Automated Bioinformatics Analysis via AutoBA

TL;DR

AutoBA is an autonomous AI tool based on large language models that simplifies and adapts complex omics data analysis processes with minimal user input, ensuring robustness, versatility, and data privacy.

Contribution

This paper introduces AutoBA, a novel AI agent that autonomously designs and executes bioinformatics analysis pipelines tailored to diverse omics data types.

Findings

Validated across multiple omics data types including WGS, RNA-seq, and spatial transcriptomics.

Demonstrates robustness and adaptability confirmed by expert bioinformaticians.

Operates locally to ensure data privacy and integrates emerging bioinformatics tools.

Abstract

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle the analysis continues to grow. In response to this need, we introduce Auto Bioinformatics Analysis (AutoBA), an autonomous AI agent based on a large language model designed explicitly for conventional omics data analysis. AutoBA simplifies the analytical process by requiring minimal user input while delivering detailed step-by-step plans for various bioinformatics tasks. Through rigorous validation by expert bioinformaticians, AutoBA's robustness and adaptability are affirmed across a diverse range of omics analysis cases, including whole genome sequencing (WGS), RNA sequencing (RNA-seq), single-cell RNA-seq, ChIP-seq, and spatial transcriptomics. AutoBA's unique capacity to self-design analysis processes based on input data variations further underscores its versatility. Compared with online bioinformatic services, AutoBA deploys the analysis locally, preserving data privacy. Moreover, different from the predefined pipeline, AutoBA has adaptability in sync with emerging bioinformatics tools. Overall, AutoBA represents a convenient tool, offering robustness and adaptability for complex omics data analysis.