SRAmetadb Export

Export the SRAKE database to the classic SRAmetadb.sqlite format for use with existing bioinformatics tools.

Basic usage

# Export with FTS5 (recommended)
srake db export -o SRAmetadb.sqlite

# Export with FTS3 for legacy tool compatibility
srake db export -o SRAmetadb.sqlite --fts-version 3

Options

Flag	Default	Description
`-o, --output`	SRAmetadb.sqlite	Output file path
`--db`	auto-detected	Source database path
`--fts-version`	5	FTS version (3 or 5)
`--batch-size`	10000	Records per batch
`--compress`	false	Gzip compress output
`-f, --force`	false	Overwrite existing file

Output schema

The exported database contains:

Table	Description
`study`	Research studies
`experiment`	Sequencing experiments
`sample`	Biological samples
`run`	Sequencing runs
`submission`	Data submissions
`sra`	Denormalized join of all tables
`sra_ft`	Full-text search virtual table (FTS3 or FTS5)
`metaInfo`	Version and creation metadata
`col_desc`	Column descriptions

FTS version choice

FTS5 (default): Faster queries, smaller index, better Unicode support. Use for new projects.

FTS3: Use when tools specifically require FTS3 (e.g., older R/Bioconductor SRAdb package).

FTS5 support requires building SRAKE with the sqlite_fts5 build tag.

Usage with R

library(DBI)
con <- dbConnect(RSQLite::SQLite(), "SRAmetadb.sqlite")
dbGetQuery(con, "SELECT * FROM study WHERE organism = 'Homo sapiens' LIMIT 10")
dbGetQuery(con, "SELECT * FROM sra_ft WHERE sra_ft MATCH 'cancer AND RNA-Seq'")

Usage with Python

import sqlite3
import pandas as pd

conn = sqlite3.connect("SRAmetadb.sqlite")
df = pd.read_sql("SELECT * FROM study WHERE organism = 'Homo sapiens'", conn)

Schema mapping

The export handles these transformations:

JSON arrays to pipe-delimited strings (["A","B"] to A|B)
Nested metadata flattened to columns
Missing legacy fields populated with defaults
SRA/Entrez URLs generated automatically