Analysis Overview
Cholangiocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1KH0M56
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Analysis Overview for Cholangiocarcinoma (Primary solid tumor cohort) - 17 October 2014. Broad Institute of MIT and Harvard. doi:10.7908/C1KH0M56
Overview
Introduction

This is an overview of Cholangiocarcinoma analysis pipelines from Firehose run "17 October 2014".

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

    • SNP6 Copy number analysis (GISTIC2)
      View Report | There were 36 tumor samples used in this analysis: 12 significant arm-level results, 4 significant focal amplifications, and 19 significant focal deletions were found.

  • 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 36 samples using the 23 copy number focal regions was identified for k = 2 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 36 samples using the 23 copy number focal regions was identified for k = 2 clusters. We computed the clustering for k = 2 to k = 8 and used the cophenetic correlation coefficient to determine the best solution.

    • 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 36 samples and 647 miRs identified 7 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 36 samples and 647 miRs identified 2 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 130 most variable miRs. Consensus ward linkage hierarchical clustering of 36 samples and 130 miRs identified 6 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 36 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.

    • 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 36 samples and 1500 genes identified 7 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 36 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.

  • Pathway Analyses

    • PARADIGM pathway analysis of mRNASeq expression and copy number data
      View Report | There were 34 significant pathways identified in this analysis.

    • PARADIGM pathway analysis of mRNASeq expression data
      View Report | There were 31 significant pathways identified in this analysis.

  • Other Correlation Analyses

    • Correlation between copy number variation genes (focal events) and molecular subtypes
      View Report | Testing the association between copy number variation 23 focal events and 7 molecular subtypes across 36 patients, 3 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 65 arm-level events and 7 molecular subtypes across 36 patients, one significant finding detected with P value < 0.05 and Q value < 0.25.

    • Correlations between copy number and mRNAseq expression
      View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 966.4, 2030.8, 2765, 3405.6, 4058, 4695.4, 5379, 6113.2, 6935, respectively.

Methods & Data
Input

  • Summary Report Date = Wed Jan 21 16:16:37 2015

  • Protection = FALSE

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