can use dplyr instead of tidyselect

DESCRIPTION

@@ -43,8 +43,7 @@ Suggests:
     scales,
     sigrap,
     testthat (>= 3.0.0),
-    tibble,
-    tidyselect,
+    tibble
 Roxygen: list(markdown = TRUE,
               roclets = c("namespace", "rd", "roxytest::testthat_roclet"))
 biocViews:

R/purple.R

@@ -643,7 +643,7 @@ purple_purity_read <- function(x) {
 
   purple_purity <- purple_purity |>
     dplyr::mutate(
-      dplyr::across(tidyselect::where(is.numeric), \(x) round(x, 2)),
+      dplyr::across(dplyr::where(is.numeric), \(x) round(x, 2)),
       dplyr::across(dplyr::everything(), as.character)
     ) |>
     tidyr::pivot_longer(dplyr::everything(), names_to = "column", values_to = "value") |>
@@ -745,7 +745,7 @@ purple_kataegis <- function(x) {
 
   data <- d$data |>
     dplyr::filter(!is.na(.data$KT)) |>
-    dplyr::select(c("CHROM", "POS", tidyselect::all_of(info_cols)))
+    dplyr::select(c("CHROM", "POS", dplyr::all_of(info_cols)))
 
   description <- d$description |>
     dplyr::filter(.data$ID %in% info_cols) |>

R/sv.R

@@ -29,9 +29,9 @@ split_double_col <- function(d, nms) {
   assertthat::assert_that(is.character(nms))
 
   outd <- d |>
-    dplyr::select(tidyselect::all_of(nms)) |>
+    dplyr::select(dplyr::all_of(nms)) |>
     dplyr::mutate(num = dplyr::row_number()) |>
-    tidyr::pivot_longer(cols = tidyselect::all_of(nms), names_to = "col_nm", values_to = "x1_x2") |>
+    tidyr::pivot_longer(cols = dplyr::all_of(nms), names_to = "col_nm", values_to = "x1_x2") |>
     tidyr::separate(.data$x1_x2, into = c("x1", "x2"), sep = ",", fill = "right") |>
     dplyr::mutate(
       x1 = round(as.double(.data$x1), 2),

conda/recipe/meta.yaml

@@ -43,7 +43,6 @@ requirements:
     - r-scales
     - r-testthat
     - r-tibble
-    - r-tidyselect
 
   run:
     - r-base
@@ -73,7 +72,6 @@ requirements:
     - r-scales
     - r-testthat
     - r-tibble
-    - r-tidyselect
 
 test:
   commands: