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.
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 |
0.271 (0.778) |
0.0288 (0.711) |
0.399 (0.778) |
0.474 (0.809) |
0.22 (0.755) |
FBXW7 | 22 (39%) | 35 |
0.517 (0.809) |
0.407 (0.778) |
0.579 (0.809) |
0.165 (0.755) |
1 (1.00) |
PPP2R1A | 16 (28%) | 41 |
0.659 (0.809) |
0.631 (0.809) |
0.384 (0.778) |
0.268 (0.778) |
0.535 (0.809) |
KRAS | 7 (12%) | 50 |
0.359 (0.778) |
0.576 (0.809) |
0.692 (0.809) |
0.0824 (0.755) |
0.557 (0.809) |
PTEN | 11 (19%) | 46 |
0.389 (0.778) |
0.504 (0.809) |
0.736 (0.844) |
0.686 (0.809) |
0.678 (0.809) |
RB1 | 6 (11%) | 51 |
0.169 (0.755) |
0.355 (0.778) |
0.0849 (0.755) |
0.0154 (0.711) |
0.329 (0.778) |
ZBTB7B | 6 (11%) | 51 |
0.134 (0.755) |
0.649 (0.809) |
0.399 (0.778) |
1 (1.00) |
0.218 (0.755) |
PIK3R1 | 6 (11%) | 51 |
0.6 (0.809) |
0.207 (0.755) |
0.653 (0.809) |
0.863 (0.949) |
0.219 (0.755) |
ARHGAP35 | 6 (11%) | 51 |
0.539 (0.809) |
0.0983 (0.755) |
0.675 (0.809) |
0.41 (0.778) |
0.0388 (0.711) |
PIK3CA | 20 (35%) | 37 |
0.206 (0.755) |
0.136 (0.755) |
1 (1.00) |
0.106 (0.755) |
0.755 (0.848) |
MAMLD1 | 4 (7%) | 53 |
0.984 (1.00) |
0.364 (0.778) |
1 (1.00) |
0.436 (0.799) |
0.304 (0.778) |
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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/22569432/transformed.cor.cli.txt
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Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/UCS-TP/22507158/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.