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
📚 Chapter 8 of 13
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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
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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 - Index Timestamp Mismatch: If tools complain that a BAM index is missing or out of date, regenerate with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
chr1or1; divergent naming causes silent alignment drops.
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