diff --git a/NAMESPACE b/NAMESPACE
index ca88b6b9..9eb54ad7 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -272,7 +272,6 @@ import(tidygraph)
 import(vctrs)
 importFrom(MASS,bandwidth.nrd)
 importFrom(MASS,kde2d)
-importFrom(dplyr,"%>%")
 importFrom(dplyr,arrange)
 importFrom(dplyr,do)
 importFrom(dplyr,group_by)
@@ -358,7 +357,6 @@ importFrom(igraph,delete_vertex_attr)
 importFrom(igraph,distances)
 importFrom(igraph,edge_attr)
 importFrom(igraph,ends)
-importFrom(igraph,get.edge.ids)
 importFrom(igraph,gorder)
 importFrom(igraph,graph_attr)
 importFrom(igraph,gsize)
diff --git a/R/autograph.R b/R/autograph.R
index e16000a2..4c2cb53a 100644
--- a/R/autograph.R
+++ b/R/autograph.R
@@ -18,7 +18,7 @@
 #'
 #' @examples
 #' library(tidygraph)
-#' gr <- create_notable('herschel') %>%
+#' gr <- create_notable('herschel') |>
 #'   mutate(class = sample(letters[1:3], n(), TRUE)) %E>%
 #'   mutate(weight = runif(n()))
 #'
diff --git a/R/edges.R b/R/edges.R
index 537851ce..926a0841 100644
--- a/R/edges.R
+++ b/R/edges.R
@@ -198,28 +198,28 @@ expand_edge_aes <- function(x) {
   }
   x
 }
-#' @importFrom dplyr %>% group_by top_n ungroup
+#' @importFrom dplyr group_by top_n ungroup
 collapse_all_edges <- function(edges) {
   from <- pmin(edges$from, edges$to)
   to <- pmax(edges$to, edges$from)
   id <- paste(from, to, sep = '-')
   if (anyDuplicated(id)) {
     edges$.id <- id
-    edges <- edges %>%
-      group_by(.data$.id) %>%
-      top_n(1) %>%
+    edges <- edges |>
+      group_by(.data$.id) |>
+      top_n(1) |>
       ungroup()
   }
   data_frame0(edges)
 }
-#' @importFrom dplyr %>% group_by top_n ungroup
+#' @importFrom dplyr group_by top_n ungroup
 collapse_dir_edges <- function(edges) {
   id <- paste(edges$from, edges$to, sep = '-')
   if (anyDuplicated(id)) {
     edges$.id <- id
-    edges <- edges %>%
-      group_by(.data$.id) %>%
-      top_n(1) %>%
+    edges <- edges |>
+      group_by(.data$.id) |>
+      top_n(1) |>
       ungroup()
   }
   data_frame0(edges)
diff --git a/R/facet_graph.R b/R/facet_graph.R
index fa882e27..6f830f52 100644
--- a/R/facet_graph.R
+++ b/R/facet_graph.R
@@ -21,7 +21,7 @@
 #'
 #' @examples
 #' library(tidygraph)
-#' gr <- as_tbl_graph(highschool) %>%
+#' gr <- as_tbl_graph(highschool) |>
 #'   mutate(popularity = as.character(cut(centrality_degree(mode = 'in'),
 #'     breaks = 3,
 #'     labels = c('low', 'medium', 'high')
diff --git a/R/facet_nodes.R b/R/facet_nodes.R
index 993abdb5..190d2fdb 100644
--- a/R/facet_nodes.R
+++ b/R/facet_nodes.R
@@ -10,7 +10,7 @@
 #'
 #' @examples
 #' library(tidygraph)
-#' gr <- as_tbl_graph(highschool) %>%
+#' gr <- as_tbl_graph(highschool) |>
 #'   mutate(popularity = as.character(cut(centrality_degree(mode = 'in'),
 #'     breaks = 3,
 #'     labels = c('low', 'medium', 'high')
diff --git a/R/geom_axis_hive.R b/R/geom_axis_hive.R
index fa50645e..cb23a274 100644
--- a/R/geom_axis_hive.R
+++ b/R/geom_axis_hive.R
@@ -1,12 +1,12 @@
 #' @rdname ggraph-extensions
 #' @format NULL
 #' @usage NULL
-#' @importFrom dplyr %>% group_by mutate slice ungroup
+#' @importFrom dplyr group_by mutate slice ungroup
 #' @export
 StatAxisHive <- ggproto('StatAxisHive', StatFilter,
   setup_data = function(data, params) {
-    data <- data %>%
