We previously showed that the mining of R-loop mapping data can reveal novel insight into R-loop dynamics genome-wide. However, little is known about how R-loops change in response to different types of perturbations. This project will involve developing an atlas of R-loop changes in response to a wide array of perturbations. We will also develop a new R/Bioconductor package for the differential analysis of R-loop mapping data that will become a component of RLSuite: https://www.biorxiv.org/content/10.1101/2022.07.13.499820v1
Data Mining, Data Integration, Software development, R-Shiny, Reactive Programming, ChIP-Seq
Avg. Hours / Week
Alex Bishop, DPhil & Henry Miller
Publication if successful?
Trainee authorship criteria (if applicable)
Trainees who contribute meaningfully to the project will be listed as co-authors. E.g., performing an entire core analysis or developing a core component of project software.
One spot is reserved for an R-shiny web developer.