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bioRxiv · 10.1101/2025.04.22.650107

SCassist: An AI Based Workflow Assistant for Single-Cell Analysis

Nagarajan, V.·Shi, G.·Arunkumar, S.·Liu, C.·Gopalakrishnan, J.·Nath, P. R.·Jang, J.·Caspi, R.
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Abstract

SummarySingle-cell RNA sequencing (scRNA-seq) data analysis often involves complex iterative workflow, requiring significant expertise and time. To navigate this complexity, we have developed SCassist, an R package that leverages the power of the large language models (LLMs) to guide and enhance scRNA-seq analysis. SCassist integrates LLMs into key workflow steps, to analyze user data and provide relevant recommendations for filtering, normalization and clustering parameters. It also provides LLM guided insightful interpretations of variable features and principal components, along with cell type annotations and enrichment analysis. SCassist provides intelligent assistance using popular LLMs like Googles Gemini, OpenAIs GPT and Metas Llama3, making scRNA-seq analysis accessible to researchers at all levels. Availability and implementationThe SCassist package, along with the detailed tutorials, is available at GitHub. https://github.com/NIH-NEI/SCassist

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Nagarajan, V., Shi, G., Arunkumar, S., Liu, C., Gopalakrishnan, J., Nath, P. R., Jang, J., Caspi, R.. 2025-04-24. SCassist: An AI Based Workflow Assistant for Single-Cell Analysis. https://doi.org/10.1101/2025.04.22.650107

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