-      group_by(.data$angle, .data$section, .data$PANEL) %>%
+    data <- data |>
+      group_by(.data$angle, .data$section, .data$PANEL) |>
       mutate(
         x = min(.data$r) * cos(.data$angle[1]) * 1.1,
         y = min(.data$r) * sin(.data$angle[1]) * 1.1,
@@ -14,8 +14,8 @@ StatAxisHive <- ggproto('StatAxisHive', StatFilter,
         yend = max(.data$r) * sin(.data$angle[1]) * 1.1,
         max_r = max(.data$r),
         min_r = min(.data$r)
-      ) %>%
-      slice(1) %>%
+      ) |>
+      slice(1) |>
       ungroup()
     data_frame0(data)
   },
@@ -26,7 +26,7 @@ StatAxisHive <- ggproto('StatAxisHive', StatFilter,
 #' @format NULL
 #' @usage NULL
 #' @importFrom grid textGrob nullGrob
-#' @importFrom dplyr %>% group_by summarise
+#' @importFrom dplyr group_by summarise
 #' @export
 GeomAxisHive <- ggproto('GeomAxisHive', GeomSegment,
   draw_panel = function(data, panel_scales, coord, label = TRUE, axis = TRUE, label_colour = 'black') {
@@ -35,8 +35,8 @@ GeomAxisHive <- ggproto('GeomAxisHive', GeomSegment,
     data$xend <- data$xend / 1.1
     data$yend <- data$yend / 1.1
     data <- coord$transform(data, panel_scales)
-    label_data <- data %>%
-      group_by(.data$axis) %>%
+    label_data <- data |>
+      group_by(.data$axis) |>
       summarise(
         x = max(.data$max_r) * cos(mean(.data$angle)),
         y = max(.data$max_r) * sin(mean(.data$angle)),
@@ -132,15 +132,15 @@ GeomAxisHive <- ggproto('GeomAxisHive', GeomSegment,
 #' @examples
 #' # Plot the flare import graph as a hive plot
 #' library(tidygraph)
-#' flareGr <- as_tbl_graph(flare$imports) %>%
+#' flareGr <- as_tbl_graph(flare$imports) |>
 #'   mutate(
 #'     type = dplyr::case_when(
 #'       centrality_degree(mode = 'in') == 0 ~ 'Source',
 #'       centrality_degree(mode = 'out') == 0 ~ 'Sink',
 #'       TRUE ~ 'Both'
 #'     )
-#'   ) %>%
-#'   activate(edges) %>%
+#'   ) |>
+#'   activate(edges) |>
 #'   mutate(
 #'     type = dplyr::case_when(
 #'       grepl('flare.analytics', paste(.N()$name[from], .N()$name[to])) ~ 'Analytics',
diff --git a/R/geom_conn_bundle.R b/R/geom_conn_bundle.R
index 414d67cf..8267cdae 100644
--- a/R/geom_conn_bundle.R
+++ b/R/geom_conn_bundle.R
@@ -58,7 +58,7 @@
 #' @examples
 #' # Create a graph of the flare class system
 #' library(tidygraph)
-#' flareGraph <- tbl_graph(flare$vertices, flare$edges) %>%
+#' flareGraph <- tbl_graph(flare$vertices, flare$edges) |>
 #'   mutate(
 #'     class = map_bfs_chr(node_is_root(), .f = function(node, dist, path, ...) {
 #'       if (dist <= 1) {
diff --git a/R/geom_edge.R b/R/geom_edge.R
index 28b14b0e..7ceb4964 100644
--- a/R/geom_edge.R
+++ b/R/geom_edge.R
@@ -2,7 +2,7 @@
 #' @format NULL
 #' @usage NULL
 #' @importFrom grid segmentsGrob polylineGrob gpar
-#' @importFrom dplyr %>% group_by_ do ungroup
+#' @importFrom dplyr group_by_ do ungroup
 #' @importFrom ggforce interpolateDataFrame
 #' @export
 GeomEdgePath <- ggproto('GeomEdgePath', GeomPath,
diff --git a/R/geom_edge_arc.R b/R/geom_edge_arc.R
index 7b86f57e..86a3b0d1 100644
--- a/R/geom_edge_arc.R
+++ b/R/geom_edge_arc.R
@@ -81,14 +81,14 @@
 #' @examples
 #' require(tidygraph)
 #' # Make a graph with different directions of edges
-#' gr <- create_notable('Meredith') %>%
-#'   convert(to_directed) %>%
