mkrg01/genome_assembly_pipeline

An integrated pipeline for eukaryotic genome assembly and gene annotation

Overview

Latest release: None, Last update: 2026-04-22

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=mkrg01/genome_assembly_pipeline

Quality control: linting: passed formatting: failed

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Conda package manager. It is recommended to install conda via Miniforge. Run

conda create -c conda-forge -c bioconda -c nodefaults --name snakemake snakemake snakedeploy

to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via

conda activate snakemake

For other installation methods, refer to the Snakemake and Snakedeploy documentation.

Step 2: Deploy workflow

With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:

mkdir -p path/to/project-workdir
cd path/to/project-workdir

In all following steps, we will assume that you are inside of that directory. Then run

snakedeploy deploy-workflow https://github.com/mkrg01/genome_assembly_pipeline . --tag None

Snakedeploy will create two folders, workflow and config. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.

Step 3: Configure workflow

To configure the workflow, adapt config/config.yml to your needs following the instructions below.

Step 4: Run workflow

The deployment method is controlled using the --software-deployment-method (short --sdm) argument.

To run the workflow using a combination of conda and apptainer/singularity for software deployment, use

snakemake --cores all --sdm conda apptainer

Snakemake will automatically detect the main Snakefile in the workflow subfolder and execute the workflow module that has been defined by the deployment in step 2.

For further options such as cluster and cloud execution, see the docs.

Step 5: Generate report

After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using

snakemake --report report.zip

Configuration

The following section is imported from the workflow’s config/README.md.

Configuration Guide

This document explains:

  1. Required input files to be placed in the raw_data directory.

  2. Configuration parameters to set in config/config.yml.

1. Input Files (raw_data/)

The pipeline requires PacBio HiFi reads. Paired-end RNA-seq reads are required when running targets that include gene prediction (gene_prediction_all, circos_plot_all, or all).

Place your raw sequencing files in the raw_data directory with the following naming conventions:

File Type

Naming Pattern

Example

PacBio HiFi reads

*.hifi_reads.bam

SAMPLE1.hifi_reads.bam

Index for HiFi reads

*.hifi_reads.bam.pbi

SAMPLE1.hifi_reads.bam.pbi

Ultra-long ONT reads (optional)

Any FASTQ path in config (.fastq.gz, .fq.gz, .fastq, .fq)

raw_data/ont_reads.fastq.gz

Hi-C reads R1 (optional)

One or more FASTQ paths in hic_reads_r1 (.fastq.gz, .fq.gz, .fastq, .fq)

raw_data/hic_R1.fastq.gz

Hi-C reads R2 (optional)

One or more FASTQ paths in hic_reads_r2 (.fastq.gz, .fq.gz, .fastq, .fq)

raw_data/hic_R2.fastq.gz

Paired-end RNA-seq (R1)

*_1.fastq.gz, *_1.fq.gz, *_1.fastq, or *_1.fq

RNASEQ1_1.fastq.gz

Paired-end RNA-seq (R2)

*_2.fastq.gz, *_2.fq.gz, *_2.fastq, or *_2.fq

RNASEQ1_2.fastq.gz

Notes:

  • The pipeline will automatically detect and process multiple PacBio HiFi and RNA-seq samples, if present.

  • RNA-seq raw FASTQ inputs can be gzipped or plain text. The pipeline normalizes them during preprocessing, so downstream rules keep using the same internal filenames.

  • Keep only one raw RNA-seq file per sample and read pair. For example, do not place both SAMPLE_1.fastq.gz and SAMPLE_1.fq in raw_data/.

  • Ultra-long ONT reads are optional and can improve assembly quality when integrated with HiFi reads. See the hifiasm documentation for details.

  • Hi-C reads are optional and should be provided as matching R1/R2 paths in hic_reads_r1 and hic_reads_r2. Multiple lanes can be listed in matching order. If Hi-C reads are configured, the pipeline uses them for hifiasm phasing, runs YaHS scaffolding on each assembly listed in selected_assemblies, and prepares Juicebox-ready contact maps. See the hifiasm documentation and the YaHS documentation for details.

