PMC

Four structure-guided spatial normalization methods work well for normalization of PET images, and the PET-guided method also works well in healthy control. However, in PD patient the PET-guided method stretches anterior putamen posteriorly to fill the posterior putamen during the non-linear spatial normalization. Color bars are scaled in standardized uptake value ratio (SUVR). Abbreviations: cvMR = MR-guided spatial normalization with conventional normalization tool, dtMR = MR-guided spatial normalization with DARTEL toolbox, ssCT = skull-stripped CT-guided spatial normalization, itCT = intensity transformed CT-guided spatial normalization, PET = PET-guided spatial normalization.

Normalization methods include: All sample mean normalization (ASMN), normalization by RN-factors taken as the mean control probe values for each of the plates (1–5) run, normalization by the worst performing sample’s reference normalization (RN) factor (sample 411) and the best performing sample’s RN-factor (sample 355), lumi smooth quantile normalization, and both the ASMN and lumi normalization followed by beta-mixture quantile normalization (BMIQ). Batch association was evaluated by ANOVA for each of the n=485,512 CpG sites interrogated.

Statistically significant radiomic features. Statistically significant radiomic features across normalization methods are identified with a circle. (A) Statistically significant radiomic features for receptor status ER across normalization methods. (B) Statistically significant radiomic features for receptor status PR across normalization methods. (C) Statistically significant radiomic features for receptor status HER2 across normalization methods. (D) Statistically significant radiomic features for receptor status TN across normalization methods. NO: non-normalized features; Scaling normalization method; Z-score normalization method; ZscoreR: Robust Z-score normalization method; LOG transformation; Quantile and Upper Quartile normalization method; WHT: Whitening normalization method.

Effect of normalization on F-data distribution. (A, top) MA-plots before and after applying different normalization schemes to F-data described in the text (). Except the raw data plot, in all the other MA-plots, black circles are data before normalization, and red circles are after normalization. (B, bottom) Box plots list the transformed log2 counts in the treatment condition after normalization (except raw data) separated by quartiles: Q1, Q2, Q3, and Q4. Q1 is the lowest quartile and Q4 is the highest quartile. The color codes for box plots from left to right are as follows: black (raw data), blue (global normalization), purple (Lowess normalization), brown (TMM normalization), orange (scaling normalization), gray (quantile normalization), green (VSN normalization), and red (INV normalization).