Analysis of mutagenesis by APOBEC cytidine deaminases (P-MACD).
View Report | There are 373 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).

CHASM 1.0.5 (Cancer-Specific High-throughput Annotation of Somatic Mutations)
View Report | There are 29874 mutations identified by MuTect and 1819 mutations with significant functional impact at BHFDR <= 0.25.

Mutation Analysis (MutSig 2CV v3.1)
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Mutation Analysis (MutSig v2.0)
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Mutation Analysis (MutSigCV v0.9)
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Mutation Assessor
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SNP6 Copy number analysis (GISTIC2)
View Report | There were 372 tumor samples used in this analysis: 30 significant arm-level results, 26 significant focal amplifications, and 33 significant focal deletions were found.

Correlation between aggregated molecular cancer subtypes and selected clinical features
View Report | Testing the association between subtypes identified by 10 different clustering approaches and 12 clinical features across 377 patients, 40 significant findings 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 59 focal events and 12 clinical features across 370 patients, 39 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 82 arm-level events and 12 clinical features across 370 patients, 33 significant findings detected with Q value < 0.25.

Correlation between gene methylation status and clinical features
View Report | Testing the association between 16488 genes and 12 clinical features across 377 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 9 clinical features related to at least one genes.

Correlation between gene mutation status and selected clinical features
View Report | Testing the association between mutation status of 99 genes and 12 clinical features across 373 patients, 12 significant findings detected with Q value < 0.25.

Correlation between miRseq expression and clinical features
View Report | Testing the association between 540 miRs and 12 clinical features across 373 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one miRs.

Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 17705 genes and 12 clinical features across 371 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 7 clinical features related to at least one genes.

Correlation between mutation rate and clinical features
View Report | Testing the association between 2 variables and 13 clinical features across 372 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 5 clinical features related to at least one variables.

Correlation between RPPA expression and clinical features
View Report | Testing the association between 219 genes and 12 clinical features across 184 samples, statistically thresholded by P value < 0.05 and Q value < 0.3, 8 clinical features related to at least one genes.

Clustering of copy number data by focal peak region with absolute value: consensus NMF
View Report | The most robust consensus NMF clustering of 372 samples using the 59 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 copy number data by peak region with threshold value: consensus NMF
View Report | The most robust consensus NMF clustering of 372 samples using the 59 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 most robust consensus NMF clustering of 429 samples using the 10015 most variable genes was identified for k = 4 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

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 398 samples and 647 miRs identified 6 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

Clustering of miRseq mature expression: consensus NMF
View Report | The most robust consensus NMF clustering of 398 samples using the 647 most variable miRs was identified for k = 7 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

Clustering of miRseq precursor expression: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 135 most variable miRs. Consensus ward linkage hierarchical clustering of 424 samples and 135 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 | The most robust consensus NMF clustering of 424 samples using the 150 most variable miRs was identified for k = 7 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine 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 423 samples and 1500 genes identified 4 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 423 samples using the 1500 most variable genes was identified for k = 5 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

Clustering of RPPA data: consensus hierarchical
View Report | Median absolute deviation (MAD) was used to select 219 most variable proteins. Consensus ward linkage hierarchical clustering of 184 samples and 219 proteins identified 5 subtypes with the stability of the clustering increasing for k = 2 to k = 10.

Clustering of RPPA data: consensus NMF
View Report | The most robust consensus NMF clustering of 184 samples using the 219 most variable proteins was identified for k = 6 clusters. We computed the clustering for k = 2 to k = 10 and uused the cophenetic correlation coefficient and the average silhouette width calculation to determine the robust clusters.

Identification of putative miR direct targets by sequencing data
View Report | The CLR algorithm was applied on 787 miRs and 17705 mRNAs across 419 samples. After 2 filtering steps, the number of 99 miR:genes pairs were detected.

GSEA Class2: Canonical Pathways enriched in each subtypes of mRNAseq_cNMF in LIHC
View Report | basic data info

PARADIGM pathway analysis of mRNASeq expression and copy number data
View Report | There were 43 significant pathways identified in this analysis.

PARADIGM pathway analysis of mRNASeq expression data
View Report | There were 50 significant pathways identified in this analysis.

Significant over-representation of pathway gene sets for a given gene list
View Report | For a given gene list, a hypergeometric test was tried to find significant overlapping canonical pathways using 1320 gene sets. In terms of FDR adjusted p.values, top 5 significant overlapping gene sets are listed as below.

Correlation between copy number variation genes (focal events) and molecular subtypes
View Report | Testing the association between copy number variation 59 focal events and 10 molecular subtypes across 370 patients, 365 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 82 arm-level events and 10 molecular subtypes across 370 patients, 319 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 99 genes and 10 molecular subtypes across 373 patients, 36 significant findings detected with P value < 0.05 and Q value < 0.25.

Correlation between mRNA expression and DNA methylation
View Report | The top 25 correlated methylation probes per gene are displayed. Total number of matched samples = 371. Number of gene expression samples = 423. Number of methylation samples = 429.

Correlations between copy number and mRNAseq expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 868.5, 1562, 2083, 2627, 3218, 3838, 4467, 5107, 5830, respectively.