Automated Identification and Quantification of Signals in Multichannel Immunofluorescence Images The SignalFinder-IF Platform

被引:11
|
作者
Barnett, Daniel [1 ]
Hall, Johnathan [1 ]
Haab, Brian [1 ]
机构
[1] Van Andel Res Inst, Ctr Canc & Cell Biol, Grand Rapids, MI USA
来源
AMERICAN JOURNAL OF PATHOLOGY | 2019年 / 189卷 / 07期
关键词
IMMUNOHISTOCHEMISTRY; COLOCALIZATION; MICROARRAY; PATHOLOGY;
D O I
10.1016/j.ajpath.2019.03.011
中图分类号
R36 [病理学];
学科分类号
100104 ;
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.
引用
收藏
页码:1402 / 1412
页数:11
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