DOI: 10.5281/zenodo.14010723
title: Online Tables for the thesis "Clustering approaches for patient stratification in psychiatry" by Jonas Hagenberg

description: This repository contains the online tables that accompany my thesis "Clustering approaches for patient stratification in psychiatry".

In the following, I list the description of all tables:

 





1: Information about somatic diseases and medication separated by status (participants labeled as cases and used in the clustering as well as controls without a DSM-IV diagnosis). N data denotes the number of individuals who had the information available. The medication information was not available for the OPTIMA cohort. N denotes the individuals who were affected by the disease or took the medication.

2: Missingness and coefficient of variation information of the immune marker data for 237 participants used in the clustering and 36 controls without a DSM-IV diagnosis. The coefficient of variation was calculated from three internal controls that were run in duplicates.

3: Variable importance of all variables the initial clustering. The variable importance is calculated as the F-value from an ANOVA model with the clusters as independent variables. The variable importance cannot be interpreted as a p-value as the variables were already used in the clustering, thereby inflating the p-values. Full version of supplementary table 3.

4: Variable importance of all gene sets in the initial clustering. Full version of supplementary table 8.

5: Variable importance of all variables the secondary analysis corrected for age, sex and BMI. Full version of supplementary table 9.

6: Variable importance of all variables the exploratory analysis including cell type proportions. Full version of supplementary table 10.

7: Variable importance of all gene sets in the exploratory analysis including cell type proportions. Full version of supplementary table 11.

8: Differentially expressed genes with regard to the CRP concentration separated by cell type. The analysis was performed with DESeq2 and the model contained CRP, IL-6 and BMI. Full version of supplementary table 12.

9: Differentially expressed genes with regard to the IL-6 concentration separated by cell type. The analysis was performed with DESeq2 and the model contained CRP, IL-6 and BMI. Full version of supplementary table 13.

10: Enriched hallmark gene sets with regard to CRP calculated with the results from the model containing CRP, IL-6 and BMI separated by cell type.

11: Enriched hallmark gene sets with regard to IL-6 calculated with the results from the model containing CRP, IL-6 and BMI separated by cell type.

12: Enriched hallmark gene sets with regard to BMI calculated with the results from the model containing CRP, IL-6 and BMI separated by cell type.

13: Enriched GO biological pathway gene sets with regard to CRP calculated with the results from the model containing CRP, IL-6 and BMI separated by cell type. Full version of supplementary table 15.

14: Enriched GO biological pathway gene sets with regard to IL-6 calculated with the results from the model containing CRP, IL-6 and BMI separated by cell type.

15: Enriched GO biological pathway gene sets with regard to BMI calculated with the results from the model containing CRP, IL-6 and BMI separated by cell type.

16: Differentially expressed genes with regard to the CRP concentration separated by cell type. The analysis was performed with DESeq2 and the model contained CRP and IL-6.

17: Differentially expressed genes with regard to the IL-6 concentration separated by cell type. The analysis was performed with DESeq2 and the model contained CRP and IL-6.

18: Differentially expressed genes with regard to the CRP concentration separated by cell type. The analysis was performed with DESeq2 and the model contained CRP and BMI.

19: Differentially expressed genes with regard to BMI separated by cell type. The analysis was performed with DESeq2 and the model contained CRP and BMI.

20: Differentially expressed genes with regard to the IL-6 concentration separated by cell type. The analysis was performed with DESeq2 and the model contained IL-6 and BMI.

21: Differentially expressed genes with regard to BMI separated by cell type. The analysis was performed with DESeq2 and the model contained IL-6 and BMI.

22: Differentially expressed genes with regard to the CRP concentration separated by cell type. The analysis was performed with DESeq2 and the model contained only CRP.

23: Differentially expressed genes with regard to the IL-6 concentration separated by cell type. The analysis was performed with DESeq2 and the model contained only IL-6.

24: Differentially expressed genes with regard to BMI separated by cell type. The analysis was performed with DESeq2 and the model contained only BMI.

25: Variable importance of initial multi-omics clustering of the DEGs identified in the single cell data set.