-#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) %>%
-#'   activate(edges) %>%
+#' gr <- create_notable('Meredith') |>
+#'   convert(to_directed) |>
+#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+#'   activate(edges) |>
 #'   mutate(
 #'     class = sample(letters[1:3], n(), replace = TRUE),
 #'     switch = sample(c(TRUE, FALSE), n(), replace = TRUE)
-#'   ) %>%
+#'   ) |>
 #'   reroute(from = to, to = from, subset = switch)
 #'
 #' ggraph(gr, 'linear') +
diff --git a/R/geom_edge_bend.R b/R/geom_edge_bend.R
index d1823b09..939378f7 100644
--- a/R/geom_edge_bend.R
+++ b/R/geom_edge_bend.R
@@ -68,9 +68,9 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_tree(20, 4) %>%
-#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) %>%
-#'   activate(edges) %>%
+#' gr <- create_tree(20, 4) |>
+#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+#'   activate(edges) |>
 #'   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 #'
 #' ggraph(gr, 'tree') +
diff --git a/R/geom_edge_bundle_path.R b/R/geom_edge_bundle_path.R
index 9714f4a2..69ff95d5 100644
--- a/R/geom_edge_bundle_path.R
+++ b/R/geom_edge_bundle_path.R
@@ -278,7 +278,7 @@ geom_edge_bundle_path0 <- function(mapping = NULL, data = get_edges(),
     )
   )
 }
-#' @importFrom igraph gsize delete_edges shortest_paths get.edge.ids is_directed
+#' @importFrom igraph gsize delete_edges shortest_paths is_directed as_edgelist
 path_bundle <- function(graph, nodes, from, to, directed = directed, max_distortion = 2, weight_fac = 2) {
   m <- gsize(graph)
   lock <- rep(FALSE, m)
@@ -294,6 +294,13 @@ path_bundle <- function(graph, nodes, from, to, directed = directed, max_distort
     cli::cli_warn("Ignoring {.arg directed} for undirected graphs")
   }
   mode <- if (is.null(directed) || !directed) "all" else "out"
+
+  all_edges <- as_edgelist(graph)
+  if (directed) {
+    all_edges <- paste(all_edges[,1], "-", all_edges[,2])
+  } else {
+    all_edges <- paste(pmin(all_edges[,1], all_edges[,2]), "-", pmax(all_edges[,1], all_edges[,2]))
+  }
   # iterate
   for (e in edges_order) {
     s <- from[e]
@@ -315,8 +322,15 @@ path_bundle <- function(graph, nodes, from, to, directed = directed, max_distort
       next()
     }
     all_edges_on_path <- rep(as.integer(path), each = 2)
-    all_edges_on_path <- all_edges_on_path[-c(1, length(all_edges_on_path))]
-    all_edges_on_path <- get.edge.ids(graph, all_edges_on_path, directed = mode != "all", error = FALSE, multi = TRUE)
+    all_edges_on_path <- matrix(all_edges_on_path[-c(1, length(all_edges_on_path))], ncol = 2, byrow = TRUE)
+    if (directed) {
+      all_edges_on_path <- paste(all_edges_on_path[,1], "-", all_edges_on_path[,2])
+    } else {
+      all_edges_on_path <- paste(pmin(all_edges_on_path[,1], all_edges_on_path[,2]),
+                                 "-",
+                                 pmax(all_edges_on_path[,1], all_edges_on_path[,2]))
+    }
+    all_edges_on_path <- all_edges %in% all_edges_on_path
     lock[all_edges_on_path] <- TRUE
     paths[[e]] <- path
   }
diff --git a/R/geom_edge_density.R b/R/geom_edge_density.R
index 11def835..b7617e59 100644
--- a/R/geom_edge_density.R
+++ b/R/geom_edge_density.R
@@ -39,8 +39,8 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('bull') %>%
