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.
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2019-07-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-019-11257-y |