Capturing single-cell heterogeneity via data fusion improves image-based profiling

A challenge with single-cell resolution methods is that cell heterogeneity should be captured while allowing for comparisons between populations. Here the authors fuse information from the dispersion profiles with the average profiles at the level of profiles’ similarity matrices for single cell ima...

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Autores principales: Mohammad H. Rohban, Hamdah S. Abbasi, Shantanu Singh, Anne E. Carpenter
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
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Acceso en línea:https://doaj.org/article/1960879fb520478bb38c90d85f45b3ae
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Sumario:A challenge with single-cell resolution methods is that cell heterogeneity should be captured while allowing for comparisons between populations. Here the authors fuse information from the dispersion profiles with the average profiles at the level of profiles’ similarity matrices for single cell imaging data.