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Automated Identification and Quantification of Signals in Multichannel Immunofluorescence Images

机译:自动识别和定量多通道免疫荧光图像中的信号

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摘要

Multimarker fluorescence analysis of tissue specimens offers the opportunity to probe the expression levels and locations of multiple markers in a single sample. Software is needed to fully capitalize on the advantages of this technology for sensitive, quantitative, and multiplexed data collection. A major challenge has been the automated identification and quantification of signals. We report on the software SignalFinder-IF, which meets that need. SignalFinder-IF uses a newly developed algorithm called Segment-Fit Thresholding, which showed robust performance for automated signal identification in side-by-side comparisons with several current methods. Two utilities provided with SignalFinder-IF enable downstream analyses. The first allows the quantification and mapping of relationships between an unlimited number of markers through user-defined sequences of AND, OR, and NOT operators. The second produces composite pictures of the signals or colocalization analysis on brightfield hematoxylin and eosin images, which is useful for understanding the morphologies and locations of cells meeting specific marker criteria. SignalFinder-IF enables high-throughput, rigorous analyses of whole-slide, multimarker data, and it promises to open new possibilities in many research and clinical applications.
机译:组织样本的多标记荧光分析提供了探测单个样品中多个标记的表达水平和位置的机会。需要使用软件来充分利用此技术的优势,以进行敏感,定量和多路复用的数据收集。一个主要的挑战是信号的自动识别和量化。我们报告了满足要求的SignalFinder-IF软件。 SignalFinder-IF使用一种新开发的算法,称为“分段拟合阈值”,该算法在与几种当前方法进行并排比较时显示出强大的自动信号识别性能。 SignalFinder-IF随附的两个实用程序可进行下游分析。第一种允许通过用户定义的AND,OR和NOT运算符序列来量化和映射无限数量的标记之间的关系。第二个在明场苏木和曙红图像上生成信号的复合图片或共定位分析,这对于理解满足特定标记标准的细胞的形态和位置很有用。 SignalFinder-IF可以对整个幻灯片,多标记数据进行高通量,严格的分析,并有望在许多研究和临床应用中打开新的可能性。

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