PMET is a powerful tool designed to assist researchers in identifying the interactions of transcription factors (TFs) to regulate gene network. By studying the combinations of homotypic and heterotypic motifs within transcription regulatory modules, PMET provides a comprehensive framework for analyzing and understanding the functional implications and regulatory dynamics associated with motif interactions in gene expression.

PMET is designed to address the limitations of traditional analysis tools by considering both homotypic and heterotypic motif combinations simultaneously.

PMET is available in both command-line and web-based versions, providing flexibility and convenience to researchers.

Essentially all you need to run PMET for your biological process of interest is a set of genomic regulatory sequences. These could be promoters of differentially expressed genes, differentially open chromatin regions, regions identified from DNA methylation assay, or regions identified using other techniques.

Homotypic Clustering: PMET can identify clusters of homotypic motifs within the genome based on the motif data provided by the user. This analysis helps uncover the significance and functionality of motifs in gene regulation.

Heterotypic Clustering: After identifying clusters of homotypic motifs,PMET further analyzes the pairings between these clusters to generate heterotypic clusters. Through this process, PMET reveals the potential interactions between motifs in gene regulation.