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Table 1 Prediction models based on candidate genes.

From: Identifying disease associated genes by network propagation

  T = 1   T=
method Gene a SNP1 b SNP2c AUC1d AUC2 e Gene SNP1 SNP2 AUC1 AUC2
Sig. Thresh.f 130 1176 1145 0.705(0.033) 0.687(0.032) 184 1314 1281 0.730(0.017) 0.715(0.013)
PSg 130 2331 2310 0.645(0.024) 0.627(0.026) 184 3279 3256 0.645(0.024) 0.626(0.026)
  1. aGene is number of genes identified as GBA associations,
  2. bSNP1 is number of SNPs mapped to these genes.
  3. cSNP2 is bSNP1 excluding snps that reach GWAS significance of 5 × 10−7.
  4. dAUC1, mean AUC of prediction models built with bSNP1, numbers in parentheses are standard deviation in cross validations.
  5. eAUC2, similar to AUC1, prediction models built with cSNP2.
  6. fSig. Thresh. = 0.01
  7. gPS means genes with highest posterior scores are selected.