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Omilayers: a Python package for efficient data management to support multi-omic analysis
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Journal Article
Omilayers: a Python package for efficient data management to support multi-omic analysis
2025
Overview
Multi-omic integration involves the management of diverse omic datasets. Conducting an effective analysis of these datasets necessitates a data management system that meets a specific set of requirements, such as rapid storage and retrieval of data with varying numbers of features and mixed data-types, ensurance of reliable and secure database transactions, extension of stored data row and column-wise and facilitation of data distribution. SQLite and DuckDB are embedded databases that fulfil these requirements. However, they utilize the structured query language (SQL) that hinders their implementation by the uninitiated user, and complicates their use in repetitive tasks due to the necessity of writing SQL queries. This study offers Omilayers, a Python package that encapsulates these two databases and exposes a subset of their functionality that is geared towards frequent and repetitive analytical procedures. Synthetic data were used to demonstrate the use of Omilayers and compare the performance of SQLite and DuckDB.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
/ Application programming interface
/ Big data management in biological domains
/ Biomedical and Life Sciences
/ Computational Biology - methods
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Data base management systems
/ Datasets
/ Information storage and retrieval
/ Methods
/ Python
/ Python (Programming language)
/ Software
/ Structured Query Language-SQL
/ Urine
