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 14 clinical features across 288 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.
Table 1. Get Full Table Overview of the association between APOBEC groups by 2 different APOBEC scores and 14 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.
|
Clinical Features |
Statistical Tests |
APOBEC MUTLOAD MINESTIMATE |
APOBEC ENRICH |
| Time from Specimen Diagnosis to Death | logrank test |
0.12 (0.419) |
0.486 (0.833) |
| Time to Death | logrank test |
0.353 (0.779) |
0.579 (0.833) |
| YEARS TO BIRTH | Kruskal-Wallis (anova) |
0.0657 (0.263) |
0.734 (0.833) |
| PRIMARY SITE OF DISEASE | Fisher's exact test |
0.444 (0.833) |
0.735 (0.833) |
| NEOPLASM DISEASESTAGE | Fisher's exact test |
0.617 (0.833) |
0.336 (0.779) |
| PATHOLOGY T STAGE | Fisher's exact test |
0.626 (0.833) |
0.243 (0.757) |
| PATHOLOGY N STAGE | Fisher's exact test |
0.35 (0.779) |
0.752 (0.833) |
| PATHOLOGY M STAGE | Fisher's exact test |
0.725 (0.833) |
0.654 (0.833) |
| MELANOMA ULCERATION | Fisher's exact test |
0.0548 (0.256) |
0.0278 (0.256) |
| MELANOMA PRIMARY KNOWN | Fisher's exact test |
0.362 (0.779) |
0.669 (0.833) |
| BRESLOW THICKNESS | Kruskal-Wallis (anova) |
0.868 (0.9) |
0.773 (0.833) |
| GENDER | Fisher's exact test |
0.0213 (0.256) |
0.458 (0.833) |
| RACE | Fisher's exact test |
0.048 (0.256) |
0.0377 (0.256) |
| ETHNICITY | Fisher's exact test |
1 (1.00) |
0.0164 (0.256) |
Table S1. Description of APOBEC group #1: 'APOBEC MUTLOAD MINESTIMATE'
| Cluster Labels | 0 | HIGH | LOW |
|---|---|---|---|
| Number of samples | 85 | 70 | 133 |
Table S2. Description of APOBEC group #2: 'APOBEC ENRICH'
| Cluster Labels | FC.HIGH.SIG | FC.LOW.NONSIG | FC.NEUTRAL |
|---|---|---|---|
| Number of samples | 4 | 83 | 201 |
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APOBEC groups file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/APOBEC_Pipelines/SKCM-TM/15234021/APOBEC_clinical_corr_input_15234069/APOBEC_for_clinical.correlaion.input.categorical.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/SKCM-TM/15087681/SKCM-TM.merged_data.txt
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Number of patients = 288
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Number of selected clinical features = 14
APOBEC classification based on APOBEC_MutLoad_MinEstimate : a. APOBEC non group -- samples with zero value, b. APOBEC hig group -- samples above median value in non zero samples, c. APOBEC hig 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. Small enrichment group -- samples with BH_Fisher_p-value_tCw = < 0.05 and APOBEC_enrich=<2, c. High enrichment gruop -- 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.