This is an overview of Uterine Corpus Endometrioid Carcinoma analysis pipelines from Firehose run "15 January 2014".
Note: These results are offered to the community as an additional reference point, enabling a wide range of cancer biologists, clinical investigators, and genome and computational scientists to easily incorporate TCGA into the backdrop of ongoing research. While every effort is made to ensure that Firehose input data and algorithms are of the highest possible quality, these analyses have not been reviewed by domain experts.
-
Sequence and Copy Number Analyses
-
LowPass Copy number analysis (GISTIC2)
View Report | There were 106 tumor samples used in this analysis: 18 significant arm-level results, 9 significant focal amplifications, and 0 significant focal deletions were found. -
Mutation Analysis (MutSig v1.5)
View Report | -
Mutation Analysis (MutSig v2.0 and MutSigCV v0.9 merged result)
View Report | -
Mutation Analysis (MutSig v2.0)
View Report | -
Mutation Analysis (MutSigCV v0.9)
View Report | -
Mutation Assessor
View Report | -
SNP6 Copy number analysis (GISTIC2)
View Report | There were 514 tumor samples used in this analysis: 28 significant arm-level results, 48 significant focal amplifications, and 50 significant focal deletions were found. -
Correlations to Clinical Parameters
-
Correlation between aggregated molecular cancer subtypes and selected clinical features
View Report | Testing the association between subtypes identified by 12 different clustering approaches and 5 clinical features across 480 patients, 27 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between copy number variation genes (focal events) and selected clinical features
View Report | Testing the association between copy number variation 98 focal events and 5 clinical features across 472 patients, 176 significant findings detected with Q value < 0.25. -
Correlation between copy number variations of arm-level result and selected clinical features
View Report | Testing the association between copy number variation 80 arm-level events and 5 clinical features across 472 patients, 83 significant findings detected with Q value < 0.25. -
Correlation between gene methylation status and clinical features
View Report | Testing the association between 20424 genes and 5 clinical features across 364 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes. -
Correlation between gene mutation status and selected clinical features
View Report | Testing the association between mutation status of 33 genes and 5 clinical features across 248 patients, 10 significant findings detected with Q value < 0.25. -
Correlation between miRseq expression and clinical features
View Report | Testing the association between 555 miRs and 5 clinical features across 471 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one miRs. -
Correlation between mRNA expression and clinical features
View Report | Testing the association between 17814 genes and 5 clinical features across 54 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes. -
Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 18555 genes and 5 clinical features across 471 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes. -
Correlation between RPPA expression and clinical features
View Report | Testing the association between 166 genes and 5 clinical features across 200 samples, statistically thresholded by Q value < 0.05, 3 clinical features related to at least one genes. -
Clustering Analyses
-
Clustering of copy number data by focal peak region with log2 ratio: consensus NMF
View Report | The most robust consensus NMF clustering of 514 samples using the 98 copy number focal regions was identified for k = 6 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution. -
Clustering of copy number data by peak region with threshold value: consensus NMF
View Report | The most robust consensus NMF clustering of 514 samples using the 98 copy number focal regions was identified for k = 3 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution. -
Clustering of Methylation: consensus NMF
View Report | The 10070 most variable methylated genes were selected based on variation. The variation cutoff are set for each tumor type empirically by fitting a bimodal distriution. For genes with multiple methylation probes, we chose the most variable one to represent the gene. Consensus NMF clustering of 406 samples and 10070 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of miRseq mature expression: consensus hierarchical
View Report | We filtered the data to 259 most variable miRs. Consensus average linkage hierarchical clustering of 386 samples and 259 miRs identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of miRseq mature expression: consensus NMF
View Report | We filtered the data to 259 most variable miRs. Consensus NMF clustering of 386 samples and 259 miRs identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of miRseq precursor expression: consensus hierarchical
View Report | We filtered the data to 150 most variable miRs. Consensus average linkage hierarchical clustering of 514 samples and 150 miRs identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of miRseq precursor expression: consensus NMF
View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 514 samples and 150 miRs identified 5 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of mRNA expression: consensus hierarchical
View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 54 samples and 1500 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of mRNA expression: consensus NMF
View Report | The most robust consensus NMF clustering of 54 samples using the 1500 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution. -
Clustering of mRNAseq gene expression: consensus hierarchical
View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 513 samples and 1500 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of mRNAseq gene expression: consensus NMF
View Report | The most robust consensus NMF clustering of 513 samples using the 1500 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution. -
Clustering of RPPA data: consensus hierarchical
View Report | 166 proteins were selected. Consensus average linkage hierarchical clustering of 200 samples and 166 proteins identified 2 subtypes with the stability of the clustering increasing for k = 2 to k = 8 and the average silhouette width calculation for selecting the robust clusters. -
Clustering of RPPA data: consensus NMF
View Report | The most robust consensus NMF clustering of 200 samples using 166 proteins was identified for k = 6 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution. -
Pathway Analyses
-
Association of mutation, copy number alteration, and subtype markers with pathways
View Report | There are 28 genes with significant mutation (Q value <= 0.1) and 315 genes with significant copy number alteration (Q value <= 0.25). The identified marker genes (Q value <= 0.01 or within top 2000) are 238 for subtype 1, 238 for subtype 2, 238 for subtype 3. Pathways significantly enriched with these genes (Q value <= 0.01) are identified : -
HotNet pathway analysis of mutation and copy number data
View Report | There were 56 significant subnetworks identified in HotNet analysis. -
PARADIGM pathway analysis of mRNA expression and copy number data
View Report | There were 27 significant pathways identified in this analysis. -
PARADIGM pathway analysis of mRNA expression data
View Report | There were 35 significant pathways identified in this analysis. -
PARADIGM pathway analysis of mRNASeq expression and copy number data
View Report | There were 59 significant pathways identified in this analysis. -
PARADIGM pathway analysis of mRNASeq expression data
View Report | There were 52 significant pathways identified in this analysis. -
Other Correlation Analyses
-
Correlation between copy number variation genes (focal events) and molecular subtypes
View Report | Testing the association between copy number variation 40 focal events and 12 molecular subtypes across 514 patients, 316 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between copy number variations of arm-level result and molecular subtypes
View Report | Testing the association between copy number variation 80 arm-level events and 12 molecular subtypes across 514 patients, 396 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between gene mutation status and molecular subtypes
View Report | Testing the association between mutation status of 33 genes and 12 molecular subtypes across 248 patients, 36 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between mRNA expression and DNA methylation
View Report | The top 25 correlated methylation probes per gene are displayed. Total number of matched samples = 400. Number of gene expression samples = 513. Number of methylation samples = 406. -
Correlations between copy number and mRNA expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.09339, -0.00978, 0.0539, 0.11134, 0.16765, 0.2245, 0.2873, 0.35928, 0.4528, respectively. -
Correlations between copy number and mRNAseq expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 996, 1512, 1956, 2411, 2933, 3468.6, 4010.7, 4618, 5345, respectively.
-
Summary Report Date = Fri Feb 28 13:07:26 2014
-
Protection = FALSE