This is an overview of Glioblastoma Multiforme analysis pipelines from FireCloud run "17 October 2017".
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 FireCloud input data and algorithms are of the highest possible quality, these analyses have not been reviewed by domain experts.
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Sequence and Copy Number Analyses
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SNP6 Copy number analysis (GISTIC2)
View Report | There were 590 tumor samples used in this analysis: 40 significant arm-level results, 24 significant focal amplifications, and 42 significant focal deletions were found. -
Correlations to Clinical Parameters
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Correlation between aggregated molecular cancer subtypes and selected clinical features
View Report | Testing the association between subtypes identified by 8 different clustering approaches and 8 clinical features across 596 patients, 2 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 66 focal events and 8 clinical features across 590 patients, 26 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 82 arm-level events and 8 clinical features across 590 patients, 14 significant findings detected with Q value < 0.25. -
Clustering Analyses
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Clustering of copy number data by focal peak region with absolute value: consensus NMF
View Report | The most robust consensus NMF clustering of 590 samples using the 66 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 10 and used the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters. -
Clustering of copy number data by peak region with threshold value: consensus NMF
View Report | The most robust consensus NMF clustering of 590 samples using the 66 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 10 and used the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters. -
Clustering of lincRNA expression: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 2500 most variable lincRNAs. Consensus ward linkage hierarchical clustering of 153 samples and 2500 lincRNAs identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Clustering of lincRNA expression: consensus NMF
View Report | The most robust consensus NMF clustering of 154 samples using the 2500 most variable lincRNAs was identified for k = 5 clusters. We computed the clustering for k = 2 to k = 10 and used the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters. -
Clustering of protein coding gene expression: consensus NMF
View Report | The most robust consensus NMF clustering of 154 samples using the 2500 most variable genes was identified for k = 5 clusters. We computed the clustering for k = 2 to k = 10 and used the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters. -
Clustering of Protein-coding gene expression: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 2500 most variable genes. Consensus ward linkage hierarchical clustering of 153 samples and 2500 genes identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Other Analyses
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Methylation__HM27_Clustering_CNMF
View Report | The most robust consensus NMF clustering of 287 samples using the 2649 most variable genes was identified for k = 8 clusters. We computed the clustering for k = 2 to k = 10 and used the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters. -
Methylation__HM27_Clustering_Consensus_Plus
View Report | Median absolute deviation (MAD) was used to select 2500 most variable genes. Consensus ward linkage hierarchical clustering of 286 samples and 2500 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Methylation__HM450_Clustering_CNMF
View Report | The most robust consensus NMF clustering of 140 samples using the 9810 most variable genes was identified for k = 3 clusters. We computed the clustering for k = 2 to k = 10 and used the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters. -
Methylation__HM450_Clustering_Consensus_Plus
View Report | Median absolute deviation (MAD) was used to select 2500 most variable genes. Consensus ward linkage hierarchical clustering of 139 samples and 2500 genes identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Other Correlation Analyses
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Correlation between copy number variation genes (focal events) and molecular subtypes
View Report | Testing the association between copy number variation 66 focal events and 8 molecular subtypes across 590 patients, 220 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 82 arm-level events and 8 molecular subtypes across 590 patients, 227 significant findings detected with P value < 0.05 and Q value < 0.25.
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Summary Report Date = Thu Dec 14 13:48:36 2017
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Protection = FALSE