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易流:一个开源的、用户友好的流式细胞仪分析软件,带有图形用户界面(GUI)。

EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI).

机构信息

Department of Bioengineering, Stanford University, Stanford, California, United States of America.

Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.

出版信息

PLoS One. 2024 Nov 13;19(11):e0308873. doi: 10.1371/journal.pone.0308873. eCollection 2024.

Abstract

Flow cytometry enables quantitative measurements of fluorescence in single cells. The technique was widely used for immunology to identify populations with different surface protein markers. More recently, the usage of flow cytometry has been extended to additional readouts, including intracellular proteins and fluorescent protein transgenes, and is widely utilized to study developmental biology, systems biology, microbiology, and many other fields. A common file format (FCS format, defined by the International Society for Advancement of Cytometry (ISAC)) has been universally adopted, facilitating data exchange between different machines. A diverse spectrum of software packages has been developed for the analysis of flow cytometry data. However, those are either 1) costly proprietary softwares, 2) open source packages with prerequisite installation of R or Python and sometimes require users to have experience in coding, or 3) online tools that are limiting for analysis of large data sets. Here, we present EasyFlow, an open-source flow cytometry analysis graphic user interface (GUI) based on Matlab or Python, that can be installed and run locally across platforms (Windows, MacOS, and Linux) without requiring previous coding knowledge. The Python version (EasyFlowQ) is also developed on a popular plotting framework (Matplotlib) and modern user interface toolkit (Qt), allowing more advanced users to customize and keep contributing to the software, as well as its tutorials. Overall, EasyFlow serves as a simple-to-use tool for inexperienced users with little coding experience to use locally, as well as a platform for advanced users to further customize for their own needs.

摘要

流式细胞术能够对单细胞中的荧光进行定量测量。该技术在免疫学中被广泛用于识别具有不同表面蛋白标记的细胞群体。最近,流式细胞术的应用已经扩展到其他读数,包括细胞内蛋白和荧光蛋白转基因,并广泛用于研究发育生物学、系统生物学、微生物学和许多其他领域。一种通用的文件格式(由国际流式细胞术学会 (ISAC) 定义的 FCS 格式)已被普遍采用,促进了不同机器之间的数据交换。已经开发了各种软件包来分析流式细胞术数据。然而,这些软件包要么是 1)昂贵的专有软件,要么是 2)需要安装 R 或 Python 的开源软件,并且有时要求用户具有编码经验,要么是 3)在线工具,这些工具对于大型数据集的分析有一定限制。在这里,我们介绍了 EasyFlow,这是一种基于 Matlab 或 Python 的开源流式细胞术分析图形用户界面 (GUI),可以在不要求事先具备编码知识的情况下在跨平台(Windows、MacOS 和 Linux)上安装和运行。Python 版本(EasyFlowQ)也是基于流行的绘图框架 (Matplotlib) 和现代用户界面工具包 (Qt) 开发的,允许更高级的用户进行定制,并为软件及其教程做出贡献。总的来说,EasyFlow 是一个简单易用的工具,适合没有编码经验的新手用户在本地使用,也是高级用户根据自己的需求进一步定制的平台。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c3c/11560029/a0f886c314de/pone.0308873.g001.jpg

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