Poster
0

CONSULT-II: Accurate taxonomic identification and profiling using locality-sensitive hashing

Avatar
Voices Powered byElevenlabs logo

Available only for arXiv papers.

Authors

Sapci, A. O. B.; Rachtman, E.; Mirarab, S.

Abstract

Taxonomic classification of metagenomic reads is a well-studied yet challenging problem. Identifying species belonging to ranks without close representation in a reference dataset are in particular challenging. While k-mer-based methods have performed well in terms of running time and accuracy, they have reduced accuracy for novel species. Here, we show that using locality-sensitive hashing (LSH) can increase the sensitivity of the k-mer-based search. Our method, which combines LSH with several heuristics techniques including soft LCA labeling and voting is more accurate than alternatives in both taxonomic classification and profiling.

Follow Us on

0 comments

Add comment
Recommended SciCasts