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Fig. 6 | Genome Medicine

Fig. 6

From: scGRNom: a computational pipeline of integrative multi-omics analyses for predicting cell-type disease genes and regulatory networks

Fig. 6

Prediction accuracy of AD clinical phenotypes from disease genes. The AD population data for prediction was from the ROSMAP cohort [51]. AD clinical phenotypes include Braak—stages that measure the severity of neurofibrillary tangle (NFT) pathology; Cerad—scores that measure neuritic plaques; Cogdx—cognitive status at the time of death; and Dcfdx—the diagnosis of cognitive status. The bar height represents the average accuracy of cross-validation (K = 5) from the prediction using logistic regression (“Methods” section). Red: scGRNom’s cell-type disease genes shared by AD and SCZ (SCZ-AD genes). Green: AD genes from GWAS [6]. Blue: randomly select genes (same number as SCZ-AD genes)

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