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Chapter 8: Clade-Specific Marker Profiling with MetaPhlAn 4

Tested Stacks: GATK 4.6.1 Samtools 1.21 Nextflow 24.10 Seurat v5.1 Python 3.12
Prerequisites: Basic Linux CLI & Sequencing Formats
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Chapter 8: Clade-Specific Marker Profiling with MetaPhlAn 4

While Kraken2 indexes entire genome assemblies, MetaPhlAn 4 profiles microbial communities using a curated catalog of ~5.1 million unique clade-specific single-copy marker genes. Because each marker belongs uniquely to a single microbial clade, read depth directly reflects relative cellular abundance without genome size bias.

Advantages of Marker-Gene Profiling
  • Extremely low false-positive rate compared to full-genome k-mer classifiers.
  • Directly estimates relative cell counts rather than DNA mass proportions.
  • Profiles bacteria, archaea, eukaryotic microbes, and viruses simultaneously.

1. Running MetaPhlAn 4

# Profile taxonomic composition using Bowtie2 marker mapping
metaphlan microbial_R1.fastq.gz,microbial_R2.fastq.gz \\
    --input_type fastq \\
    --bowtie2db /ref/metaphlan4_db/ \\
    --nproc 16 \\
    -o sample_profile.txt

# Merge profiles across multiple samples into a unified matrix
merge_metaphlan_tables.py sample1_profile.txt sample2_profile.txt > merged_abundance_table.txt
⚠️

Common Pitfalls & Troubleshooting Checklist

  • Java Heap Exhaustion (GATK / Picard): If processes terminate with java.lang.OutOfMemoryError, set your environment variable explicitly: export _JAVA_OPTIONS="-Xmx16g -Djava.io.tmpdir=/tmp".
  • Index Timestamp Mismatch: If tools complain that a BAM index is missing or out of date, regenerate with samtools index -@ 4 sample.bam.
  • Conda Channel Conflicts: Avoid ABI incompatibilities between bioconda and conda-forge by setting strict priority: conda config --set channel_priority strict.
  • Chromosome Naming Contamination: Always verify whether reference FASTA headers use chr1 or 1; divergent naming causes silent alignment drops.
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