-#'   activate(edges) %>%
+#' gr <- create_notable('bull') |>
+#'   activate(edges) |>
 #'   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 #'
 #' ggraph(gr, 'stress') +
diff --git a/R/geom_edge_diagonal.R b/R/geom_edge_diagonal.R
index dea307a4..b5ebabfe 100644
--- a/R/geom_edge_diagonal.R
+++ b/R/geom_edge_diagonal.R
@@ -76,9 +76,9 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_tree(20, 4) %>%
-#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) %>%
-#'   activate(edges) %>%
+#' gr <- create_tree(20, 4) |>
+#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+#'   activate(edges) |>
 #'   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 #'
 #' ggraph(gr, 'tree') +
diff --git a/R/geom_edge_elbow.R b/R/geom_edge_elbow.R
index 5ba40815..69c68ba3 100644
--- a/R/geom_edge_elbow.R
+++ b/R/geom_edge_elbow.R
@@ -74,10 +74,10 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' irisDen <- hclust(dist(iris[1:4], method = 'euclidean'), method = 'ward.D2') %>%
-#'   as_tbl_graph() %>%
-#'   mutate(class = sample(letters[1:3], n(), TRUE)) %>%
-#'   activate(edges) %>%
+#' irisDen <- hclust(dist(iris[1:4], method = 'euclidean'), method = 'ward.D2') |>
+#'   as_tbl_graph() |>
+#'   mutate(class = sample(letters[1:3], n(), TRUE)) |>
+#'   activate(edges) |>
 #'   mutate(class = sample(letters[1:3], n(), TRUE))
 #'
 #' ggraph(irisDen, 'dendrogram', circular = TRUE) +
diff --git a/R/geom_edge_fan.R b/R/geom_edge_fan.R
index 3cec5a8d..87078994 100644
--- a/R/geom_edge_fan.R
+++ b/R/geom_edge_fan.R
@@ -77,8 +77,8 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('bull') %>%
-#'   convert(to_directed) %>%
+#' gr <- create_notable('bull') |>
+#'   convert(to_directed) |>
 #'   bind_edges(data.frame(from = c(1, 2, 2, 3), to = c(2, 1, 3, 2))) %E>%
 #'   mutate(class = sample(letters[1:3], 9, TRUE)) %N>%
 #'   mutate(class = sample(c('x', 'y'), 5, TRUE))
@@ -250,17 +250,17 @@ geom_edge_fan0 <- function(mapping = NULL, data = get_edges(),
     )
   )
 }
-#' @importFrom dplyr %>% group_by arrange mutate n ungroup transmute
+#' @importFrom dplyr group_by arrange mutate n ungroup transmute
 create_fans <- function(from, to, params) {
   from$.id <- paste(pmin(from$from, to$to), pmax(from$from, to$to), sep = '-')
   from$.orig_ind <- seq_len(nrow(from))
-  position <- from %>%
-    group_by(.data$PANEL, .data$.id) %>%
-    arrange(.data$from) %>%
-    mutate(position = seq_len(n()) - 0.5 - n() / 2) %>%
-    mutate(position = .data$position * ifelse(.data$from < .data$to, 1, -1)) %>%
-    ungroup() %>%
-    arrange(.data$.orig_ind) %>%
+  position <- from |>
+    group_by(.data$PANEL, .data$.id) |>
+    arrange(.data$from) |>
+    mutate(position = seq_len(n()) - 0.5 - n() / 2) |>
+    mutate(position = .data$position * ifelse(.data$from < .data$to, 1, -1)) |>
+    ungroup() |>
+    arrange(.data$.orig_ind) |>
     transmute(position = .data$position)
   position <- position$position
   max_fans <- max(table(from$.id))
diff --git a/R/geom_edge_hive.R b/R/geom_edge_hive.R
index d7ee791b..53f44624 100644
--- a/R/geom_edge_hive.R
+++ b/R/geom_edge_hive.R
@@ -74,15 +74,15 @@
 #' @examples
 #' # Plot the flare import graph as a hive plot
 #' library(tidygraph)
