A comprehensive bioinformatics toolkit for identifying synteny and structural variations between genomic sequences using SYRI and minimap2.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install syri-analysis
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install syri-analysis using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is SYRI Synteny Analysis?
This skill provides a high-performance workflow for SYRI (Synteny and Rearrangement Identifier), a powerful tool designed to find structural variations (SVs) and syntenic regions between two whole-genome assemblies. It streamlines the complex process of comparative genomics by integrating sequence alignment, data cleaning, and sophisticated visualization.
By leveraging the Openclaw Skills framework, researchers can automate the extraction of chromosomes, execute high-speed alignments with minimap2, and generate publication-ready plots using plotsr. It addresses common technical hurdles like CIGAR string formatting and output buffering, ensuring a reliable analysis pipeline for large-scale genomic data.
SYRI Synteny Analysis Use Cases
- Comparing two different genome assemblies to identify inversions, translocations, and duplications.
- Visualizing chromosome-level synteny for evolutionary biology research.
- Detecting large-scale structural variants (SVs) that are often missed by short-read sequencing.
- Renaming and reorienting chromosomes to standardize comparative genomic datasets.
How SYRI Synteny Analysis Works
- Extract and rename target chromosomes from FASTA files, applying reverse complements where necessary to align orientations.
- Generate chromosome length files (.len) for both reference and query genomes to define the genomic coordinate system.
- Perform high-speed sequence alignment using minimap2 with specific flags like --eqx to ensure compatibility with SYRI.
- Clean the resulting SAM files by removing log entries and filtering for high-quality mapping scores (MAPQ >= 20).
- Run the SYRI analysis engine to classify genomic regions into syntenic, inverted, or transposed blocks.
- Visualize the results using plotsr to create high-resolution synteny maps for specific chromosomes or the entire genome.
SYRI Synteny Analysis Setup
Prerequisites
Install the necessary bioinformatics tools via conda or pip:
# Install core alignment and analysis tools
conda install -c bioconda minimap2 syri plotsr
# Install Biopython for sequence processing
pip install biopython
Optimization Tip
For large genomes, set your thread count between 64 and 120 to significantly accelerate the minimap2 alignment phase.
SYRI Synteny Analysis Data Schema & Taxonomy
The skill generates a structured output directory containing various genomic feature files. Below is the primary metadata taxonomy:
| File | Description |
|---|---|
| syri.out | Main structural variation annotations (primary result) |
| syri.vcf | Results in VCF format for downstream variant analysis |
| synOut.txt | Coordinates of syntenic regions |
| invOut.txt | Coordinates of inversion events |
| TLOut.txt | Coordinates of translocation events |
| dupOut.txt | Coordinates of duplication events |
| snps.txt | Exact positions of identified SNPs |
Data organization within Openclaw Skills ensures that reference genomes, query genomes, and intermediate SAM files are tracked for reproducibility.
SYRI Synteny Analysis Advanced Features
- Buffer Management: Utilizes stdbuf to prevent 0-byte SAM file errors during long-running alignments.
- Automated Orientation: Python-based preprocessing scripts to automatically handle reverse complement adjustments for query sequences.
- High-Performance Computing: Optimized for multi-threaded environments (64-120 threads) to handle gigabase-scale assemblies.
- Custom Visualization: Granular control over plotsr parameters to adjust height, width, and specific chromosome filtering for publication-quality figures.
SKILL.md
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