Analysis Overview for Head and Neck Squamous Cell Carcinoma
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)
Overview
Introduction

This is the analysis overview for Firehose run "24 October 2012".

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

- Clustering Analyses

- Clustering of Methylation: consensus NMF
  View Report | The 4424 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 310 samples and 4424 genes identified 8 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 212 samples using the 150 most variable proteins 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 RPPA data: consensus hierarchical
  View Report | The 150 most variable proteins were selected. Consensus average linkage hierarchical clustering of 212 samples and 150 proteins 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 303 samples using the 1500 most variable genes 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 mRNAseq gene expression: consensus hierarchical
  View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 303 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 miRseq expression: consensus NMF
  View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 309 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 expression: consensus hierarchical
  View Report | We filtered the data to 150 most variable miRs. Consensus average linkage hierarchical clustering of 309 samples and 150 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.

- Correlation Analyses

- Correlation between gene methylation status and clinical features
  View Report | Testing the association between 17419 genes and 8 clinical features across 299 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

- Correlation between molecular cancer subtypes and selected clinical features
  View Report | Testing the association between subtypes identified by 7 different clustering approaches and 8 clinical features across 311 patients, 9 significant findings detected with P value < 0.05.

- Correlation between RPPA expression and clinical features
  View Report | Testing the association between 174 genes and 8 clinical features across 212 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

- Correlation between mRNAseq expression and clinical features
  View Report | Testing the association between 18388 genes and 8 clinical features across 302 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

- Correlation between miRseq expression and clinical features
  View Report | Testing the association between 564 genes and 8 clinical features across 308 samples, statistically thresholded by Q value < 0.05, 4 clinical features related to at least one genes.

- Correlation between mRNA expression and DNA methylation
  View Report | The top 25 correlated methylation probes per gene are displayed. Total number of matched samples = 303. Number of gene expression samples = 303. Number of methylation samples = 303.

Methods & Data
Input

- Run Prefix = analyses__2012_10_24

- Summary Report Date = Fri Nov 16 16:03:01 2012

- Protection = FALSE

Copyright © 2012 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
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