This study investigates key genes contributing to lupus nephritis(LN).While extensive research has elucidated various aspects of LN pathogenesis,the specific involvement of phosphorylation-related genes(PRGs)in this c...This study investigates key genes contributing to lupus nephritis(LN).While extensive research has elucidated various aspects of LN pathogenesis,the specific involvement of phosphorylation-related genes(PRGs)in this context remains an area of growing interest.We employ single-cell RNA sequencing analysis on renal tissues from 24 LN patients and 10 healthy controls.Leveraging the nonnegative matrix factorization(NMF)algorithm,we identified critical gene patterns and constructed 61 predictive models using a comprehensive suite of 12 machine learning algorithms.We developed a predictive model using 6 PRGs,enhanced by a LASSO plus Naive Bayes approach.展开更多
基金supported by the Science and Technology Program for Basic Research in Shenzhen,Guangdong,China(No.JCYJ20200109140412476,JCYJ20190809095811254,GCZX2015043017281705)the Clinical Research Project in Shenzhen,Guangdong,China(No.20213357002,20213357028)+1 种基金the Team-based Medical Science Research Program in Shenzhen,Guangdong,China(No.2024YZZ06)Shenzhen High-level Hospital Construction Fund in Shenzhen,Guangdong,China(No.2024).
文摘This study investigates key genes contributing to lupus nephritis(LN).While extensive research has elucidated various aspects of LN pathogenesis,the specific involvement of phosphorylation-related genes(PRGs)in this context remains an area of growing interest.We employ single-cell RNA sequencing analysis on renal tissues from 24 LN patients and 10 healthy controls.Leveraging the nonnegative matrix factorization(NMF)algorithm,we identified critical gene patterns and constructed 61 predictive models using a comprehensive suite of 12 machine learning algorithms.We developed a predictive model using 6 PRGs,enhanced by a LASSO plus Naive Bayes approach.
