Benchmarking short-read metagenomics tools for removing host contamination.

ABSTRACT:

Background

The rapid evolution of metagenomic sequencing technology offers remarkable opportunities to explore the intricate roles of microbiome in host health and disease, as well as to uncover the unknown structure and functions of microbial communities. However, the swift accumulation of metagenomic data poses substantial challenges for data analysis. Contamination from host DNA can substantially compromise result accuracy and increase additional computational resources by including nontarget sequences.

Results

In this study, we assessed the impact of computational host DNA decontamination on downstream analyses, highlighting its importance in producing accurate results efficiently. We also evaluated the performance of conventional tools like KneadData, Bowtie2, BWA, KMCP

SUBMITTER: Gao Y 

PROVIDER: S-EPMC11878760 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature