sql/README.md

SQLite Metadata System for Plant-mSyn

This directory contains the SQLite-based metadata system for efficient gene searches across multi-genome synteny comparisons.

Overview

The metadata system consists of two types of databases:

1. Central Metadata Database (plantmsyn_metadata.db)

   • Stores genome registry, comparison runs, and file manifests
   • Enables quick lookup of which comparison files exist for any genome pair
   • Tracks custom genome uploads and their expiration dates

2. Per-Genome Search Catalogs (search_catalogs/<genome>.catalog.sqlite)

   • One catalog per query genome
   • Maps gene IDs to target genomes where matches exist
   • Enables O(1) lookup: "For gene X in genome A, which target genomes have hits?"

Why This System?

Without an index, searching for a gene requires scanning ~200 comparison files to find matches. This is fast locally but slow in cloud environments with network-based storage.

With the catalog system:

1. Look up the gene in the query genome's catalog → get list of target genomes with matches
2. Fetch only those specific comparison files
3. Extract the full match rows

This reduces file reads from ~200 to typically ~5-10 per search.

Directory Structure

sql/
├── README.md                           # This file
├── plantmsyn_metadata.db              # Central metadata database
├── search_catalogs/                   # Per-genome search catalogs
│   ├── arabidopsis_thaliana.catalog.sqlite
│   ├── glycine_max.catalog.sqlite
│   └── ...
└── test_sqlite_metadata.py            # Validation test script

Building the Databases

First-time build

cd /path/to/Multi-genomes\ synteny/Scripts
python build_sqlite_metadata.py

Rebuild from scratch

python build_sqlite_metadata.py --rebuild

Clean up expired custom genomes

python build_sqlite_metadata.py --cleanup-expired

Options

Option	Description
--rebuild, -r	Drop and rebuild all databases from scratch
--cleanup-expired, -c	Remove metadata for expired custom genomes (2-week expiry)
--version VERSION	Dataset version string (default: v1)
--verbose, -v	Enable debug logging

Testing

Run the validation tests to ensure the metadata system is working correctly:

cd /path/to/Multi-genomes\ synteny/sql
python test_sqlite_metadata.py

The tests verify:

• Database tables exist and have correct schema
• Genome counts match filesystem
• Comparison runs are properly linked
• File manifests point to existing files
• Search catalogs are queryable
• Gene lookups return valid results
• Cross-validation against actual .last.filtered files

Database Schemas

Central Database Tables

genome

Column	Type	Description
genome_id	INTEGER	Primary key
genome_name	TEXT	Unique identifier (e.g., arabidopsis_thaliana)
display_name	TEXT	Human-readable name
is_custom	INTEGER	1 if custom upload, 0 if database genome
created_at	TEXT	ISO timestamp
expires_at	TEXT	Expiration date for custom genomes
gene_count	INTEGER	Number of genes
protein_count	INTEGER	Number of proteins

comparison_run

Column	Type	Description
run_id	INTEGER	Primary key
query_genome_id	INTEGER	FK → genome
target_genome_id	INTEGER	FK → genome
dataset_version	TEXT	Version string (e.g., v1)
created_at	TEXT	ISO timestamp
status	TEXT	completed, failed, or pending

run_file

Column	Type	Description
run_id	INTEGER	FK → comparison_run
file_kind	TEXT	i1.blocks, last.filtered, lifted.anchors, etc.
file_path	TEXT	Relative path from MCSCAN_RESULTS_DIR
file_bytes	INTEGER	File size
file_checksum	TEXT	MD5 hash
created_at	TEXT	ISO timestamp

search_catalog

Column	Type	Description
dataset_version	TEXT	Version string
query_genome_id	INTEGER	FK → genome
catalog_path	TEXT	Relative path to catalog file
catalog_bytes	INTEGER	Catalog file size
catalog_checksum	TEXT	MD5 hash
created_at	TEXT	ISO timestamp

Per-Genome Catalog Tables

gene_to_run

Column	Type	Description
query_gene_id	TEXT	Gene identifier
target_genome_name	TEXT	Target genome where matches exist
run_id	INTEGER	Reference to comparison_run
hit_count	INTEGER	Number of matches for this gene
best_identity	REAL	Highest identity score

File Directionality

• .i1.blocks files: Directional. A.B.i1.blocks means query=A, target=B. Both A→B and B→A are stored as separate comparison runs.
• .last.filtered files: Contain matches in both directions. The same file is associated with both A→B and B→A runs.
• .lifted.anchors files: Similar to last.filtered, contain both directions.

Example Usage

Query gene targets from catalog

import sqlite3
from path_config import SEARCH_CATALOGS_DIR

genome = "arabidopsis_thaliana"
gene_id = "AT1G01010"

conn = sqlite3.connect(SEARCH_CATALOGS_DIR / f"{genome}.catalog.sqlite")
cursor = conn.execute("""
    SELECT target_genome_name, hit_count, best_identity
    FROM gene_to_run
    WHERE query_gene_id = ?
""", (gene_id,))

for row in cursor:
    print(f"  {row[0]}: {row[1]} hits, best identity {row[2]:.1f}%")

Get comparison files for a genome pair

import sqlite3
from path_config import METADATA_DB_PATH, MCSCAN_RESULTS_DIR

conn = sqlite3.connect(METADATA_DB_PATH)
cursor = conn.execute("""
    SELECT rf.file_kind, rf.file_path
    FROM run_file rf
    JOIN comparison_run cr ON rf.run_id = cr.run_id
    JOIN genome gq ON cr.query_genome_id = gq.genome_id
    JOIN genome gt ON cr.target_genome_id = gt.genome_id
    WHERE gq.genome_name = ? AND gt.genome_name = ?
""", ("arabidopsis_thaliana", "glycine_max"))

for row in cursor:
    full_path = MCSCAN_RESULTS_DIR / row[1]
    print(f"  {row[0]}: {full_path}")

Custom Genome Lifecycle

Custom genomes uploaded by users expire after 2 weeks. The expiration date is stored in genome.expires_at.

To clean up expired genomes:

python build_sqlite_metadata.py --cleanup-expired

This removes:

• Genome entry from genome table
• Associated comparison runs from comparison_run table
• File manifest entries from run_file table
• Search catalog entry from search_catalog table
• The actual catalog file from search_catalogs/

Versioning

The system supports multiple dataset versions via the dataset_version column. This allows running the pipeline with different parameters and storing results side-by-side.

Default version: v1

To build with a different version:

python build_sqlite_metadata.py --version v2

Troubleshooting

"No comparison runs found"

• Check that Mcscan_results/protein_pairwise/i1_blocks/ contains .i1.blocks files
• Run with --verbose to see detailed discovery logs

"Catalog not found for genome X"

• The genome may not have any outgoing comparisons
• Check if BED file exists in bed_files/

"Gene lookup returns no results"

• Verify the gene ID format matches what's in the BED file
• Check if the genome has been processed (has comparisons)

Integration Notes

The metadata system is designed to work alongside existing scripts without modification:

• Existing scripts continue to work by scanning files directly
• New/updated scripts can optionally use the metadata system for faster lookups
• The path_config.py module provides SQL_DIR, SEARCH_CATALOGS_DIR, and METADATA_DB_PATH constants

For cloud deployment, the SQLite files can be stored in S3 and downloaded/cached locally as needed.