Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells

Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells

Complex interactions between different host immune cell types can determine the outcome of pathogen infections. Here, Avraham and colleagues present a deconvolution algorithm that uses single-cell RNA and bulk RNA sequencing measurements of pathogen-infected cells to predict disease risk outcomes.

Bibliographic Details
Main Authors: Noa Bossel Ben-Moshe, Shelly Hen-Avivi, Natalia Levitin, Dror Yehezkel, Marije Oosting, Leo A. B. Joosten, Mihai G. Netea, Roi Avraham
Format: Article
Language:English
Published: Nature Publishing Group 2019-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-019-11257-y

Internet

https://doi.org/10.1038/s41467-019-11257-y

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