서울대학교 생물정보학 협동과정 주최로 세미나를 아래와 같이 열고자 하오니 많은 참여 바랍니다.

세미나는 Zoom을 통한 온라인 강의로 예정되어 있으며 강의에 참여하고자 하시는 분께서는 아래의 링크로 참여 부탁드리겠습니다.

*줌으로 참석하기 위해서는 "참석자로 회의 참가" --> 이름, 성, 이메일 주소, 이메일 주소 확인을 입력하시고 등록하시면 회의 참석이 가능합니다.

일시: 2023년 10월 10일 화요일 오전 11시

연사: 김상우 교수님 (연세대학교)

Zoom link: http://snu-ac-kr.zoom.us/s/93550554795

Title: Towards accurate detection of low-allele fraction somatic and mosaic mutations

Abstract

Accurate detection of somatic variants has been a central problem in genomic study for a long time. Many computational and experimental techniques were developed to detect mutations with variant allele frequency (VAF) of <1%. However, there are still many challenges remaining from various artifacts in sample collection and preparation, sequencing, ambiguity in genome alignment and also human errors.

We have been working on this problem for many years, and here we will talk about our approaches on this problem. This includes our earlier work on developing computational algorithms to enhance the variant calling performances in the presence of impurity (Virmid, Genome Biol 2013), and with sequencing replication (Replow, Nat. Communs 2019), which could detect somatic mutations of VAF less than 5% and 1%, respectively. We will then talk about our efforts to construct a trustworthy reference standard for low-allele mosaic variants (MRS, Scientific Data 2022), and a benchmark study of nine available tools and approaches on it (Nature Methods 2023). This benchmark study also drew several important conclusions in the optimal analysis of low-AF mosaic mutations.

Our strategies include non-computational approaches to detect low AF variants for liquid biopsy. We developed a CRISPR-cas9 based method to increase variant allele frequencies by reducing non-variant DNA fragment (2022, patent submitted). This will provide a way of detecting low-AF cancer driver and druggable mutations in clinic.

This talk will also cover methods for descriptive studies, in which statistical features (e.g., mutation burden and signatures) are assessed rather than finding specific mutations. Duplex-sequencing derived methods provided excellent ways for it. We will also introduce our ongoing work on the similar aspect, but mainly in a computational-level in a conventional sequencing (Moana, ongoing).

Finally, we will introduce a few methods that handle human errors, including external DNA contamination (Vecuum, 2016) and sample mixup (BamixChecker, 2019) that can be also used routinely to prevent rare, but devastating errors in the NGS analysis.

(+) 세미나 관련 문의사항은 이메일(jun4541@snu.ac.kr)로 부탁드립니다.