Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases

Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases

Cell type deconvolution from bulk expression data rely on a reference expression matrix. Here, the authors introduce a basis matrix built using data from both healthy and diseased samples profiled on 42 platforms, reducing biases introduced by single-platform matrices built using healthy samples.

Bibliographic Details
Main Authors: Francesco Vallania, Andrew Tam, Shane Lofgren, Steven Schaffert, Tej D. Azad, Erika Bongen, Winston Haynes, Meia Alsup, Michael Alonso, Mark Davis, Edgar Engleman, Purvesh Khatri
Format: Article
Language:English
Published: Nature Publishing Group 2018-11-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-018-07242-6

Internet

https://doi.org/10.1038/s41467-018-07242-6

Similar Items