Journal Article

aMeta: an accurate and memory-efficient ancient metagenomic profiling workflow

Vicente, Mário, Unneberg, Per, Bergfeldt, Nora, Naidoo, Thijessen, Kırdök, Emrah, Götherström, Anders, Oskolkov, Nikolay, Krzewińska, Maja, van der Valk, Tom, Dalén, Love, Pochon, Zoé, Altınışık, N. Ezgi, Mirabello, Claudio

2023

Overview

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.

• Publisher: BioMed Central,Springer Nature B.V,BMC
• Subject: Ancient DNA / Ancient metagenomics / Animal Genetics and Genomics / archaeology / Bioinformatics / Bioinformatics (Computational Biology) / Bioinformatik (Beräkningsbiologi) / Biomedical and Life Sciences / Classification / Computer and Information Sciences / computer hardware / Data- och informationsvetenskap (Datateknik) / DNA / DNA fingerprinting / Evolutionary Biology / genome / Genomes / Human Genetics / Life Sciences / Metagenomics / Method / microbial detection / Microbial Genetics and Genomics / Microbiome profiling / Natural Sciences / Naturvetenskap / Pathogen detection / Plant Genetics and Genomics / Taxonomy