Analysis Overview for Thyroid Adenocarcinoma
(primary solid tumor cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Overview
Introduction

This is the analysis overview for Firehose run "18 March 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

- Copy number analysis (GISTIC2)
  View Report | There were 432 tumor samples used in this analysis: 18 significant arm-level results, 0 significant focal amplifications, and 31 significant focal deletions were found.

- Mutation Analysis (MutSigCV v0.9)
  View Report |

- Mutation Analysis (MutSig vS2N)
  View Report |

- Clustering Analyses

- Clustering of copy number data: consensus NMF
  View Report | The most robust consensus NMF clustering of 432 samples using the 31 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 5143 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 500 samples and 5143 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 RPPA data: consensus NMF
  View Report | The most robust consensus NMF clustering of 224 samples using the 175 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 175 most variable proteins were selected. Consensus average linkage hierarchical clustering of 224 samples and 175 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 409 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 mRNAseq gene expression: consensus hierarchical
  View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 409 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 411 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 411 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.

- Correlation Analyses

- Preprocessing of clinical data
  View Report | Clinical data for tier 1 clinical variables are generated.

- Correlation between copy number variations of arm-level result and selected clinical features
  View Report | Testing the association between copy number variation 36 arm-level results and 15 clinical features across 303 patients, 27 significant findings detected with Q value < 0.25.

- Correlation between copy number variation genes (focal) and selected clinical features
  View Report | Testing the association between copy number variation 24 arm-level results and 15 clinical features across 303 patients, 15 significant findings detected with Q value < 0.25.

- Correlation between gene methylation status and clinical features
  View Report | Testing the association between 17090 genes and 13 clinical features across 286 samples, statistically thresholded by Q value < 0.05, 12 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 8 different clustering approaches and 15 clinical features across 318 patients, 30 significant findings detected with P value < 0.05 and Q value < 0.25.

- Correlation between RPPA expression and clinical features
  View Report | Testing the association between 175 genes and 13 clinical features across 164 samples, statistically thresholded by Q value < 0.05, 8 clinical features related to at least one genes.

- Correlation between mRNAseq expression and clinical features
  View Report | Testing the association between 18025 genes and 13 clinical features across 289 samples, statistically thresholded by Q value < 0.05, 13 clinical features related to at least one genes.

- Correlation between miRseq expression and clinical features
  View Report | Testing the association between 532 genes and 13 clinical features across 300 samples, statistically thresholded by Q value < 0.05, 11 clinical features related to at least one genes.

- Correlations between copy number and mRNAseq expression
  View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 423, 1138, 1795.4, 2123, 2447, 2795, 3188, 3688, 4364, respectively.

- Correlation between mRNA expression and DNA methylation
  View Report | The top 25 correlated methylation probes per gene are displayed. Total number of matched samples = 409. Number of gene expression samples = 409. Number of methylation samples = 409.

- Correlation between copy number variations of arm-level result and molecular subtypes
  View Report | Testing the association between copy number variation 42 arm-level results and 8 molecular subtypes across 432 patients, 95 significant findings detected with Q value < 0.25.

- Correlation between copy number variation genes and molecular subtypes
  View Report | Testing the association between copy number variation of 25 peak regions and 8 molecular subtypes across 432 patients, 44 significant findings detected with Q value < 0.25.

Methods & Data
Input

- Run Prefix = awg_thca__2013_03_18

- Summary Report Date = Thu Apr 4 15:43:48 2013

- Protection = FALSE

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