Analysis Overview - Esophageal Carcinoma (Primary solid tumor)

Analysis Overview

Esophageal Carcinoma (Primary solid tumor)

23 September 2013 | analyses__2013_09_23

Maintainer Information

Citation Information

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Analysis Overview for Esophageal Carcinoma (Primary solid tumor cohort) - 23 September 2013. Broad Institute of MIT and Harvard. doi:10.7908/C14M92VZ

Overview

Introduction

This is an overview of Esophageal Carcinoma analysis pipelines from Firehose run "23 September 2013".

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

LowPass Copy number analysis (GISTIC2)
View Report | There were 15 tumor samples used in this analysis: 8 significant arm-level results, 1 significant focal amplifications, and 0 significant focal deletions were found.
SNP6 Copy number analysis (GISTIC2)
View Report | There were 63 tumor samples used in this analysis: 23 significant arm-level results, 25 significant focal amplifications, and 40 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 2 different clustering approaches and 7 clinical features across 19 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 63 focal events and 7 clinical features across 19 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 54 arm-level events and 7 clinical features across 19 patients, 3 significant findings detected with Q value < 0.25.

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 63 samples using the 65 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 8841 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 63 samples and 8841 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.

Other Correlation Analyses

Correlation between copy number variation genes and molecular subtypes
View Report | Testing the association between copy number variation of 65 peak regions and 2 molecular subtypes across 63 patients, 6 significant findings detected with 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 71 arm-level results and 2 molecular subtypes across 63 patients, 5 significant findings detected with Q value < 0.25.

Methods & Data

Input

Summary Report Date = Mon Oct 21 14:49:29 2013
Protection = FALSE

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