This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.
Testing the association between mutation status of 11 genes and 5 clinical features across 57 patients, no significant finding detected with Q value < 0.25.
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No gene mutations related to clinical features.
Table 1. Get Full Table Overview of the association between mutation status of 11 genes and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.
|
Clinical Features |
Time to Death |
YEARS TO BIRTH |
RADIATION THERAPY |
HISTOLOGICAL TYPE |
RACE | ||
| nMutated (%) | nWild-Type | logrank test | Wilcoxon-test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
| TP53 | 51 (89%) | 6 |
0.289 (0.803) |
0.0288 (0.725) |
0.406 (0.803) |
0.474 (0.814) |
0.222 (0.762) |
| FBXW7 | 22 (39%) | 35 |
0.556 (0.814) |
0.407 (0.803) |
0.589 (0.814) |
0.161 (0.752) |
1 (1.00) |
| PPP2R1A | 16 (28%) | 41 |
0.632 (0.814) |
0.631 (0.814) |
0.553 (0.814) |
0.267 (0.803) |
0.535 (0.814) |
| KRAS | 7 (12%) | 50 |
0.343 (0.803) |
0.576 (0.814) |
0.696 (0.814) |
0.084 (0.752) |
0.562 (0.814) |
| PTEN | 11 (19%) | 46 |
0.403 (0.803) |
0.504 (0.814) |
0.739 (0.847) |
0.689 (0.814) |
0.677 (0.814) |
| RB1 | 6 (11%) | 51 |
0.164 (0.752) |
0.355 (0.803) |
0.0901 (0.752) |
0.0152 (0.725) |
0.329 (0.803) |
| ZBTB7B | 6 (11%) | 51 |
0.127 (0.752) |
0.649 (0.814) |
0.406 (0.803) |
1 (1.00) |
0.217 (0.762) |
| PIK3R1 | 6 (11%) | 51 |
0.633 (0.814) |
0.207 (0.762) |
0.659 (0.814) |
0.862 (0.93) |
0.219 (0.762) |
| ARHGAP35 | 6 (11%) | 51 |
0.548 (0.814) |
0.0983 (0.752) |
0.672 (0.814) |
0.409 (0.803) |
0.0396 (0.725) |
| PIK3CA | 20 (35%) | 37 |
0.161 (0.752) |
0.136 (0.752) |
0.786 (0.865) |
0.105 (0.752) |
0.756 (0.849) |
| MAMLD1 | 4 (7%) | 53 |
0.978 (1.00) |
0.364 (0.803) |
1 (1.00) |
0.43 (0.814) |
0.305 (0.803) |
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Mutation data file = sample_sig_gene_table.txt from Mutsig_2CV pipeline
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Processed Mutation data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/UCS-TP/20063030/transformed.cor.cli.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/UCS-TP/19775681/UCS-TP.merged_data.txt
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Number of patients = 57
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Number of significantly mutated genes = 11
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Number of selected clinical features = 5
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Exclude genes that fewer than K tumors have mutations, K = 3
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 or multi-class clinical features (nominal or ordinal), 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.