Principal components analysis demonstrated a significant variation in protein abundance scores between the 32 TMT10plex groups. Many experimental factors are intrinsic with TMT10plex group: off-gel electrophoresis (OGE) fractionation date, TMT labeling date, and date of MS acquisition, which are prone to significant variation. Therefore, an initial generalized linear model (GLM) correcting for only TMT10plex group was performed before further investigating the effect of other covariates on protein group ratios. All GLM protein abundance scores were then log10-transformed to achieve normal distribution. Covariates including age, gender, and center (AIBL or KARVIAH) were investigated. We found that most proteins were significantly affected by these covariates, and therefore, subsequent GLM to include these confounders was appropriate. Missing protein abundance observations were imputed with the R package “mice” (version 2.46.0) using four imputations, four iterations, and 50 other proteins as a predictor. The 50 predictor proteins were chosen using the feature selection method LASSO via the R package “glmnet” (version 2.0-13) (40) with an α penalty cost of 1, the result of which was a list of proteins ranked by their correlation with the protein to impute; the top 50 predictor proteins were selected from this list.

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