VoPo leverages cellular heterogeneity for predictive modeling of single-cell data

VoPo leverages cellular heterogeneity for predictive modeling of single-cell data

Single-cell technologies are increasingly prominent in clinical applications, but predictive modelling with such data in large cohorts has remained computationally challenging. We developed a new algorithm, ‘VoPo’, for predictive modelling and visualization of single cell data for translational appl...

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Autores principales: Natalie Stanley, Ina A. Stelzer, Amy S. Tsai, Ramin Fallahzadeh, Edward Ganio, Martin Becker, Thanaphong Phongpreecha, Huda Nassar, Sajjad Ghaemi, Ivana Maric, Anthony Culos, Alan L. Chang, Maria Xenochristou, Xiaoyuan Han, Camilo Espinosa, Kristen Rumer, Laura Peterson, Franck Verdonk, Dyani Gaudilliere, Eileen Tsai, Dorien Feyaerts, Jakob Einhaus, Kazuo Ando, Ronald J. Wong, Gerlinde Obermoser, Gary M. Shaw, David K. Stevenson, Martin S. Angst, Brice Gaudilliere, Nima Aghaeepour
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Science
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Acceso en línea:https://doaj.org/article/e63eb4be164c423694059f87cd18e59d
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Sumario:Single-cell technologies are increasingly prominent in clinical applications, but predictive modelling with such data in large cohorts has remained computationally challenging. We developed a new algorithm, ‘VoPo’, for predictive modelling and visualization of single cell data for translational applications.

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