Integration of Single-Cell and Bulk RNA Sequencing Data using Ecotype Machine Learning for Prognostic Biomarker Discovery in Gastric Cancer
Yalu Zheng,
Tengzheng Li,
Yunting Qi
et al.
Abstract:Background
EcoTyper is a new machine learning framework, this work attempted to constructed an EcoTyper-related prognostic model for gastric cancer (GC).
Methods
The scRNA-seq data and bulk RNA-seq data for GC were obtained from the GEO and TCGA databases, respectively. Cell composition deconvolution was performed using CIBERSORTx. EcoTyper was employed for de novo discovery of scRNA-seq cell states and communities. Weighted Correlation Network Analysis was applied to explore the gene co-expression networks … Show more
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