Online Tables for the thesis "Clustering approaches for patient stratification in psychiatry" by Jonas Hagenberg

<p>This repository contains the online tables that accompany my thesis "Clustering approaches for patient stratification in psychiatry".</p> <p>In the following, I list the description of all tables:</p> <p>&nbsp;</p> <div> <div> <p>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.</p> <p>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.</p> <p>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.</p> <p>4: Variable importance of all gene sets in the initial clustering. Full version of supplementary table 8.</p> <p>5: Variable importance of all variables the secondary analysis corrected for age, sex and BMI. Full version of supplementary table 9.</p> <p>6: Variable importance of all variables the exploratory analysis including cell type proportions. Full version of supplementary table 10.</p> <p>7: Variable importance of all gene sets in the exploratory analysis including cell type proportions. Full version of supplementary table 11.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>24: Differentially expressed genes with regard to BMI separated by cell type. The analysis was performed with DESeq2 and the model contained only BMI.</p> <p>25: Variable importance of initial multi-omics clustering of the DEGs identified in the single cell data set.</p> </div> </div>