Analysis Overview
Pheochromocytoma and Paraganglioma (Primary solid tumor)
02 April 2015 | analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1G15ZXB
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Analysis Overview for Pheochromocytoma and Paraganglioma (Primary solid tumor cohort) - 02 April 2015. Broad Institute of MIT and Harvard. doi:10.7908/C1G15ZXB
Overview
Introduction

This is an overview of Pheochromocytoma and Paraganglioma analysis pipelines from Firehose run "02 April 2015".

Summary

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.

Results

- Sequence and Copy Number Analyses

- Analysis of mutagenesis by APOBEC cytidine deaminases (P-MACD).
  View Report | There are 178 tumor samples in this analysis. The Benjamini-Hochberg-corrected p-value for enrichment of the APOBEC mutation signature in 0 samples is <=0.05. Out of these, 0 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).

- CHASM 1.0.5 (Cancer-Specific High-throughput Annotation of Somatic Mutations)
  View Report | There are 1756 mutations identified by MuTect and 200 mutations with significant functional impact at BHFDR <= 0.25.

- Mutation Analysis (MutSig 2CV v3.1)
  View Report |

- Mutation Analysis (MutSig v1.5)
  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 162 tumor samples used in this analysis: 19 significant arm-level results, 7 significant focal amplifications, and 21 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 10 different clustering approaches and 5 clinical features across 179 patients, one significant finding 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 28 focal events and 4 clinical features across 162 patients, one 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 69 arm-level events and 4 clinical features across 162 patients, one significant finding detected with Q value < 0.25.

- Correlation between gene methylation status and clinical features
  View Report | Testing the association between 19848 genes and 5 clinical features across 179 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 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 9 genes and 5 clinical features across 178 patients, 2 significant findings detected with Q value < 0.25.

- Correlation between miRseq expression and clinical features
  View Report | Testing the association between 524 miRs and 5 clinical features across 179 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 clinical features related to at least one miRs.

- Correlation between mRNAseq expression and clinical features
  View Report | Testing the association between 17994 genes and 5 clinical features across 179 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 clinical features related to at least one genes.

- Correlation between mutation rate and clinical features
  View Report | Testing the association between 2 variables and 6 clinical features across 178 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 4 clinical features related to at least one variables.

- Correlation between RPPA expression and clinical features
  View Report | Testing the association between 192 genes and 3 clinical features across 79 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 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 162 samples using the 28 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 copy number data by peak region with threshold value: consensus NMF
  View Report | The most robust consensus NMF clustering of 162 samples using the 28 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 11233 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 179 samples and 11233 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 | Median absolute deviation (MAD) was used to select 647 most variable miRs. Consensus ward linkage hierarchical clustering of 178 samples and 647 miRs identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

- Clustering of miRseq mature expression: consensus NMF
  View Report | We filtered the data to 647 most variable miRs. Consensus NMF clustering of 178 samples and 647 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 miRseq precursor expression: consensus hierarchical
  View Report | Median absolute deviation (MAD) was used to select 131 most variable miRs. Consensus ward linkage hierarchical clustering of 179 samples and 131 miRs identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

- Clustering of miRseq precursor expression: consensus NMF
  View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 179 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 mRNAseq gene expression: consensus hierarchical
  View Report | Median absolute deviation (MAD) was used to select 1500 most variable genes. Consensus ward linkage hierarchical clustering of 179 samples and 1500 genes identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

- Clustering of mRNAseq gene expression: consensus NMF
  View Report | The most robust consensus NMF clustering of 179 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 | Median absolute deviation (MAD) was used to select 192 most variable proteins. Consensus ward linkage hierarchical clustering of 79 samples and 192 proteins identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

- Clustering of RPPA data: consensus NMF
  View Report | The most robust consensus NMF clustering of 79 samples using 192 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.

- Other Analyses

- Aggregate Analysis Features
  View Report | 178 samples and 205 features are included in this feature table. The figures below show which genomic pair events are co-occurring and which are mutually-exclusive.

- Identification of putative miR direct targets by sequencing data
  View Report | The CLR algorithm was applied on 759 miRs and 17994 mRNAs across 179 samples. After 2 filtering steps, the number of 112 miR:genes pairs were detected.

- Pathway Analyses

- GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in PCPG-TP
  View Report | basic data info

- PARADIGM pathway analysis of mRNASeq expression and copy number data
  View Report | There were 31 significant pathways identified in this analysis.

- PARADIGM pathway analysis of mRNASeq expression data
  View Report | There were 39 significant pathways identified in this analysis.

- Significant over-representaion of pathway genesets for a given gene list
  View Report | For a given gene list, a hypergeometric test was tried to find significant overlapping canonical pathway gene sets. In terms of FDR adjusted p.values, no significant overlapping gene sets are found.

- Other Correlation Analyses

- Correlation between copy number variation genes (focal events) and molecular subtypes
  View Report | Testing the association between copy number variation 28 focal events and 10 molecular subtypes across 162 patients, 94 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 69 arm-level events and 10 molecular subtypes across 162 patients, 139 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 9 genes and 10 molecular subtypes across 178 patients, 32 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 = 179. Number of gene expression samples = 179. Number of methylation samples = 179.

- Correlations between copy number and mRNAseq expression
  View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 750, 1616.6, 2174, 2723.2, 3227, 3769, 4346.6, 5033.4, 5899.2, respectively.

Methods & Data
Input

- Summary Report Date = Sat Aug 15 14:39:43 2015

- Protection = FALSE

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