Detection of Pathogenic Microbe Composition Using Next-Generation Sequencing Data.

ABSTRACT: Next-generation sequencing (NGS) technologies have provided great opportunities to analyze pathogenic microbes with high-resolution data. The main goal is to accurately detect microbial composition and abundances in a sample. However, high similarity among sequences from different species and the existence of sequencing errors pose various challenges. Numerous methods have been developed for quantifying microbial composition and abundance, but they are not versatile enough for the analysis of samples with mixtures of noise. In this paper, we propose a new computational method, PGMicroD, for the detection of pathogenic microbial composition in a sample using NGS data. The method first filters the potentially mistakenly mapped reads and extracts multiple species-related features from the seq

SUBMITTER: Zhao H 

PROVIDER: S-EPMC7734255 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature