Classifying Gene Expression Profiles from Pairwise mRNA Comparisons

By Donald Geman, Christian d'Avignon, Daniel Q. Naiman, Raimond L. Winslow. Statistical Applications in Genetics and Molecular Biology, 2004

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SingleCellNet: a computational tool to classify single cell RNA-Seq data across platforms and across species (2018, methodology): “To make query and reference data compatible across platforms and species, we use a transformation based on comparing the expression of pairs of genes within each cell, a method inspired by the top-scoring pair classifier (Geman et al., 2004).”
Computational assignment of cell-cycle stage from single-cell transcriptome data. (2015, positive): “In order to assess the relevance of individual genes for classiﬁcation, we analysed the loadings on PC1 for the PCA-based method and assigned a score to the pairs of genes for the pairs method (following the approach introduced in [23]; see Appendix B.3”