Using the Qap Grid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic Signatures

In this chapter, we illustrate the use of an integrated mathematical method for joint clustering and visualization of large-scale datasets. In applying these clustering methodologies to biological datasets, we aim to identify differentially expressed genes according to cell type by building molecular signatures supported by statistical scores. In doing so, we also aim to find a global map of highly co-expressed clusters. Variations in these clusters may well indicate other pathological trends and changes. © Springer Science+Business Media New York 2017.