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COMPARE, an ultra-fast and robust suite for multiparametric screening, identifies phenotypic drug responses in acute myeloid leukemia
bioRxiv - Cancer Biology Pub Date : 2021-01-18 , DOI: 10.1101/2021.01.08.425880
Morteza Chalabi Hajkarim , Ella Karjalainen , Mikhail Osipovitch , Konstantinos Dimopoulos , Sandra Leigh Gordon , Francesca Ambri , Kasper Dindler Rasmussen , Kirsten Grønbæk , Kristian Helin , Krister Wennerberg , Kyoung Jae Won

Multiparametric phenotypic screening of cells, for example assessing their responses to small molecules or knockdown/knockout of specific genes, is a powerful approach to understanding cellular systems and identifying potential new therapeutic strategies. However, automated tools for analyzing similarities and differences between a large number of tested conditions have not been readily available. Methods designed for clustering cells cannot identify differences between samples effectively. We introduce COMPARE for ultra-fast and robust analysis of multiparametric high-throughput screening. Applying a mass-aware gridding algorithm using hypercubes, COMPARE performs automatic and effective similarity comparison for hundreds to thousands of tests and provides information about the treatment effect. Particularly for screening data, COMPARE is equipped with modules to remove various sources of bias. Benchmarking tests show that COMPARE can circumvent batch effects and perform a similarity analysis substantially faster than conventional analysis tools. Applying COMPARE to high-throughput flow cytometry screening data, we were able to distinguish subtle phenotypic drug responses in a human sample and a genetically engineered mouse model with acute myeloid leukemia (AML). COMPARE revealed groups of drugs with similar responses even though their mechanisms are distinct from each other. In another screening, COMPARE effectively circumvented batch effects and grouped samples from AML and myelodysplastic syndrome (MDS) patients using clinical flow cytometry data.

中文翻译:

COMPARE是一种用于多参数筛选的超快速且强大的套件,可识别急性髓细胞性白血病的表型药物反应

细胞的多参数表型筛选,例如评估它们对小分子的反应或特定基因的敲除/敲除,是了解细胞系统和确定潜在新治疗策略的有效方法。然而,用于分析大量测试条件之间的相似性和差异的自动化工具尚不可用。设计用于聚类细胞的方法无法有效识别样品之间的差异。我们推出COMPARE,可对多参数高通量筛选进行超快速且强大的分析。应用使用超立方体的大众感知网格算法,COMPARE对数百至数千个测试执行自动有效的相似度比较,并提供有关治疗效果的信息。特别是对于筛选数据 COMPARE配备了可消除各种偏差源的模块。基准测试表明,COMPARE可以规避批次效应,并且比常规分析工具执行相似性分析的速度要快得多。将COMPARE应用于高通量流式细胞术筛选数据,我们能够区分人类样品和具有急性髓样白血病(AML)的基因工程小鼠模型中的细微表型药物反应。COMPARE揭示了具有相似反应的药物组,即使它们的机制彼此不同。在另一项筛选中,COMPARE使用临床流式细胞术数据有效地规避了AML和骨髓增生异常综合症(MDS)患者的批次效应和分组样本。基准测试表明,COMPARE可以规避批次效应,并且比常规分析工具执行相似性分析的速度要快得多。将COMPARE应用于高通量流式细胞术筛选数据,我们能够区分人类样品和具有急性髓样白血病(AML)的基因工程小鼠模型中的细微表型药物反应。COMPARE揭示了具有相似反应的药物组,即使它们的机制彼此不同。在另一项筛选中,COMPARE使用临床流式细胞术数据有效地规避了AML和骨髓增生异常综合症(MDS)患者的批次效应和分组样本。基准测试表明,COMPARE可以规避批次效应,并且比常规分析工具执行相似性分析的速度要快得多。将COMPARE应用于高通量流式细胞术筛选数据,我们能够区分人类样品和具有急性髓样白血病(AML)的基因工程小鼠模型中的细微表型药物反应。COMPARE揭示了具有相似反应的药物组,即使它们的机制彼此不同。在另一项筛选中,COMPARE使用临床流式细胞术数据有效地规避了AML和骨髓增生异常综合症(MDS)患者的批次效应和分组样本。我们能够区分人类样本和具有急性髓样白血病(AML)的基因工程小鼠模型中的细微表型药物反应。COMPARE揭示了具有相似反应的药物组,即使它们的机制彼此不同。在另一项筛选中,COMPARE使用临床流式细胞术数据有效地规避了AML和骨髓增生异常综合症(MDS)患者的批次效应和分组样本。我们能够区分人类样本和具有急性髓样白血病(AML)的基因工程小鼠模型中的细微表型药物反应。COMPARE揭示了具有相似反应的药物组,即使它们的机制彼此不同。在另一项筛选中,COMPARE使用临床流式细胞术数据有效地规避了AML和骨髓增生异常综合症(MDS)患者的批次效应和分组样本。
更新日期:2021-01-19
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