Applying tidy principles to investigating chromatin composition and architecture
The integration of tidy tools into genomics analysis catalyzes a paradigm shift in the way researchers approach data manipulation and interpretation. By adhering to the principles of tidy data organization and the elegant syntax of tidyverse packages, researchers can navigate the complexities of genomic datasets with unprecedented ease and efficiency. I will unveil two novel packages: plyinteractions, specifically developed to manipulate chromatin conformation capture (3C, Hi-C micro-C, etc), and tidyCoverage, to manipulate and extract coverage tracks within the tidyomics framework. plyinteractions and tidyCoverage packages introduce novel SummarizedExperiment-derived S4 classes to store genomics data and expand tidy methods. They synergize the existing functionalities of tidyverse and Bioconductor, to seamlessly intertwine data manipulation, aggregation, visualization, and modeling within a unified framework. This integrated workflow not only enhances the clarity and reproducibility of analyses but also empowers researchers to extract deeper biological insights from their data, offering a glimpse into the future of genomics analysis.