Combining machine learning and single-cell sequencing to identify key immune genes in sepsis

Abstract This research aimed to identify novel indicators for sepsis by analyzing RNA sequencing data from peripheral blood samples obtained from sepsis patients (n = 23) and healthy controls (n = 10). 5148 differentially expressed genes were identified using the DESeq2 technique and 5636 differenti...

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Bibliographic Details
Main Authors: Hao Wang, Linghan Len, Li Hu, Yingchun Hu
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-85799-1
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