Description

Quantitative R-loop tracks present normalized and weighted R-loop signals integrated across multiple profiling technologies and biological samples, yielding both R-loop scores and R-loop zones. The R-loop score is displayed as three stacked bigWig tracks representing Watson-strand, Crick-strand, and undetermined-strand signals, together offering a genome-wide view of R-loop occupancy. R-loop zones are defined by trimming continuous signal tracts at 25% of their local maximum. This track provides a unified, normalized view of the R-loop landscape across diverse datasets, enabling users to identify conserved, high-confidence R-loop-forming loci.

Methods

• Data Preparation
  • To facilitate cross-sample comparison, we applied a modified Robust Z-score to normalize the signal values of each sample. The modified Robust Z-score was calculated as (R-loop peak signal − lower fence) / MAD, and values greater than 10 were capped at 10.
• Calculation of technology score
  • Normalized R-loop signals were smoothed using a sliding window approach (window size = 100 bp; step size = 10 bp). For each R-loop mapping technology, the average R-loop signal across all samples was calculated for each window to obtain a technology score. For stranded R-loop mapping technologies, strand information was retained during computation to define the strandness of the final results. Meanwhile, Watson and Crick peaks were merged during the calculation to enable integration with non-stranded R-loop mapping technologies.
• Calculation of weighted R-loop score
  • For non-strand specific data, technology scores were summed to obtain the R-loop score for each window. The summed window score was then multiplied by the number of technologies with a score greater than 0 in that window to yield the weighted R-loop score. The same procedure was applied to stranded R-loop technologies to obtain stranded R-loop score. Non-stranded R-loop score that overlapped with Watson or Crick R-loop scores were proportionally assigned to the Watson or Crick strand.
• Identification of high-confidence R-loop regions
  • Contiguous regions with a score > 0 are highly likely to harbor R-loops. After excluding regions with R-loop scores below the lower quantile within each contiguous region, the remaining regions are considered high-confidence R-loop regions.