Spidlen Josef, Barsky Aaron, Breuer Karin, Carr Peter, Nazaire Marc-Danie, Hill Barbara Allen, Qian Yu, Liefeld Ted, Reich Michael, Mesirov Jill P, Wilkinson Peter, Scheuermann Richard H, Sekaly Rafick-Pierre, Brinkman Ryan R
Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada.
Source Code Biol Med. 2013 Jul 3;8(1):14. doi: 10.1186/1751-0473-8-14.
Traditional flow cytometry data analysis is largely based on interactive and time consuming analysis of series two dimensional representations of up to 20 dimensional data. Recent technological advances have increased the amount of data generated by the technology and outpaced the development of data analysis approaches. While there are advanced tools available, including many R/BioConductor packages, these are only accessible programmatically and therefore out of reach for most experimentalists. GenePattern is a powerful genomic analysis platform with over 200 tools for analysis of gene expression, proteomics, and other data. A web-based interface provides easy access to these tools and allows the creation of automated analysis pipelines enabling reproducible research.
In order to bring advanced flow cytometry data analysis tools to experimentalists without programmatic skills, we developed the GenePattern Flow Cytometry Suite. It contains 34 open source GenePattern flow cytometry modules covering methods from basic processing of flow cytometry standard (i.e., FCS) files to advanced algorithms for automated identification of cell populations, normalization and quality assessment. Internally, these modules leverage from functionality developed in R/BioConductor. Using the GenePattern web-based interface, they can be connected to build analytical pipelines.
GenePattern Flow Cytometry Suite brings advanced flow cytometry data analysis capabilities to users with minimal computer skills. Functionality previously available only to skilled bioinformaticians is now easily accessible from a web browser.
传统的流式细胞术数据分析很大程度上基于对多达20维数据的一系列二维表示进行交互式且耗时的分析。最近的技术进步增加了该技术产生的数据量,超过了数据分析方法的发展速度。虽然有先进的工具可用,包括许多R/BioConductor软件包,但这些工具只能通过编程方式访问,因此大多数实验人员无法使用。基因模式(GenePattern)是一个强大的基因组分析平台,拥有200多种用于分析基因表达、蛋白质组学和其他数据的工具。基于网络的界面提供了对这些工具的便捷访问,并允许创建自动化分析管道,实现可重复研究。
为了将先进的流式细胞术数据分析工具带给没有编程技能的实验人员,我们开发了基因模式流式细胞术套件。它包含34个开源的基因模式流式细胞术模块,涵盖从流式细胞术标准(即FCS)文件的基本处理到细胞群体自动识别、归一化和质量评估的高级算法等方法。在内部,这些模块利用了R/BioConductor中开发的功能。使用基于网络的基因模式界面,可以将它们连接起来构建分析管道。
基因模式流式细胞术套件为计算机技能有限的用户带来了先进的流式细胞术数据分析能力。以前只有熟练的生物信息学家才能使用的功能现在可以通过网络浏览器轻松访问。