An approach for extensibly profiling the molecular states of cellular subpopulations.
An approach for extensibly profiling the molecular states of cellular subpopulations.
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DOI：
10.1038/nmeth.1375
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发表时间：
2009-10
期刊：
影响因子：
48
通讯作者：
Altschuler, Steven J.
中科院分区：
文献类型：
--
作者：
Loo, Lit-Hsin;Lin, Hai-Jui;Steininger, Robert J., III;Wang, Yanqin;Wu, Lani F.;Altschuler, Steven J.
显微镜检查经常揭示表型不同的细胞亚群的存在。然而，观察到的亚群的进一步表征可能受到可以同时监测的生物分子标记物的数量的限制。在这里，我们提出了一种计算方法，可扩展地分析细胞亚群释放一个或多个成像通道，以监测额外的探针。在我们的方法中，我们训练分类器，以基于仅从原始标记的子集中提取的表型特征的增强集合来准确地重新识别亚群。然后从重复实验逐步构建亚群谱，其中细胞用不同但重叠的标记物组标记。我们应用我们的方法来表征亚群之间的分子差异，以及分化小鼠前脂肪细胞，极化人类嗜酸性粒细胞样细胞和分裂人类癌细胞的群体内的标记物的功能分组。
Microscopy often reveals the existence of phenotypically distinct cellular subpopulations. However, further characterization of observed subpopulations can be limited by the number of biomolecular markers that can be simultaneously monitored. Here, we present a computational approach for extensibly profiling cellular subpopulations by freeing up one or more imaging channels to monitor additional probes. In our approach, we train classifiers to re-identify subpopulations accurately based on an enhanced collection of phenotypic features extracted from only a subset of the original markers. Subpopulation profiles were then constructed step-wise from replicate experiments, in which cells were labeled with different but overlapping marker sets. We applied our approach to characterize molecular differences among subpopulations, and functional groupings of markers within populations of differentiating mouse preadipocytes, polarizing human neutrophil-like cells, and dividing human cancer cells.
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DOI：
10.1083/jcb.115.1.1
发表时间：
1991-10
期刊：
The Journal of cell biology
影响因子：
--
作者：
Pines J;Hunter T
通讯作者：
Hunter T
影响因子：
48
作者：
Loo, Lit-Hsin;Wu, Lani F.;Altschuler, Steven J.
通讯作者：
Altschuler, Steven J.
影响因子：
5.3
作者：
Dulic, V;Stein, GH;Reed, SI
通讯作者：
Reed, SI
影响因子：
64.8
作者：
Chang, Hannah H.;Hemberg, Martin;Huang, Sui
通讯作者：
Huang, Sui
影响因子：
56.9
作者：
Lee, TI;Rinaldi, NJ;Young, RA
通讯作者：
Young, RA