MetaPhlAn 4 Profiling
MetaPhlAn 4 uses ~5M clade-specific markers from 26,970 species-level genome bins. Supports both short reads (bowtie2) and long reads (minimap2).
Basic Profiling
bash
# Profile single sample
metaphlan sample.fastq.gz \
--input_type fastq \
--output_file profile.txt
Paired-End Reads
bash
# MetaPhlAn processes PE as single file or concatenated
metaphlan reads_R1.fastq.gz,reads_R2.fastq.gz \
--input_type fastq \
--output_file profile.txt \
--mapout sample.map.bz2
Save Mapping Output for Reuse (MetaPhlAn 4.2+)
bash
# First run - save intermediate mapping
metaphlan sample.fastq.gz \
--input_type fastq \
--mapout sample.map.bz2 \
--output_file profile.txt
# Rerun with different settings without realigning
metaphlan sample.map.bz2 \
--input_type mapout \
--output_file profile_v2.txt
Long-Read Support (MetaPhlAn 4+)
bash
# Long reads automatically use minimap2 instead of bowtie2
metaphlan long_reads.fastq.gz \
--input_type fastq \
--output_file profile.txt
Common Options
bash
metaphlan sample.fastq.gz \
--input_type fastq \
--nproc 8 \ # CPU threads
--tax_lev s \ # Taxonomic level (k,p,c,o,f,g,s,t)
--min_cu_len 2000 \ # Min total nucleotide length
--stat_q 0.2 \ # Quantile for robust average
--output_file profile.txt \
--mapout sample.map.bz2
Install Database
bash
# Download database (done automatically on first run) metaphlan --install # Or specify database location (MetaPhlAn 4.2+) metaphlan --install --db_dir /path/to/db
Analysis Types
bash
# Relative abundances (default) metaphlan sample.fastq.gz --input_type fastq -t rel_ab # Relative abundances with read counts metaphlan sample.fastq.gz --input_type fastq -t rel_ab_w_read_stats # Marker presence/absence metaphlan sample.fastq.gz --input_type fastq -t marker_pres_table # Marker abundances metaphlan sample.fastq.gz --input_type fastq -t marker_ab_table
Multiple Samples
bash
# Process each sample
for fq in samples/*.fastq.gz; do
sample=$(basename $fq .fastq.gz)
metaphlan $fq \
--input_type fastq \
--nproc 4 \
--output_file profiles/${sample}_profile.txt \
--mapout mapout/${sample}.map.bz2
done
# Merge profiles
merge_metaphlan_tables.py profiles/*_profile.txt > merged_abundance.txt
Filter by Taxonomic Level
bash
# Species only metaphlan sample.fastq.gz --input_type fastq --tax_lev s -o species.txt # Genus only metaphlan sample.fastq.gz --input_type fastq --tax_lev g -o genus.txt # All levels (default) metaphlan sample.fastq.gz --input_type fastq --tax_lev a -o all_levels.txt
Output Format
code
#SampleID sample #clade_name relative_abundance k__Bacteria 100.0 k__Bacteria|p__Proteobacteria 65.23 k__Bacteria|p__Proteobacteria|c__Gammaproteobacteria 62.15 k__Bacteria|p__Proteobacteria|c__Gammaproteobacteria|o__Enterobacterales 58.42 k__Bacteria|p__Proteobacteria|c__Gammaproteobacteria|o__Enterobacterales|f__Enterobacteriaceae 55.21 k__Bacteria|p__Proteobacteria|c__Gammaproteobacteria|o__Enterobacterales|f__Enterobacteriaceae|g__Escherichia 52.33 k__Bacteria|p__Proteobacteria|c__Gammaproteobacteria|o__Enterobacterales|f__Enterobacteriaceae|g__Escherichia|s__Escherichia_coli 52.33
Parse Output in Python
python
import pandas as pd
profile = pd.read_csv('profile.txt', sep='\t', comment='#', header=None,
names=['clade', 'abundance'])
species = profile[profile['clade'].str.contains('\\|s__')]
species['species'] = species['clade'].str.split('|').str[-1].str.replace('s__', '')
species.sort_values('abundance', ascending=False).head(20)
Extract SGBs (Strain-level)
bash
# Include strain-level genomic bins
metaphlan sample.fastq.gz \
--input_type fastq \
--tax_lev t \ # Include t__ level (SGBs)
--output_file profile_with_sgb.txt
Sample Metadata in Output
bash
# Add sample ID to output
metaphlan sample.fastq.gz \
--input_type fastq \
--sample_id sample_name \
--output_file profile.txt
Key Parameters (MetaPhlAn 4.2+)
| Parameter | Default | Description |
|---|---|---|
| --input_type | fastq | Input format (fastq, mapout) |
| --nproc | 4 | CPU threads |
| --tax_lev | a | Taxonomic level (a=all) |
| --stat_q | 0.2 | Quantile value |
| --min_cu_len | 2000 | Min clade length |
| -t | rel_ab | Analysis type |
| --mapout | none | Save mapping output |
| --db_dir | default | Database directory |
Note: Unknown species estimation is now enabled by default in MetaPhlAn 4.2+
Analysis Types (-t)
| Type | Description |
|---|---|
| rel_ab | Relative abundances (%) |
| rel_ab_w_read_stats | With read statistics |
| marker_pres_table | Marker presence/absence |
| marker_ab_table | Marker abundances |
| clade_specific_strain_tracker | Strain tracking |
Related Skills
- •kraken-classification - Alternative k-mer based classification
- •abundance-estimation - Bracken for Kraken2 abundances
- •metagenome-visualization - Visualize profiles