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

aMeta is a Snakemake workflow for identifying microbial sequences in ancient DNA shotgun metagenomics samples. The workflow performs:

• trimming adapter sequences and removing reads shorter than 30 bp with Cutadapt
• quality control before and after trimming with FastQC and MultiQC
• taxonomic sequence kmer-based classification with KrakenUniq
• sequence alignment with Bowtie2 and screening for common microbial pathogens
• deamination pattern analysis with MapDamage2
• Lowest Common Ancestor (LCA) sequence alignment with Malt
• authentication and validation of identified microbial species with MaltExtract