MetaCHIP: community-level horizontal gene transfer identification through the combination of best-match and phylogenetic approaches.

ABSTRACT:

Background

Metagenomic datasets provide an opportunity to study horizontal gene transfer (HGT) on the level of a microbial community. However, current HGT detection methods cannot be applied to community-level datasets or require reference genomes. Here, we present MetaCHIP, a pipeline for reference-independent HGT identification at the community level.

Results

Assessment of MetaCHIP's performance on simulated datasets revealed that it can predict HGTs with various degrees of genetic divergence from metagenomic datasets. The results also indicated that the detection of very recent gene transfers (i.e. those with low levels of genetic divergence) from metagenomics datasets is largely affected by the read assembly step. Comparison of MetaCHIP with a previous analysis on soil b

SUBMITTER: Song W 

PROVIDER: S-EPMC6399960 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature