In Bishop-Laboratory/RLSeq: RLSeq: An analysis package for R-loop mapping data

`r i`. `r names(resAnchor)` {#`r resAnchor`}

r GenomeInfoDb::genome(object)[1] Gene annotations were downloaded from AnnotationHub{target="_blank"} and overlapped with R-loop ranges in r object@metadata$sampleName. For additional detail, please refer to the RLSeq::geneAnnotation documentation (link{target="_blank"}). The resulting gene table was then filtered for the top 2000 peaks (by p-adjusted value) and is observed here:

geneRes <- rlresult(object, resultName = "geneAnnoRes")

# Display
spec_now <- paste0(
  "geneAnno_",
  gsub(object@metadata$sampleName, pattern = " ", replacement = "_")
)
odf <- object %>%
  as.data.frame()

# If V9 is available (means narrow/broadPeak) show top results
if ("qval" %in% colnames(odf)) {
 odf$peak_name <- rownames(odf)
 numrow <- nrow(odf)
 odf %>%
  dplyr::slice_max(qval, n = min(numrow, 2000)) %>%
  dplyr::inner_join(geneRes, by = "peak_name") %>%
  dplyr::relocate(gene_id, .after = peak_name) %>%
  DT::datatable(
    options = list(
          dom = "Bfrtip", 
          scrollX = TRUE,
          buttons = list(
            extend  = 'collection',
            buttons = list(
              list(extend='csv', filename=spec_now),
              list(extend='excel', filename=spec_now)
            ),
            text    = 'Download'
          )
      )
  )
} else {
  cat("\nNo padjusted column was provided. Top results gene annotations will",
      " not be shown. Please see RLRanges() for more details.")
}