aMeta: an accurate and memory-efficient ancient metagenomic profiling workflow
Pochon Z, Bergfeldt N, Kırdök E, Vicente M, Naidoo T, van der Valk T, Altınışık NE, Krzewińska M, Dalén L, Götherström A, Mirabello C, Unneberg P, Oskolkov N.
Abstract
Analysis of microbial data from archaeological samples is a growing field with great potential for understanding ancient environments, lifestyles, and diseases. However, high error rates have been a challenge in ancient metagenomics, and the availability of computational frameworks that meet the demands of the field is limited. Here, we propose aMeta, an accurate metagenomic profiling workflow for ancient DNA designed to minimize the amount of false discoveries and computer memory requirements. Using simulated data, we benchmark aMeta against a current state-of-the-art workflow and demonstrate its superiority in microbial detection and authentication, as well as substantially lower usage of computer memory. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-023-03083-9. Keywords: Ancient metagenomics, Pathogen detection, Microbiome profiling, Ancient DNA
This page indexes the study's public bibliographic record. The full text belongs to the journal; follow the DOI above to read it at the source.