Analyzing the results

Evaluation metrics

The base-maf (base minor allele frequency) and maf (target minor allele frequency) filters were toggled with. However, there was no difference in the evaluation metrics obtained.

R2 was obtained from the summary file generated by PRSice as described previously.

Using a merged dataframe containing phenotype, age, sex, and PRS, AUC is computed as follows in R:

# Compute AUC for only PRS
auc_prs <- roc(df$PHENO, df$PRS)$auc

# Create GLM for PRS, age, and sex
prs_model <- glm(PHENO ~ PRS + Age + Sex, data = df, family = binomial)

# Get predicted probabilities from the model
predicted_probs <- predict(prs_model, type = "response")

# Compute combined AUC
auc_combined <- roc(df$PHENO, predicted_probs)$auc

# Print combined AUC
print(auc_combined)

Evaluation metrics	PGS000074	PGS000785
R2	0.0505	0.0576
AUC (only PRS)	0.5783	0.6058
AUC (PRS + age + sex)	0.6976	0.7095

Distribution plots

PGS000074	PGS000785

Odds ratio plots

PGS000074	PGS000785