This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.
Testing the association between mutation status of 46 genes and 3 clinical features across 83 patients, no significant finding detected with Q value < 0.25.
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No gene mutations related to clinical features.
Clinical Features |
AGE |
RADIATIONS RADIATION REGIMENINDICATION |
NEOADJUVANT THERAPY |
||
nMutated (%) | nWild-Type | t-test | Fisher's exact test | Fisher's exact test | |
POM121 | 3 (4%) | 80 |
0.0611 (1.00) |
0.172 (1.00) |
1 (1.00) |
ZNF285 | 3 (4%) | 80 |
0.51 (1.00) |
1 (1.00) |
1 (1.00) |
MUC4 | 13 (16%) | 70 |
0.974 (1.00) |
1 (1.00) |
1 (1.00) |
C9ORF150 | 3 (4%) | 80 |
0.76 (1.00) |
1 (1.00) |
0.139 (1.00) |
NKX3-1 | 5 (6%) | 78 |
0.463 (1.00) |
1 (1.00) |
1 (1.00) |
FIP1L1 | 3 (4%) | 80 |
0.168 (1.00) |
1 (1.00) |
1 (1.00) |
NDUFS4 | 3 (4%) | 80 |
0.093 (1.00) |
0.0086 (1.00) |
1 (1.00) |
AGT | 3 (4%) | 80 |
0.6 (1.00) |
1 (1.00) |
1 (1.00) |
CCNF | 3 (4%) | 80 |
0.643 (1.00) |
0.172 (1.00) |
0.0052 (0.713) |
DUSP27 | 3 (4%) | 80 |
0.824 (1.00) |
1 (1.00) |
1 (1.00) |
CLSTN1 | 3 (4%) | 80 |
0.093 (1.00) |
0.0086 (1.00) |
1 (1.00) |
TP53 | 5 (6%) | 78 |
0.64 (1.00) |
1 (1.00) |
1 (1.00) |
TPTE2 | 6 (7%) | 77 |
0.561 (1.00) |
0.0398 (1.00) |
0.0247 (1.00) |
FRG1 | 5 (6%) | 78 |
0.19 (1.00) |
0.0272 (1.00) |
0.0168 (1.00) |
ZNF492 | 4 (5%) | 79 |
0.188 (1.00) |
0.224 (1.00) |
1 (1.00) |
YBX1 | 3 (4%) | 80 |
0.784 (1.00) |
1 (1.00) |
1 (1.00) |
SPOP | 4 (5%) | 79 |
0.481 (1.00) |
1 (1.00) |
0.182 (1.00) |
ARHGAP11B | 4 (5%) | 79 |
0.838 (1.00) |
0.224 (1.00) |
0.182 (1.00) |
SCAI | 5 (6%) | 78 |
0.299 (1.00) |
1 (1.00) |
1 (1.00) |
LILRB3 | 4 (5%) | 79 |
0.512 (1.00) |
1 (1.00) |
1 (1.00) |
ZNF814 | 4 (5%) | 79 |
0.527 (1.00) |
0.224 (1.00) |
0.182 (1.00) |
CTNNB1 | 3 (4%) | 80 |
0.992 (1.00) |
0.172 (1.00) |
0.139 (1.00) |
PDE4DIP | 6 (7%) | 77 |
0.605 (1.00) |
1 (1.00) |
1 (1.00) |
PRR21 | 4 (5%) | 79 |
0.00302 (0.417) |
0.224 (1.00) |
0.0102 (1.00) |
NOTCH2NL | 3 (4%) | 80 |
0.562 (1.00) |
0.172 (1.00) |
1 (1.00) |
ANKRD36 | 4 (5%) | 79 |
0.602 (1.00) |
1 (1.00) |
1 (1.00) |
OR6N1 | 3 (4%) | 80 |
0.367 (1.00) |
0.172 (1.00) |
1 (1.00) |
PRIM2 | 4 (5%) | 79 |
0.381 (1.00) |
1 (1.00) |
0.182 (1.00) |
POTEC | 3 (4%) | 80 |
0.647 (1.00) |
1 (1.00) |
1 (1.00) |
LRIT2 | 4 (5%) | 79 |
0.491 (1.00) |
1 (1.00) |
1 (1.00) |
OR4D5 | 3 (4%) | 80 |
0.092 (1.00) |
1 (1.00) |
1 (1.00) |
ZNF98 | 4 (5%) | 79 |
0.964 (1.00) |
0.224 (1.00) |
0.182 (1.00) |
CROCC | 5 (6%) | 78 |
0.885 (1.00) |
1 (1.00) |
1 (1.00) |
CYP2D6 | 4 (5%) | 79 |
0.848 (1.00) |
1 (1.00) |
1 (1.00) |
ATM | 5 (6%) | 78 |
0.882 (1.00) |
0.273 (1.00) |
1 (1.00) |
MLL3 | 7 (8%) | 76 |
0.618 (1.00) |
0.364 (1.00) |
0.302 (1.00) |
TAF1L | 3 (4%) | 80 |
0.142 (1.00) |
1 (1.00) |
1 (1.00) |
PRB1 | 3 (4%) | 80 |
0.353 (1.00) |
1 (1.00) |
1 (1.00) |
CNTNAP5 | 5 (6%) | 78 |
0.488 (1.00) |
1 (1.00) |
1 (1.00) |
BCL6 | 3 (4%) | 80 |
0.0299 (1.00) |
1 (1.00) |
1 (1.00) |
OR5L2 | 3 (4%) | 80 |
0.0989 (1.00) |
1 (1.00) |
1 (1.00) |
TTLL11 | 3 (4%) | 80 |
0.419 (1.00) |
1 (1.00) |
1 (1.00) |
TRIOBP | 3 (4%) | 80 |
0.544 (1.00) |
1 (1.00) |
1 (1.00) |
UGT2B10 | 3 (4%) | 80 |
0.949 (1.00) |
0.172 (1.00) |
1 (1.00) |
SLITRK4 | 3 (4%) | 80 |
0.726 (1.00) |
1 (1.00) |
1 (1.00) |
PRG4 | 4 (5%) | 79 |
0.523 (1.00) |
1 (1.00) |
0.182 (1.00) |
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Mutation data file = PRAD.mutsig.cluster.txt
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Clinical data file = PRAD.clin.merged.picked.txt
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Number of patients = 83
-
Number of significantly mutated genes = 46
-
Number of selected clinical features = 3
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Exclude genes that fewer than K tumors have mutations, K = 3
For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' 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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.