This pipeline computes the correlation between APOBRC groups and selected clinical features.
Testing the association between APOBEC groups identified by 2 different apobec score and 15 clinical features across 481 patients, no significant finding detected with Q value < 0.25.
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3 subtypes identified in current cancer cohort by 'APOBEC MUTLOAD MINESTIMATE'. These subtypes do not correlate to any clinical features.
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3 subtypes identified in current cancer cohort by 'APOBEC ENRICH'. These subtypes do not correlate to any clinical features.
Clinical Features |
Statistical Tests |
APOBEC MUTLOAD MINESTIMATE |
APOBEC ENRICH |
Time to Death | logrank test |
0.312 (0.646) |
0.314 (0.646) |
YEARS TO BIRTH | Kruskal-Wallis (anova) |
0.078 (0.404) |
0.0532 (0.399) |
PATHOLOGIC STAGE | Fisher's exact test |
0.931 (0.961) |
0.535 (0.698) |
PATHOLOGY T STAGE | Fisher's exact test |
0.415 (0.655) |
0.036 (0.36) |
PATHOLOGY N STAGE | Fisher's exact test |
0.961 (0.961) |
0.496 (0.698) |
PATHOLOGY M STAGE | Fisher's exact test |
0.366 (0.646) |
0.275 (0.646) |
GENDER | Fisher's exact test |
0.771 (0.889) |
0.916 (0.961) |
RADIATION THERAPY | Fisher's exact test |
0.467 (0.698) |
0.532 (0.698) |
KARNOFSKY PERFORMANCE SCORE | Kruskal-Wallis (anova) |
0.821 (0.913) |
0.181 (0.544) |
HISTOLOGICAL TYPE | Fisher's exact test |
0.108 (0.404) |
0.0278 (0.36) |
NUMBER PACK YEARS SMOKED | Kruskal-Wallis (anova) |
0.0112 (0.337) |
0.155 (0.517) |
YEAR OF TOBACCO SMOKING ONSET | Kruskal-Wallis (anova) |
0.0904 (0.404) |
0.105 (0.404) |
RESIDUAL TUMOR | Fisher's exact test |
0.388 (0.646) |
0.386 (0.646) |
RACE | Fisher's exact test |
0.653 (0.784) |
0.592 (0.74) |
ETHNICITY | Fisher's exact test |
0.341 (0.646) |
0.36 (0.646) |
Cluster Labels | 0 | HIGH | LOW |
---|---|---|---|
Number of samples | 265 | 113 | 103 |
Cluster Labels | FC.HIGH.ENRICH | FC.LOW.ENRICH | FC.NO.ENRICH |
---|---|---|---|
Number of samples | 147 | 69 | 265 |
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APOBEC groups file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/APOBEC_Pipelines/LUAD-TP/22552622/__DELETED__1436046:APOBEC_clinical_corr_input_22572022/APOBEC_for_clinical.correlaion.input.categorical.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/LUAD-TP/22506767/LUAD-TP.merged_data.txt
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Number of patients = 481
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Number of selected clinical features = 15
APOBEC classification based on APOBEC_MutLoad_MinEstimate : a. APOBEC non group -- samples with zero value, b. APOBEC high group -- samples above median value in non zero samples, c. APOBEC low group -- samples below median value in non zero samples.
APOBEC classification based on APOBEC_enrich : a. No Enrichmment group -- all samples with BH_Fisher_p-value_tCw > 0.05, b. Low enrichment group -- samples with BH_Fisher_p-value_tCw = < 0.05 and APOBEC_enrich=<2, c. High enrichment group -- samples with BH_Fisher_p-value_tCw =< 0.05 and APOBEC_enrich>2.
For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R
For binary clinical features, two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R
For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.
In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.