-#' flareGr <- as_tbl_graph(flare$imports) %>%
+#' flareGr <- as_tbl_graph(flare$imports) |>
 #'   mutate(
 #'     type = dplyr::case_when(
 #'       centrality_degree(mode = 'in') == 0 ~ 'Source',
 #'       centrality_degree(mode = 'out') == 0 ~ 'Sink',
 #'       TRUE ~ 'Both'
 #'     )
-#'   ) %>%
-#'   activate(edges) %>%
+#'   ) |>
+#'   activate(edges) |>
 #'   mutate(
 #'     type = dplyr::case_when(
 #'       grepl('flare.analytics', paste(.N()$name[from], .N()$name[to])) ~ 'Analytics',
diff --git a/R/geom_edge_link.R b/R/geom_edge_link.R
index 7faebb88..91551e4e 100644
--- a/R/geom_edge_link.R
+++ b/R/geom_edge_link.R
@@ -134,9 +134,9 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('bull') %>%
-#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) %>%
-#'   activate(edges) %>%
+#' gr <- create_notable('bull') |>
+#'   mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+#'   activate(edges) |>
 #'   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 #'
 #' ggraph(gr, 'stress') +
diff --git a/R/geom_edge_parallel.R b/R/geom_edge_parallel.R
index 980b7049..93cdb3a5 100644
--- a/R/geom_edge_parallel.R
+++ b/R/geom_edge_parallel.R
@@ -68,8 +68,8 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('bull') %>%
-#'   convert(to_directed) %>%
+#' gr <- create_notable('bull') |>
+#'   convert(to_directed) |>
 #'   bind_edges(data.frame(from = c(1, 2, 2, 3), to = c(2, 1, 3, 2))) %E>%
 #'   mutate(class = sample(letters[1:3], 9, TRUE)) %N>%
 #'   mutate(class = sample(c('x', 'y'), 5, TRUE))
@@ -230,16 +230,16 @@ geom_edge_parallel0 <- function(mapping = NULL, data = get_edges(),
     )
   )
 }
-#' @importFrom dplyr %>% group_by arrange summarise n ungroup pull
+#' @importFrom dplyr group_by arrange summarise n ungroup pull
 edge_positions <- function(from, to, params) {
   from$.id <- paste(pmin(from$from, to$to), pmax(from$from, to$to), sep = '-')
   from$.orig_ind <- seq_len(nrow(from))
-  from %>%
-    group_by(.data$PANEL, .data$.id) %>%
-    arrange(.data$from) %>%
-    mutate(position = seq_len(n()) - 0.5 - n() / 2) %>%
-    mutate(position = .data$position * ifelse(.data$from < .data$to, 1, -1)) %>%
-    ungroup() %>%
-    arrange(.data$.orig_ind) %>%
+  from |>
+    group_by(.data$PANEL, .data$.id) |>
+    arrange(.data$from) |>
+    mutate(position = seq_len(n()) - 0.5 - n() / 2) |>
+    mutate(position = .data$position * ifelse(.data$from < .data$to, 1, -1)) |>
+    ungroup() |>
+    arrange(.data$.orig_ind) |>
     pull(.data$position)
 }
diff --git a/R/geom_edge_point.R b/R/geom_edge_point.R
index 028db507..d0cad42e 100644
--- a/R/geom_edge_point.R
+++ b/R/geom_edge_point.R
@@ -42,11 +42,11 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('zachary') %>%
-#'   mutate(group = group_infomap()) %>%
-#'   morph(to_split, group) %>%
-#'   activate(edges) %>%
-#'   mutate(edge_group = as.character(.N()$group[1])) %>%
+#' gr <- create_notable('zachary') |>
+#'   mutate(group = group_infomap()) |>
+#'   morph(to_split, group) |>
+#'   activate(edges) |>
+#'   mutate(edge_group = as.character(.N()$group[1])) |>
 #'   unmorph()
 #'
 #' ggraph(gr, 'matrix', sort.by = node_rank_hclust()) +
diff --git a/R/geom_edge_tile.R b/R/geom_edge_tile.R
index 8ddefba6..85062e76 100644
--- a/R/geom_edge_tile.R