2. Configuration File (config/config.yml)

Edit config/config.yml to match your dataset and analysis requirements.
Below are the available parameters:

Parameter

Description

Example

assembly_name

Name used for output files

"Dioncophyllum_thollonii"

assembly_version

Version used for output files

"v1.0"

selected_assemblies

One or more assemblies to process after hifiasm. Allowed values: {"primary", "hap1", "hap2"}. Downstream outputs are written under assembly-specific subdirectories such as results/fcs/assembly/<selected_assembly>/... or results/submission/<selected_assembly>/.... When Hi-C integration is enabled, these correspond to hifiasm hic.p_ctg, hic.hap1.p_ctg, and hic.hap2.p_ctg outputs, which are then scaffolded with YaHS, exported as Juicebox-ready contact-map files under results/juicebox/<selected_assembly>/..., and written under results/yahs/assembly/<selected_assembly>/... before RepeatMasker and later steps. Organelle submission assets are staged separately under results/submission/organelle/... according to oatk_organelle.

["primary", "hap1", "hap2"]

submission_assemblies

One or more assemblies to package for submission. Must be a subset of selected_assemblies.

["primary"]

hifiasm_dual_scaf

Optional: Enable hifiasm self-scaffolding by adding --dual-scaf. {true, false}

false

ont_reads

Optional: Path to ultra-long ONT reads in FASTQ format (.fastq.gz, .fq.gz, .fastq, or .fq). Set to null to disable ONT integration. See hifiasm docs

null

hic_reads_r1

Optional: Hi-C read 1 input for hifiasm phasing, YaHS scaffolding, and Juicebox-ready contact maps. Set to null to disable Hi-C integration, or provide one or more FASTQ paths as a YAML list. Must be paired with hic_reads_r2. See hifiasm docs

["raw_data/hic_R1.fastq.gz"]

hic_reads_r2

Optional: Hi-C read 2 input for hifiasm phasing, YaHS scaffolding, and Juicebox-ready contact maps. Must match hic_reads_r1 in length and order.

["raw_data/hic_R2.fastq.gz"]

yahs_restriction_enzymes

Optional: Restriction enzyme motif(s) passed to YaHS with -e during Hi-C scaffolding. Set to null to use YaHS defaults. See YaHS docs

"GATC"

oatk_lineage

Lineage of the Oatk HMM profile database. Lineage list

"magnoliopsida"

oatk_organelle

Organelle to assemble. {"mito", "pltd", "mito_and_pltd"}

"mito_and_pltd"

oatk_minimum_kmer_coverage

Minimum kmer coverage used for Oatk. Instructions

"250"

fcs_gx_taxid

NCBI Taxonomy ID for FCS-GX screening. NCBI Taxonomy Tree

"122299" for Dioncophyllum thollonii

busco_lineage_dataset

BUSCO lineage dataset for genome completeness assessment. Lineage list

"embryophyta_odb12"

tidk_clade

Clade for tidk find. Lineage list

"Caryophyllales"

tidk_telomeric_repeat_unit

A telomeric repeat unit for tidk search. A Telomeric Repeat Database

"AAACCCT"

dfam_version

Version of the Dfam database for RepeatMasker. Dfam releases

"3.9"

dfam_partitions

Dfam partitions. See README.txt.

"0,5,6" (Viridiplantae)

dfam_lineage_name

Name of the Dfam lineage to use.

"Viridiplantae"

orthodb_version

Version of the OrthoDB database (used by Braker3). ProtHint instructions

"12"

orthodb_lineage

OrthoDB lineage dataset to use. Lineage list

"Viridiplantae"

orthodb_md5sum

MD5 checksum of the OrthoDB database. Checksums

"34c1f027a1a7b10f225b69fbd5500587"

min_long_contig_length

Minimum contig length to be considered a “long contig” for downstream visualization (e.g., Circos plots).

1_000_000

circos_plot_tracks

Track configuration for the Circos plot

{id: "gene", label: "Gene model", color: "#4C72B0", window_size: 500_000}

circos_plot_x_major_tick_interval

Major tick interval (in bp) for the x-axis in Circos plots. Major ticks are labeled.

10_000_000

circos_plot_x_minor_tick_interval

Minor tick interval (in bp) for the x-axis in Circos plots. Minor ticks are unlabeled.

5_000_000

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