CTGS program user guide
CTGS (Cancer Target Gene Screening) is designed to dataset based analysis. You have to select dataset first in Datasets page
After selection of dataset, you can visualize multi-omics data for specific genes on customized subgroup. It's consists with plot by quantities and plot by correlations. A detailed description on how to use them can be found in the popup tip that appears when dragging the mouse cursor to the corresponding term in the analysis page.
- Plot quantities: differential quantities of specific genes or gene set by each multi-omics layer (DNA copy-number, RNA expressionn, DNA methylation) for subtypes or clinical implications.
- Plot correlations: correlation analysis for specific genes or gene set between multi-omics layers.
For example, ERBB2 expression by subtypes in METABRIC recurred and hormon therapy patients, you can see it like as following page and options
After selection of dataset, you can do survival analysis for specific genes on customized subgroup. It's consists with by quantities and by alterations. A detailed description on how to use them can be found in the popup tip that appears when dragging the mouse cursor to the corresponding term in the analysis page.
- By quantities: survival analysis by continuous variables including RNA expression and DNA methylation. CTGS supports max-sig cutoff method for stratification of patients.
- By alterations: survival analysis by categorical variables including CNAs and mutations. CTGS supports combination of genetic alteration of two genes.
For example, survival analysis for ERBB2-GATA3 co-amplification in METABRIC, you can check with following page and options.
Target gene screening
This suggests the target genes from the selected dataset on customized subgroup. It is based on the status of gene expression, amplification, DNA methylation and survival analysis.
- By amplification: by ConSig-Amp method, DNA amplification target genes were nominated according to subtype or clinical implication.
- By DNA methylation: by ConSig-Met method, DNA methylation target genes were nominated according to subtype or clinical implicationn.
More details, you can see Features page.