Benchmarking of Multivariate Similarity Measures for High-Content Screening Fingerprints in Phenotypic Drug Discovery
Benchmarking of Multivariate Similarity Measures for High-Content Screening Fingerprints in Phenotypic Drug Discovery
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DOI：
10.1177/1087057113501390
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发表时间：
2013-12-01
影响因子：
--
通讯作者：
Selzer, Paul
中科院分区：
文献类型：
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作者：
Reisen, Felix;Zhang, Xian;Selzer, Paul
高含量筛选（HCS）是药物发现的强大工具，能够以高通量方式测量细胞对化学干扰的反应。HCS以高度多重和定量的方式提供细胞表型的基于图像的读出，包括诸如形状、强度或纹理的特征。相应的特征向量可用于表征表型，因此被定义为HCS指纹。HCS指纹的系统分析允许细胞反应的客观计算比较。因此，这种比较有助于从高通量HCS活动中检测具有不同表型结果的不同化合物。特征选择方法和相似性度量作为表型识别和聚类的基础，对于此类计算分析的质量至关重要。我们系统地评估了16种不同的相似性度量，结合线性和非线性特征选择方法，以获取生物相关的图像特征。基于非线性相关性的相似性度量，如Kendall和斯皮尔曼在大多数评估场景中表现良好，优于其他常用的度量（如欧几里得距离）。在我们的实验中，我们还提出了四个新的修改的连接图的相似性，超过了原来的版本。本研究为今后HCS的遗传表型分析奠定了基础。
High-content screening (HCS) is a powerful tool for drug discovery being capable of measuring cellular responses to chemical disturbance in a high-throughput manner. HCS provides an image-based readout of cellular phenotypes, including features such as shape, intensity, or texture in a highly multiplexed and quantitative manner. The corresponding feature vectors can be used to characterize phenotypes and are thus defined as HCS fingerprints. Systematic analyses of HCS fingerprints allow for objective computational comparisons of cellular responses. Such comparisons therefore facilitate the detection of different compounds with different phenotypic outcomes from high-throughput HCS campaigns. Feature selection methods and similarity measures, as a basis for phenotype identification and clustering, are critical for the quality of such computational analyses. We systematically evaluated 16 different similarity measures in combination with linear and nonlinear feature selection methods for their potential to capture biologically relevant image features. Nonlinear correlation-based similarity measures such as Kendall's and Spearman's perform well in most evaluation scenarios, outperforming other frequently used metrics (such as the Euclidian distance). We also present four novel modifications of the connectivity map similarity that surpass the original version, in our experiments. This study provides a basis for generic phenotypic analysis in future HCS campaigns.