This pipeline computes the correlation between significant copy number variation (cnv focal) genes and molecular subtypes.
Testing the association between copy number variation 2 focal events and 10 molecular subtypes across 66 patients, no significant finding detected with P value < 0.05 and Q value < 0.25.
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No focal cnvs related to molecuar subtypes.
Clinical Features |
CN CNMF |
METHLYATION CNMF |
RPPA CNMF |
RPPA CHIERARCHICAL |
MRNASEQ CNMF |
MRNASEQ CHIERARCHICAL |
MIRSEQ CNMF |
MIRSEQ CHIERARCHICAL |
MIRSEQ MATURE CNMF |
MIRSEQ MATURE CHIERARCHICAL |
||
nCNV (%) | 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 | |
amp 8q23 3 | 19 (29%) | 47 |
0.232 (0.421) |
0.292 (0.421) |
0.189 (0.421) |
0.0442 (0.295) |
0.0322 (0.295) |
0.0247 (0.295) |
0.642 (0.677) |
0.228 (0.421) |
0.1 (0.402) |
0.1 (0.402) |
amp 15q22 31 | 23 (35%) | 43 |
0.28 (0.421) |
0.643 (0.677) |
0.204 (0.421) |
0.372 (0.465) |
0.293 (0.421) |
0.18 (0.421) |
0.905 (0.905) |
0.295 (0.421) |
0.446 (0.524) |
0.318 (0.424) |
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Copy number data file = all_lesions.txt from GISTIC pipeline
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Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/KICH-TP/22507963/transformed.cor.cli.txt
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Molecular subtype file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/KICH-TP/22539844/KICH-TP.transferedmergedcluster.txt
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Number of patients = 66
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Number of significantly focal cnvs = 2
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Number of molecular subtypes = 10
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Exclude genes that fewer than K tumors have alterations, 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.