Identification of immune feature genes and intercellular profiles in diabetic cardiomyopathy

Table 1 Detailed information on the datasets used in this study

Accession number	Method	Origin	Samples		Aim
			DCM	CTL
GSE5606	Bulk RNA-seq	Rattus norvegicus	7	7	Merged as discovery cohorts
GSE6880	Bulk RNA-seq	Rattus norvegicus	3	3
GSE4745	Bulk RNA-seq	Rattus norvegicus	12	12	Merged as validation cohorts
GSE197999	Bulk RNA-seq	Rattus norvegicus	5	5
GSE213337	scRNA-seq	Mus musculus	1	1	Single cell analysis

RNA-seq: RNA sequencing; DCM: Diabetic cardiomyopathy; CTL: Control.

Table 2 Results of least absolute shrinkage and selection operator and support vector machine recursive feature elimination algorithms for the selection of immune-related feature genes

LASSO		SVM-RFE
Variables	Coefficients	Variables	Accuracy	Kappa
Penk	4.895	Il12a	0.800	0.600
Il12a	0	Angptl4	0.900	0.800
Gcgr	-4.308	Rbp7	0.967	0.933
Rbp7	1.761	Sctr	0.900	0.800
Inha	-1.155	Penk	1.000	1.000
Sctr	0	Gcgr	1.000	1.000
Angptl4	2.382	Inha	1.000	1.000

LASSO: Least absolute shrinkage and selection operator; SVM-RFE: Support vector machine recursive feature elimination; Penk: Proenkephalin; Gcgr: Glucagon receptor; Rbp7: Retinol binding protein 7; Inha: Inhibin subunit alpha.