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Background Alternative polyadenylation (APA) has emerged as a pervasive mechanism that contributes to the transcriptome complexity and dynamics of gene regulation. The current tsunami of whole genome poly(A) site data from various conditions generated by 3′ end sequencing provides a valuable data source for the study of APA-related gene expression. Cluster analysis is a powerful technique for investigating...
Alternative polyadenylation (APA) can lead to various mRNA isforms differing in their 3' UTR, which contributes to the dynamics of gene regulation, including stability, localization and translation of mRNA. However, clustering of genes using poly(A) site data has not been extensively studied. Here we constructed a two-layer model based on canonical correlation analysis (CCA) to explore the clustering...
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