This is an overview of Adrenocortical Carcinoma 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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Analysis of mutagenesis by APOBEC cytidine deaminases (P-MACD).
View Report | There are 92 tumor samples in this analysis. The Benjamini-Hochberg-corrected p-value for enrichment of the APOBEC mutation signature in 5 samples is <=0.05. Out of these, 4 have enrichment values >2, which implies that in such samples at least 50% of APOBEC signature mutations have been in fact made by APOBEC enzyme(s). -
Mutation Assessor
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Mutation Signature Analysis
View Report | Our analysis idenfied 2 solution(s) of mutational signatures across 92 samples by BayesNMF method. -
SNP6 Copy number analysis (GISTIC2)
View Report | There were 90 tumor samples used in this analysis: 34 significant arm-level results, 8 significant focal amplifications, and 32 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 10 different clustering approaches and 12 clinical features across 92 patients, 27 significant findings detected with P value < 0.05 and Q value < 0.25. -
Correlation between APOBEC groups and selected clinical features
View Report | Testing the association between APOBEC groups identified by 2 different apobec score and 12 clinical features across 92 patients, no significant finding detected with P value < 0.05 and Q value < 0.25. -
Correlation between APOBEC signature variables and clinical features
View Report | Testing the association between 3 variables and 12 clinical features across 92 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one variables. -
Correlation between copy number variation genes (focal events) and selected clinical features
View Report | Testing the association between copy number variation 40 focal events and 12 clinical features across 90 patients, no significant finding 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 12 clinical features across 90 patients, no significant finding detected with Q value < 0.25. -
Correlation between gene mutation status and selected clinical features
View Report | Testing the association between mutation status of 7 genes and 12 clinical features across 92 patients, one significant finding detected with Q value < 0.25. -
Correlation between mutation rate and clinical features
View Report | Testing the association between 2 variables and 13 clinical features across 92 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 6 clinical features related to at least one variables. -
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 90 samples using the 40 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. -
Clustering of copy number data by peak region with threshold value: consensus NMF
View Report | The most robust consensus NMF clustering of 90 samples using the 40 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 78 samples and 2500 lincRNAs identified 3 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 79 samples using the 2500 most variable lincRNAs 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. -
Clustering of miR mature expression: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 284 most variable miRs. Consensus ward linkage hierarchical clustering of 79 samples and 284 miRs identified 7 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Clustering of miR mature expression: consensus NMF
View Report | The most robust consensus NMF clustering of 80 samples using the 284 most variable miRs 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 79 samples using the 2500 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 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 78 samples and 2500 genes identified 7 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Other Analyses
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Identification of putative miR direct targets by sequencing data
View Report | The CLR algorithm was applied on 756 miRs and 18543 mRNAs across 79 samples. After 2 filtering steps, the number of 32 miR:gene pairs were detected. -
Methylation__HM450_Clustering_CNMF
View Report | The most robust consensus NMF clustering of 80 samples using the 18655 most variable genes was identified for k = 7 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 79 samples and 2500 genes identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10. -
Mutation_MutSig2CV
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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 40 focal events and 10 molecular subtypes across 90 patients, 138 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 10 molecular subtypes across 90 patients, 297 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 7 genes and 10 molecular subtypes across 92 patients, 9 significant findings detected with P value < 0.05 and Q value < 0.25.
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Summary Report Date = Thu Dec 14 13:38:16 2017
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Protection = FALSE