Scalability Challenges in Large-Scale Sequence Search

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Scalability Challenges in Large-Scale Sequence Search

When	Wednesday, September 28, 2022, 10:30 AM – 11:45 AM (MT)
Where	WEB 3780

Abstract

Sequence-level searches on large collections of RNA sequencing experiments, such as the NCBI Sequence Read Archive (SRA), would enable one to ask many questions about the expression or variation of a given transcript in a population. Building an efficient and scalable sequence search index at the scale of SRA data is a challenging task and requires fundamental innovations in compression and scalable indexing. Recently, several tools have been proposed to index and search through SRA data but they offer various trade-offs in terms of space, speed, updatability, and accuracy. In this talk, I will present Mantis, a fast, exact, and updatable sequence search index. Mantis uses recent advancements in fast and compact hash tables, domain-specific data compression techniques, and scalable indexing to build a scalable and updatable index and supports fast sequence searches on ~40K experiments (>100TB) in size from SRA.

Speaker

Tags: biology & genomics data management

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