+++ b/R/geom_edge_tile.R
@@ -42,11 +42,11 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('zachary') %>%
-#'   mutate(group = group_infomap()) %>%
-#'   morph(to_split, group) %>%
-#'   activate(edges) %>%
-#'   mutate(edge_group = as.character(.N()$group[1])) %>%
+#' gr <- create_notable('zachary') |>
+#'   mutate(group = group_infomap()) |>
+#'   morph(to_split, group) |>
+#'   activate(edges) |>
+#'   mutate(edge_group = as.character(.N()$group[1])) |>
 #'   unmorph()
 #'
 #' ggraph(gr, 'matrix', sort.by = node_rank_hclust()) +
diff --git a/R/geom_node_point.R b/R/geom_node_point.R
index e39423ff..b50b099a 100644
--- a/R/geom_node_point.R
+++ b/R/geom_node_point.R
@@ -29,7 +29,7 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('bull') %>%
+#' gr <- create_notable('bull') |>
 #'   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 #'
 #' ggraph(gr, 'stress') + geom_node_point()
diff --git a/R/geom_node_text.R b/R/geom_node_text.R
index 7ff3cca4..0f458105 100644
--- a/R/geom_node_text.R
+++ b/R/geom_node_text.R
@@ -40,7 +40,7 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('bull') %>%
+#' gr <- create_notable('bull') |>
 #'   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 #'
 #' ggraph(gr, 'stress') +
diff --git a/R/geom_node_tile.R b/R/geom_node_tile.R
index 26ac0b30..eb93bab9 100644
--- a/R/geom_node_tile.R
+++ b/R/geom_node_tile.R
@@ -34,7 +34,7 @@
 #' @examples
 #' # Create a graph of the flare class system
 #' library(tidygraph)
-#' flareGraph <- tbl_graph(flare$vertices, flare$edges) %>%
+#' flareGraph <- tbl_graph(flare$vertices, flare$edges) |>
 #'   mutate(
 #'     class = map_bfs_chr(node_is_root(), .f = function(node, dist, path, ...) {
 #'       if (dist <= 1) {
diff --git a/R/geom_node_voronoi.R b/R/geom_node_voronoi.R
index 1603afaf..0855cff1 100644
--- a/R/geom_node_voronoi.R
+++ b/R/geom_node_voronoi.R
@@ -32,7 +32,7 @@
 #'
 #' @examples
 #' require(tidygraph)
-#' gr <- create_notable('meredith') %>%
+#' gr <- create_notable('meredith') |>
 #'   mutate(group = sample(letters[1:4], n(), TRUE))
 #'
 #' ggraph(gr) +
diff --git a/R/layout_stress.R b/R/layout_stress.R
index b67597d8..7b06259d 100644
--- a/R/layout_stress.R
+++ b/R/layout_stress.R
@@ -38,6 +38,7 @@
 #' by David Schoch
 #'
 #' @importFrom graphlayouts layout_with_stress layout_with_constrained_stress layout_with_fixed_coords
+#' @importFrom igraph gorder
 #' @importFrom rlang eval_tidy enquo
 #'
 layout_tbl_graph_stress <- function(graph, weights = NULL, niter = 500,
@@ -55,18 +56,15 @@ layout_tbl_graph_stress <- function(graph, weights = NULL, niter = 500,
   if (is.null(x_coord) && is.null(y_coord)) {
     xy <- layout_with_stress(graph, weights = weights, iter = niter,
                              tol = tolerance, mds = mds, bbox = bbox)
-  } else if (!is.null(x_coord) && !is.null(y_coord)) {
-    xy <- cbind(x_coord, y_coord)
+  } else {
+    xy <- cbind(x_coord %||% NA, y_coord %||% NA)
+    if (nrow(xy) != gorder(graph)) {
+      cli::cli_abort("If {.arg x_coord} and/or {.arg y_coord} is given they must equal the number of nodes in the graph")
+    }
     if (anyNA(xy)) {
       xy <- layout_with_fixed_coords(graph, xy, weights = weights, iter = niter,
                                      tol = tolerance, mds = mds, bbox = bbox)
