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DTSTART;TZID=America/Los_Angeles:20261030T130000
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DTSTAMP:20261021T162533Z
CREATED:20261021T162533Z
LAST-MODIFIED:20261021T162533Z
UID:10017879-1793365200-1793368800@live-events-ucsc.pantheonsite.io
SUMMARY:Asri\, M. (BMEB) - Genome Inference in the Pangenome Era
DESCRIPTION:Human genome references have provided unified coordinate systems for mapping genetic variation\, enabling numerous discoveries in genomics. However\, mapping to a single linear reference can be misleading or even impossible when a sample’s genome is highly divergent from the reference\, an issue known as reference bias. Recent advances in long-read sequencing technologies and computational techniques have made generating high-quality genome assemblies at scale more feasible than ever. This shift has paved the way for efforts such as the Human Pangenome Reference Consortium (HPRC)\, whose mission is to build a human pangenome reference that represents human genetic diversity and mitigates reference bias. In this dissertation\, I present methods I developed that contribute to building more accurate pangenome references and advancing their applications in variant calling\, ultimately enabling more accurate genome inference. \nFirst\, I introduce Secphase\, a tool for correcting read mappings with direct applications in fixing assembly errors. Secphase corrects mismapped Pacific Biosciences (PacBio) HiFi reads by leveraging long-range phasing information from Oxford Nanopore Technologies (ONT) data. As a core component of the PHARAOH pipeline\, Secphase was coupled with DeepPolisher\, a transformer-based polisher\, to polish 230 HPRC assemblies\, reducing errors by half. \nSecond\, I present HMM-Flagger\, a reference-free tool for detecting structural misassemblies based on the coverage of mapped long reads. It models read coverage using a hidden Markov model (HMM)\, enabling it to classify coverage anomalies as erroneous blocks\, false duplications\, or collapsed blocks. HMM-Flagger has been used extensively in the evaluation and selection of genome assemblies for the HPRC releases. \nFinally\, as an application of pangenomes\, I highlight work on extending DeepVariant to build a pangenome-aware variant caller by augmenting sample-specific input data with pangenome alignments. Using Element Biosciences reads\, pangenome-aware DeepVariant generated call sets with up to 46.5% fewer errors than existing methods. \nEvent Host: Mobin Asri\, PhD Candidate\, Biomolecular Engineering & Bioinformatics  \nAdvisor: Benedict Paten \nZoom: https://ucsc.zoom.us/j/91210219698?pwd=HA0b0by9HcKlKiBua7anVBZ7ZfSfJu.1 \nPasscode: 594980
URL:https://live-events-ucsc.pantheonsite.io/event/asri-m-bmeb-genome-inference-in-the-pangenome-era/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
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