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

Genome Biol. 24 (1) 242 [2023-10-23; online 2023-10-23]

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.

Ancient DNA [Technology development]

Bioinformatics Long-term Support WABI [Collaborative]

Bioinformatics Support, Infrastructure and Training [Collaborative]

PubMed 37872569

DOI 10.1186/s13059-023-03083-9

Crossref 10.1186/s13059-023-03083-9

pmc: PMC10591440
pii: 10.1186/s13059-023-03083-9

Publications 9.5.0