BWT construction and search at the terabase scale
원문 초록
Motivation: Burrows-Wheeler Transform (BWT) is a common component in full-text indices. Initially developed for data compression, it is particularly powerful for encoding redundant sequences such as pangenome data. However, BWT construction is resource intensive and hard to be parallelized, and many methods for querying large full-text indices only report exact matches or their simple extensions. These limitations have hampered the biological applications of full-text indices. Results: We developed ropebwt3 for efficient BWT construction and query. Ropebwt3 indexed 320 assembled human genomes in 65 hours and indexed 7.3 terabases of commonly studied bacterial assemblies in 26 days. This was achieved using up to 170 gigabytes of memory at the peak without working disk space. Ropebwt3 can find maximal exact matches and inexact alignments under affine-gap penalties, and can retrieve similar local haplotypes matching a query sequence. It demonstrates the feasibility of full-text indexing at the terabase scale. Availability and implementation: https://github.com/lh3/ropebwt3
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
Stationary MMD Points for Cubature
MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models
Efficient compression of neural networks and datasets
DD-Ranking: Rethinking the Evaluation of Dataset Distillation
ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.