Cancer is a complex disease, and like other complex diseases, changes in gene expression and structural variation correlate with each other and together play an integrated role in the development of cancer. Understanding the correlation among gene expression, structural variation and protein expression is indispensable in oncology research.
Oncoland provides dynamic correlation visualization for RNA-Seq, miRNA-Seq, somatic mutation, copy number variation and protein RPPA data.
Take ESR1, estrogen receptor 1, for example, the RNA-Seq Expression=> RNA-Seq Expression provides the correlation and scatterplot view of ESR1 expression with all other genes:
In OncoLand, you can filter any criteria of your interest in tumor type, sample metadata, clinical subpopulation and more.
For instance, if you were interested in Estrogen Receptor positive samples in primary breast cancer, just filter it:
The correlation and scatterplot view will dynamically change with the filter criteria:
Li, Jie, et al. "Identification of high-quality cancer prognostic markers and metastasis network modules." Nature communications 1 (2010): 34.