This pipeline computes the correlation between significantly recurrent gene mutations and molecular subtypes.
Testing the association between mutation status of 3 genes and 14 molecular subtypes across 316 patients, no significant finding detected with P value < 0.05 and Q value < 0.25.
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No gene mutations related to molecuar subtypes.
Clinical Features |
MRNA CNMF |
MRNA CHIERARCHICAL |
MIR CNMF |
MIR CHIERARCHICAL |
CN CNMF |
METHLYATION CNMF |
RPPA CNMF |
RPPA CHIERARCHICAL |
MRNASEQ CNMF |
MRNASEQ CHIERARCHICAL |
MIRSEQ CNMF |
MIRSEQ CHIERARCHICAL |
MIRSEQ MATURE CNMF |
MIRSEQ MATURE CHIERARCHICAL |
||
nMutated (%) | nWild-Type | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | Fisher's exact test | |
TP53 | 276 (87%) | 40 |
0.772 (1.00) |
0.465 (1.00) |
0.245 (1.00) |
0.187 (1.00) |
0.716 (1.00) |
0.774 (1.00) |
0.411 (1.00) |
0.313 (1.00) |
0.779 (1.00) |
0.898 (1.00) |
0.326 (1.00) |
0.186 (1.00) |
0.147 (1.00) |
0.734 (1.00) |
TBP | 4 (1%) | 312 |
1 (1.00) |
1 (1.00) |
0.819 (1.00) |
0.476 (1.00) |
0.0357 (1.00) |
0.205 (1.00) |
0.131 (1.00) |
0.872 (1.00) |
1 (1.00) |
1 (1.00) |
0.689 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
SRC | 4 (1%) | 312 |
0.834 (1.00) |
1 (1.00) |
0.298 (1.00) |
0.383 (1.00) |
0.127 (1.00) |
0.392 (1.00) |
0.483 (1.00) |
0.325 (1.00) |
0.605 (1.00) |
0.324 (1.00) |
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Mutation data file = OV-TP.mutsig.cluster.txt
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Molecular subtypes file = OV-TP.transferedmergedcluster.txt
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Number of patients = 316
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Number of significantly mutated genes = 3
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Number of Molecular subtypes = 14
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Exclude genes that fewer than K tumors have mutations, K = 3
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.