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Kaplan Meier survival analysis (univariate) and Cox proportional hazards modeling (adjusted for age, body mass index, and stratified for batch effects) were used to study association of tertiles of metabolites on all-cause mortality in TwinsUK.
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The following effects were used in the analysis: type (WT-untreated, WT Li-treated, and KO) as the biological effect and batch as the random effect.
The data were normalized using subset-quantile within array normalization (SWAN) [ 52], and potential batch effects were removed using ComBat [ 53].
Batch effects were assessed using multidimensional scaling (MDS) plots for gender, sequencing flow cell and disease stage and by using the edgeR bioconductor package for RNA-Seq.
Arrays were processed using the R package lumi (R version 2.15.1, lumi version 2.8.0) with VST transformation and RSN normalization, and batch effects were removed using ComBat (Johnson et al, 2007).
To compare our RIC data and the ESCs/iPSCs data from Ma et al.27, batch effects were corrected using ComBat program in SVA package version 3.22.063 so that HDFs from the both studies had concordant expression profiles.
Batch effects were minimized using COMBAT [27] with the non-parametric option, floored at 0.00001, and log2 transformed.
Batch effects were removed using the BFRM algorithm, and MP1 expression levels were examined.
Cross-cohort batch effects were corrected using the COMBAT empirical Bayes method (Johnson et al, 2007).
Batch effects were removed using the ComBat algorithm in the SVA software package (19).
Batch effects were removed using the ComBat algorithm in the sva package [ 30].
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