Analysis Overview
Uveal Melanoma (Primary solid tumor)
13 July 2018  |  None
Maintainer Information
Maintained by Broad Institute GDAC (Broad Institute of MIT & Harvard)
Overview
Introduction

This is an overview of Uveal Melanoma analysis pipelines from FireCloud run "13 July 2018".

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 FireCloud 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 80 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).

    • Mutation Analysis (MutSig 2CV v3.1 hg38 beta)
      View Report | 

    • Mutation Assessor
      View Report | 

    • Mutation Signature Analysis
      View Report | Our analysis idenfied 1 solution(s) of mutational signatures across 80 samples by BayesNMF method.

    • SNP6 Copy number analysis (GISTIC2)
      View Report | There were 80 tumor samples used in this analysis: 41 significant arm-level results, 3 significant focal amplifications, and 18 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 7 clinical features across 80 patients, 13 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 ENRICH' and 7 clinical features across 80 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 7 clinical features across 80 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 2 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 21 focal events and 7 clinical features across 80 patients, 10 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 51 arm-level events and 7 clinical features across 80 patients, 10 significant findings 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 7 clinical features across 80 patients, 2 significant findings detected with Q value < 0.25.

    • Correlation between mRNAseq expression and clinical features
      View Report | Testing the association between 18131 genes and 7 clinical features across 80 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 3 clinical features related to at least one genes.

    • Correlation between mutation rate and clinical features
      View Report | Testing the association between 2 variables and 8 clinical features across 80 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 1 clinical feature related to at least one variables.

  • Clustering Analyses

    • Clustering of copy number data by focal peak region with absolute value: consensus NMF
      View Report | The most robust consensus NMF clustering of 80 samples using the 21 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 copy number data by peak region with threshold value: consensus NMF
      View Report | The most robust consensus NMF clustering of 80 samples using the 21 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.

    • 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 80 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 80 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 miR mature expression: consensus hierarchical
      View Report | Median absolute deviation (MAD) was used to select 278 most variable miRs. Consensus ward linkage hierarchical clustering of 80 samples and 278 miRs identified 5 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 278 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 80 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 80 samples and 2500 genes identified 4 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

  • Other Analyses

    • Aggregate_Analysis_Features
      View Report | 79 samples and 228 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 754 miRs and 18131 mRNAs across 80 samples. After 2 filtering steps, the number of 43 miR:gene pairs were detected.

    • Methylation__HM450_Clustering_CNMF
      View Report | The most robust consensus NMF clustering of 80 samples using the 9550 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.

    • 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 80 samples and 2500 genes identified 3 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

    • Pathway_GSEA_mRNA
      View Report | basic data info

  • Other Correlation Analyses

    • Correlation between copy number variation genes (focal events) and molecular subtypes
      View Report | Testing the association between copy number variation 21 focal events and 10 molecular subtypes across 80 patients, 131 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 51 arm-level events and 10 molecular subtypes across 80 patients, 118 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 80 patients, 33 significant findings detected with P value < 0.05 and Q value < 0.25.

Methods & Data
Input
  • Summary Report Date = Thu Sep 13 08:45:59 2018

  • Protection = FALSE