biostudies-literatureWang SU.S. Department of Health and Human ServicesNIAID NIH HHSSchool of Dental Medicine, University of PittsburghNational Institutes of HealthNIAID1278-1294.e4https://www.ebi.ac.uk/biostudies/studies/S-EPMC11659032biostudies-literatureUnknown15(12)Analysis of multi-modal datasets can identify multi-scale interactions underlying biological systems but can be beset by spurious connections due to indirect impacts propagating through an unmapped biological network. For example, studies in macaques have shown that Bacillus Calmette-Guerin (BCG) vaccination by an intravenous route protects against tuberculosis, correlating with changes across various immune data modes. To eliminate spurious correlations and identify critical immune interactions in a public multi-modal dataset (systems serology, cytokines, and cytometry) of vaccinated macaques, we applied Markov fields (MFs), a data-driven approach that explains vaccine efficacy and immune correlations via multivariate network paths, without requiring large numbers of samples (i.e., macaquCell systemsMarkov field network model of multi-modal data predicts effects of immune system perturbations on intravenous BCG vaccination in macaques.PMC1165903275N93019C00071F31 AI150171AI150171U19 AI167899AI167899Chao MCKracinovsky KLin PLFlynn JLLauffenburger DARoederer MFortune SMWang CTomko JScanga CAMyers AJSeder RAAlter GRodgers MAMugahid DWang SBorish HJIrvine EBDarrah PAMaiello PfalseMarkov field network model of multi-modal data predicts effects of immune system perturbations on intravenous BCG vaccination in macaques.Analysis of multi-modal datasets can identify multi-scale interactions underlying biological systems but can be beset by spurious connections due to indirect impacts propagating through an unmapped biological network. For example, studies in macaques have shown that Bacillus Calmette-Guerin (BCG) vaccination by an intravenous route protects against tuberculosis, correlating with changes across various immune data modes. To eliminate spurious correlations and identify critical immune interactions in a public multi-modal dataset (systems serology, cytokines, and cytometry) of vaccinated macaques, we applied Markov fields (MFs), a data-driven approach that explains vaccine efficacy and immune correlations via multivariate network paths, without requiring large numbers of samples (i.e., macaqu2024-01-01T00:00:00Z2024 Dec2026-06-06T04:12:42.265Z2026-05-25T03:12:01.112ZS-EPMC116590323950496910.1016/j.cels.2024.10.001