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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




SciLifeLab acknowledgement

  • Bioinformatics platform (NBIS)