flowmeta 0.1.1

Integrated metagenomic workflow orchestration

FlowMeta: Automated End-to-End Metagenomic Profiling Pipeline 🚀

FlowMeta packages a 10-step, end-to-end metagenomic workflow into a single Python command that can be deployed on any Linux/WSL environment. Each processing phase writes *.task.complete flags so you can resume or re-run individual stages with confidence across microbiome, environmental, or any shotgun metagenomic study.

✨ Highlights

• End-to-end orchestration (flowmeta_base) covering fastp ➜ Bowtie2 ➜ Kraken2/Bracken ➜ host-taxid filtering ➜ final OTU/MPA matrix merge.
• Smart checkpointing with .task.complete for incremental runs.
• Shared-memory (optional) caching for Kraken2 databases.
• Configurable project prefix (e.g. SMOOTH-) applied to Step 6 outputs.
• Detailed per-step logs stored alongside generated data.

📦 Installation

conda create -n flowmeta python=3.8 -y
conda activate flowmeta  # or any Python >= 3.8 environment
# Dependance
conda install -c bioconda fastp bowtie2 samtools kraken2 bracken -y
conda install -c conda-forge scipy pandas -y

# Install from PyPi: https://pypi.org/project/flowmeta/0.1.0/
pip install flowmeta

# Validate the installation
flowmeta_base -h

Tip: the auxiliary YAML file environment.yml captures the recommended Conda environment, including Python, pandas/numpy, and the build toolchain. Alternative setup paths (Conda, mamba, pip) are described in docs/tutorial.html so you can pick the package manager that matches your infrastructure. When using an internal build, install the local wheel via pip install dist/flowmeta-0.1.0-py3-none-any.whl.

🏁 Quick Start

flowmeta_base \
    --input_dir /mnt/data/01-raw \
    --output_dir /mnt/data/flowmeta-out \
    --db_bowtie2 /mnt/db/GRCh38_noalt_as/GRCh38_noalt_as \
    --db_kraken /mnt/db/k2ppf \
    --threads 8 \
    --project_prefix SMOOTH-

All downstream folders (02-qc … 09-mpa) are created automatically inside --output_dir. Existing results are reused unless --force is specified.

🧭 CLI Cheatsheet

Flag	Description
--input_dir	Directory containing raw FASTQ files (defaults to paired _1.fastq.gz/_2.fastq.gz).
--output_dir	Target workspace; the pipeline creates 02-qc … 09-mpa here.
--db_bowtie2	Path prefix of the host Bowtie2 index.
--db_kraken	Kraken2 database directory (must include hash.k2d, opts.k2d, taxo.k2d).
--threads	Worker threads per sample.
--batch	Number of samples processed in parallel (fastp/Kraken).
--min_count	Bracken minimum count threshold during host-taxid filtering (Step 5).
--project_prefix	Optional label prepended to Step 6 merged assets (e.g. SMOOTH-).
--force	Recompute even if .task.complete exists for the step.
--step	Resume from a specific logical step (1–10). Leave unset to run the entire workflow.
--skip_host_extract	Skip samtools-based host FASTQ extraction (Step 3).
--no_shm/--shm_path	Control Kraken2 shared-memory caching.

Full parameter descriptions and advanced scenarios are documented in docs/tutorial.html.

🔟 Step Map & Resuming

Use --step N to start from the desired checkpoint (defaults to --step 1, i.e. run everything). The CLI prints a per-step banner that includes the task description and how many samples/files are ready. --force can be combined with any step to ignore existing .task.complete markers.

Step	Purpose	Files counted when announced
1	fastp trimming and QC reporting.	FASTQ pairs in 01-raw matching suffix1.
2	fastp integrity verification.	.task.complete (or _fastp.json) in 02-qc.
3	Bowtie2 host depletion (FASTQ + BAM generation).	.task.complete in 02-qc.
4	Host-removed FASTQ integrity check.	_host_remove_R1.fastq.gz in 03-hr.
5	Optional samtools host-read export.	.bam in 04-bam.
6	Stage Kraken2 DB to shared memory (--no_shm disables).	N/A.
7	Kraken2/Bracken classification.	_host_remove_R1.fastq.gz in 03-hr.
8	Kraken report validation.	.kraken.report.std.txt in 06-ku.
9	Remove host taxa + rerun Bracken.	.kraken.report.std.txt in 06-ku.
10	Merge OTU/MPA/Bracken matrices.	.nohuman.kraken.mpa.std.txt (08-ku2) + .bracken tables (07-bracken).

Kraken2 Reference Databases

• 🔗 Download pre-built Kraken2 libraries directly from the official mirror: https://benlangmead.github.io/aws-indexes/k2
• 📦 After downloading, extract the archive and point --db_kraken to the directory containing hash.k2d, opts.k2d, and taxo.k2d.
• 💾 Consider staging the database on fast SSD or RAM disk when processing large cohorts.

Bowtie2 Host Reference (Human Example)

1. 📥 Fetch the GRCh38 primary assembly FASTA from the NCBI FTP mirror:

   wget https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.28_GRCh38.p13/GCA_000001405.28_GRCh38.p13_genomic.fna.gz
   gunzip GCA_000001405.28_GRCh38.p13_genomic.fna.gz
   

2. 🧹 Optionally remove alternative contigs if you prefer the noalt subset:

   seqkit grep -rvp 'alt|PATCH' GCA_000001405.28_GRCh38.p13_genomic.fna > GRCh38_noalt.fna
   

3. 🧱 Build the Bowtie2 index:

   bowtie2-build GRCh38_noalt.fna GRCh38_noalt_as/GRCh38_noalt_as
   

4. 📁 Supply the resulting prefix directory to --db_bowtie2 (e.g. --db_bowtie2 /mnt/db/GRCh38_noalt_as/GRCh38_noalt_as).

📂 Output Layout

01-raw/           # user-supplied FASTQ (read-only)
02-qc/            # fastp outputs + integrity checks
03-hr/            # host-removed FASTQ
04-bam/           # Bowtie2 BAM/indices
05-host/          # optional host reads (samtools)
06-ku/            # Kraken2 reports/outputs
07-bracken/       # Bracken abundance tables
08-ku2/           # Host-filtered rerun (reports + diversity metrics)
09-mpa/           # Merge matrices, count tables, final summaries

Every folder contains per-sample *.task.complete markers to enable resumable runs.

📚 Documentation

• Companion README (operations cheat sheet): README.zh.md
• HTML tutorial: docs/tutorial.html
• Quick validation script: docs/quickstart.md

🤝 Support

For bug reports or integration questions please reach out directly:

Dongqiang Zeng · 📧 [e-mail]

GitHub project: https://github.com/SkinMicrobe/FlowMeta