Figure 1

Delineation of the proposed approach. Delineation of (a) current and (b) proposed approaches for studies using transcriptomic analysis. Suppose that the hypothesis for transcriptomic experiment is that cell subset X is defective in the differentiation programme D. (a) Typical approach in immunological studies using transcriptomic analysis. Cell subset X and its controls are analysed by microarray analysis or RNA-seq. Note that the interpretation of the results of data analysis is made essentially by “current knowledge,” where considerable arbitrariness and bias can be introduced. (b) Proposed approach using Canonical Correspondence Analysis (CCA). The original hypothesis is decomposed into two parts, “cell subset X is defective…” and “…in the differentiation programme D,” based on which two transcriptomic datasets are prepared. Note that the same genes must be used in both matrices Z and X. X is standardised (S), and projected onto Z using a projection matrix Q. Thus, the projected space QS is the interpretable part of the main data X. SVD is applied to QS, producing sample and gene scores (‘X’ and ‘Gene’ in the new space). Differentiation programmes are visualised as regression coefficients between Z and the new axes. The results are visualised as a triplot that show relationships between cell subset X, genes, and differentiation programmes. The visualisation process ensures the transparency of the interpretation.