Copy number analysis (GISTIC2)
View Report | There were 303 tumor samples used in this analysis: 26 significant arm-level results, 28 significant focal amplifications, and 42 significant focal deletions were found.

Mutation Analysis (MutSig)
View Report | MAF used for this analysis: LUAD.final_analysis_set.maf

Clustering of copy number data: consensus NMF
View Report | The most robust consensus NMF clustering of 303 samples using the 70 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 4403 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 220 samples and 4403 genes 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 RPPA data: consensus NMF
View Report | The most robust consensus NMF clustering of 237 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 237 samples and 150 proteins 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 mRNA expression: consensus NMF
View Report | The most robust consensus NMF clustering of 32 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 mRNA expression: consensus hierarchical
View Report | The 1500 most variable genes were selected. Consensus average linkage hierarchical clustering of 32 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 mRNAseq gene expression: consensus NMF
View Report | The most robust consensus NMF clustering of 250 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 250 samples and 1500 genes 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 miRseq expression: consensus NMF
View Report | We filtered the data to 150 most variable miRs. Consensus NMF clustering of 100 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 100 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 between copy number variations of arm-level result and selected clinical features
View Report | Testing the association between copy number variation 79 arm-level results and 11 clinical features across 285 patients, 3 significant findings detected with Q value < 0.25.

Correlation between copy number variation genes and selected clinical features
View Report | Testing the association between copy number variation of 70 peak regions and 11 clinical features across 285 patients, 6 significant findings detected with Q value < 0.25.

Correlation between gene methylation status and clinical features
View Report | Testing the association between 20231 genes and 11 clinical features across 216 samples, statistically thresholded by Q value < 0.05, 7 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 11 clinical features across 283 patients, 14 significant findings detected with P value < 0.05.

Correlation between gene mutation status and selected clinical features
View Report | Testing the association between mutation status of 351 genes and 11 clinical features across 172 patients, 9 significant findings detected with Q value < 0.25.

Correlation between RPPA expression and clinical features
View Report | Testing the association between 174 genes and 11 clinical features across 227 samples, statistically thresholded by Q value < 0.05, 5 clinical features related to at least one genes.

Correlation between mRNA expression and clinical features
View Report | Testing the association between 17814 genes and 8 clinical features across 32 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

Correlation between mRNAseq expression and clinical features
View Report | Testing the association between 18275 genes and 11 clinical features across 250 samples, statistically thresholded by Q value < 0.05, 7 clinical features related to at least one genes.

Correlation between miRseq expression and clinical features
View Report | Testing the association between 524 genes and 11 clinical features across 100 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

Correlations between copy number and mRNA expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.12546, -0.0186, 0.0605, 0.1312, 0.1987, 0.26944, 0.34298, 0.42, 0.5197, respectively.

Correlations between copy number and mRNAseq expression
View Report | The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 1031.4, 1733, 2314.2, 2884, 3486, 4107, 4771, 5430.2, 6202, 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 = 185. Number of gene expression samples = 250. Number of methylation samples = 220.

Association of mutation, copy number alteration, and subtype markers with pathways
View Report | There are 214 genes with significant mutation (Q value <= 0.1) and 448 genes with significant copy number alteration (Q value <= 0.25). The identified marker genes (Q value <= 0.01 or within top 2000) are 19 for subtype 1, 19 for subtype 2, 19 for subtype 3. Pathways significantly enriched with these genes (Q value <= 0.01) are identified :

PARADIGM pathway analysis of mRNA expression data
View Report | There were 43 significant pathways identified in this analysis.

PARADIGM pathway analysis of mRNA expression and copy number data
View Report | There were 38 significant pathways identified in this analysis.