In this panel, you can search for genes that are most correlated with a target gene or gene signature within selected datasets. Some gene signature lists are provided.

This module calculates the Pearson correlation coefficient (PCC) for pairwise gene expression levels across datasets and generates a network highlighting the strongest associations. Users can identify both positively correlated and anti-correlated genes.

Parameters:

• Gene: Input a gene/isoform or gene signature of interest.
• Top # Genes: Set the number of top correlated genes to display. (Maximum: 1000)
• Interaction Pattern: Select interaction pattern of interest.
• Log Transformation: Apply log2 transformation to normalize the gene expression data.
• TCGA Tumor/TCGA Normal/GTEx/Used Expression Datasets: Select cancer types of interest in the "TCGA Tumor", "TCGA Normal" or "GTEx" field and click "add" to build dataset list in the "Used Expression Datasets" field. Also, manual input of cancer types split by comma (e.g. COAD Tumor,READ Tumor) is also acceptable. The correlation analysis is based on the datasets list.

Notes:

• When searching for a single gene, the displayed network graph highlights the top 10 nodes with the highest correlation related to the target gene within the selected datasets and interaction patterns.
• When searching for multiple genes, the displayed network graph the top 10 nodes with the highest degrees connected to the target genes within the selected datasets and interaction patterns.