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NeurIPS 2025 · Poster

scPilot: Large Language Model Reasoning Toward Automated Single-Cell Analysis and Discovery

Yiming Gao, Zhen Wang, Jefferson Chen, Mark Antkowiak, Mengzhou Hu, JungHo Kong, Dexter Pratt, Jieyuan Liu, Enze Ma, Zhiting Hu, Eric P. Xing

Overview

scPilot brings iterative, data-grounded reasoning to single-cell RNA-seq analysis. An LLM inspects data, invokes bioinformatics tools, explains its hypotheses, and revises them as new evidence becomes available. The framework covers cell-type annotation, developmental trajectories, and transcription-factor targeting.

The accompanying scBench evaluates these capabilities across nine curated datasets. The paper reports an 11% average annotation accuracy improvement with o1 and a 30% reduction in trajectory graph-edit distance with Gemini 2.5 Pro relative to one-shot prompting.

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