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h5. Batch vs clinical traits Number of clinical traits: 31 Number of batches based on DNA methylation data: 19 Relationship between batch and the center: {code:collapse=true}> table(batchID,two) two batchID 02 06 08 12 14 15 16 19 26 27 28 32 41 74 76 81 87 0186 25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0199 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0218 0 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0242 0 53 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0279 34 17 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0287 26 16 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0297 13 0 19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0314 2 7 6 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0337 0 10 0 16 0 1 0 0 0 0 0 0 0 0 0 0 0 0392 0 7 0 10 6 0 5 0 0 0 0 0 0 0 0 0 0 0521 0 4 0 12 12 3 7 6 3 0 0 0 0 0 0 0 0 0595 0 4 0 4 13 0 1 10 1 4 9 0 0 0 0 0 0 0788 5 12 0 0 3 0 0 0 0 13 10 4 0 0 0 0 0 0915 0 0 0 9 2 0 0 9 0 0 0 5 4 0 0 0 0 1228 0 1 0 0 2 0 1 3 1 0 0 15 4 0 0 0 0 1481 0 5 0 3 0 0 0 0 6 0 11 1 0 0 9 0 0 1697 0 13 0 0 1 1 0 10 1 0 3 2 1 0 5 1 1 1844 0 10 0 0 5 0 0 1 2 0 1 0 1 6 10 1 0 2004 0 7 0 0 3 0 0 4 0 0 0 0 0 0 0 0 0{code} Relationship between batch and clinical variable, significant correlations (entire table can be found [here|^BatchClinicalInfoCorrelationsGBM.txt]) {csv}GBM_clinical,DataType,NumberOfNAs,Test,Pvalue year_of_initial_pathologic_diagnosis,integer,35,Kruskal-Wallis rank sum test,1.34E-64 pretreatment_history,factor,35,Pearson's Chi-squared test,2.98E-29 histological_type,factor,35,Pearson's Chi-squared test,6.11E-20 initial_pathologic_diagnosis_method,factor,37,Pearson's Chi-squared test,5.24E-15 vital_status,factor,36,Pearson's Chi-squared test,8.36E-15 hormonal_therapy,factor,59,Pearson's Chi-squared test,6.50E-14 targeted_molecular_therapy,factor,65,Pearson's Chi-squared test,5.80E-10 additional_pharmaceutical_therapy,factor,72,Pearson's Chi-squared test,4.19E-05 additional_drug_therapy,factor,73,Pearson's Chi-squared test,5.08E-05 days_to_last_followup,integer,35,Kruskal-Wallis rank sum test,2.90E-04 person_neoplasm_cancer_status,factor,88,Pearson's Chi-squared test,4.81E-04 additional_chemo_therapy,factor,106,Pearson's Chi-squared test,5.18E-03 days_to_death,integer,169,Kruskal-Wallis rank sum test,6.30E-03 days_to_birth,integer,35,Kruskal-Wallis rank sum test,1.13E-02 age_at_initial_pathologic_diagnosis,integer,35,Kruskal-Wallis rank sum test,1.20E-02{csv} h5. Survival vs batch Code for automatic analysis of survival and correlation with clinical traits can be found [here|^SurvivalBasicAnalysis.R]. Kaplan Meier Curve and survival by batch: !KaplanMeierCurveGBM.png|thumbnail! !SurvivalByBatchGBM.png|thumbnail! Summary of the cox proportional hazards model can be found [here|^SurvivalBatchSummaryStatisticsGBM.txt], batch shows significant correlation with survival (Likelihood ratio test= 31 on 17 df, p=0.02; Wald test = 28.17 on 17 df, p=0.04297; Score (logrank) test = 29.48 on 17 df, p=0.03035) I need to state here (and for all cancer types from TCGA that I have analyzed and will analyze) that the p-valuevalues for the association of the batches with the clinical traits correspond to ALL batches. However, actual DNA methylation (or other data) may not be available for all batches yet. For example, for GBM I have 9 batchedbatches for the downloaded 286 patients. I still see significant correlation between these batches and the clinical traits (p values might be bigger though. For example, correlation between histological type and batches is 3.9e-11). h5. DNA methylation Downloaded the data in the last week of December, 27k, Level1, 294 patients. Weird format for the files, methylated and unmethylated probe intensities are in the first and second columns, different from the format that was used for other datasets. Compared list of DNA methylation patients with the technical info, tech info is available for only 286 patients. Stick with those for the analysis. |
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