ClearFinder: a Python GUI for annotating cells in cleared mouse brain.

IF 2.9 3区生物学 Q2 BIOCHEMICAL RESEARCH METHODS

BMC Bioinformatics Pub Date : 2025-01-21 DOI:10.1186/s12859-025-06039-x

Stefan Pastore, Philipp Hillenbrand, Nils Molnar, Irina Kovlyagina, Monika Chanu Chongtham, Stanislav Sys, Beat Lutz, Margarita Tevosian, Susanne Gerber

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引用次数: 0

Abstract

Background: Tissue clearing combined with light-sheet microscopy is gaining popularity among neuroscientists interested in unbiased assessment of their samples in 3D volume. However, the analysis of such data remains a challenge. ClearMap and CellFinder are tools for analyzing neuronal activity maps in an intact volume of cleared mouse brains. However, these tools lack a user interface, restricting accessibility primarily to scientists proficient in advanced Python programming. The application presented here aims to bridge this gap and make data analysis accessible to a wider scientific community.

Results: We developed an easy-to-adopt graphical user interface for cell quantification and group analysis of whole cleared adult mouse brains. Fundamental statistical analysis, such as PCA and box plots, and additional visualization features allow for quick data evaluation and quality checks. Furthermore, we present a use case of ClearFinder GUI for cross-analyzing the same samples with two cell counting tools, highlighting the discrepancies in cell detection efficiency between them.

Conclusions: Our easily accessible tool allows more researchers to implement the methodology, troubleshoot arising issues, and develop quality checks, benchmarking, and standardized analysis pipelines for cell detection and region annotation in whole volumes of cleared brains.

查看原文本刊更多论文

ClearFinder：一个Python GUI，用于注释已清除的老鼠大脑中的细胞。

背景：组织清除结合光片显微镜在神经科学家中越来越受欢迎，他们对3D体积样品的公正评估感兴趣。然而，对这些数据的分析仍然是一个挑战。ClearMap和CellFinder是分析清除小鼠大脑完整体积内神经元活动图的工具。然而，这些工具缺乏用户界面，限制了主要对精通高级Python编程的科学家的访问。这里展示的应用程序旨在弥合这一差距，并使数据分析能够为更广泛的科学界所接受。结果：我们开发了一个易于使用的图形用户界面，用于细胞定量和全清除成年小鼠脑的组分析。基本的统计分析，如PCA和箱形图，以及额外的可视化特性允许快速的数据评估和质量检查。此外，我们提出了一个ClearFinder GUI用例，用两种细胞计数工具交叉分析相同的样本，突出了它们之间细胞检测效率的差异。结论：我们易于使用的工具允许更多的研究人员实施方法，排除出现的问题，并开发质量检查，基准测试和标准化分析管道，用于细胞检测和区域注释。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Bioinformatics 生物-生化研究方法

CiteScore

5.70

自引率

3.30%

发文量

506

审稿时长

4.3 months

期刊介绍： BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.