkit for nanopore signal alignment, analysis, and visualization. Building off signal processing methods from UNCALLED version 1, UNCALLED4 features interactive alignment visualizations, an alignment algorithm guided by Guppy metadata, methods for comparing Tombo and nanopolish alignments, and epigenetic modification detection statistics. Uncalled4 is implemented in C++ and Python, and provides a command line interface, Python API, and browser-based display.

Sam Kovaka

Sam Kovaka

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