bioRxivBioinformaticsPreprint
NanoCortex: A Unified Agentic System for Nanopore Sequencing Analysis
Qini Xia, Ziyuan Wang, Mina Shokoufandeh, Sara H. RouhanifardiD, Meni WanunuiD
Abstract
Nanopore sequencing has enabled various layers of information about DNA and RNA sequence isoforms and chemical modifications. Yet, the archipelago of disjoint nanopore analysis tools makes navigating among these a significant challenge for the nanopore user. We present NanoCortex, a unified autonomous agentic framework designed to bridge this shortcoming by providing end-to-end data processing which ranges from raw signal basecalling to biological interpretation. Built upon Gemini API services that incur usage-based API costs and orchestrated through the Gemini Agent Development Kit (ADK), the system utilizes a multi-agent architecture to autonomously perform task parsing, code generation, iterative code-level self-correction of code, and scientific interpretation. Following code generation, the code can be used offline. Benchmarking reveals that NanoCortex achieves significantly higher usability across complex analytical tasks compared to general-purpose large language models. The framework seamlessly integrates experimental data with meta-analysis of publicly available, biological databases to facilitate the extraction of biologically meaningful insights from sequencing data without cumbersome computational steps.
- assay: whole-genome sequencing
- assay: long-read sequencing
- research focus: benchmarking
- research focus: software / tool
- approach: deep learning
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 0
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