     }
-  } else {
-    dim <- if (is.null(x_coord)) "y" else "x"
-    coord <- if (is.null(x_coord)) y_coord else x_coord
-    xy <- layout_with_constrained_stress(graph, coord = coord, fixdim = dim,
-                                         weights = weights, iter = niter,
-                                         tol = tolerance, mds = mds, bbox = bbox)
   }
 
   nodes <- data_frame0(x = xy[,1],y = xy[,2], circular = FALSE)
diff --git a/README.Rmd b/README.Rmd
index 0b82e442..6a2d8c13 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -36,7 +36,7 @@ library(ggraph)
 library(tidygraph)
 
 # Create graph of highschool friendships
-graph <- as_tbl_graph(highschool) %>% 
+graph <- as_tbl_graph(highschool) |> 
     mutate(Popularity = centrality_degree(mode = 'in'))
 
 # plot using ggraph
diff --git a/README.md b/README.md
index d3c46a7f..8bc0b93a 100644
--- a/README.md
+++ b/README.md
@@ -35,7 +35,7 @@ library(tidygraph)
 #>     filter
 
 # Create graph of highschool friendships
-graph <- as_tbl_graph(highschool) %>% 
+graph <- as_tbl_graph(highschool) |> 
     mutate(Popularity = centrality_degree(mode = 'in'))
 
 # plot using ggraph
diff --git a/man/autograph.Rd b/man/autograph.Rd
index 861d9cbe..b04cae3a 100644
--- a/man/autograph.Rd
+++ b/man/autograph.Rd
@@ -41,7 +41,7 @@ it should be created manually.
 }
 \examples{
 library(tidygraph)
-gr <- create_notable('herschel') \%>\%
+gr <- create_notable('herschel') |>
   mutate(class = sample(letters[1:3], n(), TRUE)) \%E>\%
   mutate(weight = runif(n()))
 
diff --git a/man/facet_graph.Rd b/man/facet_graph.Rd
index 038c7889..63a6c524 100644
--- a/man/facet_graph.Rd
+++ b/man/facet_graph.Rd
@@ -87,7 +87,7 @@ each panel (even when nodes are not drawn).
 }
 \examples{
 library(tidygraph)
-gr <- as_tbl_graph(highschool) \%>\%
+gr <- as_tbl_graph(highschool) |>
   mutate(popularity = as.character(cut(centrality_degree(mode = 'in'),
     breaks = 3,
     labels = c('low', 'medium', 'high')
diff --git a/man/facet_nodes.Rd b/man/facet_nodes.Rd
index 82b08391..35e348e0 100644
--- a/man/facet_nodes.Rd
+++ b/man/facet_nodes.Rd
@@ -77,7 +77,7 @@ panel.
 }
 \examples{
 library(tidygraph)
-gr <- as_tbl_graph(highschool) \%>\%
+gr <- as_tbl_graph(highschool) |>
   mutate(popularity = as.character(cut(centrality_degree(mode = 'in'),
     breaks = 3,
     labels = c('low', 'medium', 'high')
diff --git a/man/geom_axis_hive.Rd b/man/geom_axis_hive.Rd
index 0b9ec3be..73a6ea86 100644
--- a/man/geom_axis_hive.Rd
+++ b/man/geom_axis_hive.Rd
@@ -78,15 +78,15 @@ geom_axis_hive understand the following aesthetics.
 \examples{
 # Plot the flare import graph as a hive plot
 library(tidygraph)
-flareGr <- as_tbl_graph(flare$imports) \%>\%
+flareGr <- as_tbl_graph(flare$imports) |>
   mutate(
     type = dplyr::case_when(
       centrality_degree(mode = 'in') == 0 ~ 'Source',
       centrality_degree(mode = 'out') == 0 ~ 'Sink',
       TRUE ~ 'Both'
     )
-  ) \%>\%
-  activate(edges) \%>\%
+  ) |>
+  activate(edges) |>
   mutate(
     type = dplyr::case_when(
       grepl('flare.analytics', paste(.N()$name[from], .N()$name[to])) ~ 'Analytics',
diff --git a/man/geom_conn_bundle.Rd b/man/geom_conn_bundle.Rd
index 17040dcb..67a1785c 100644
--- a/man/geom_conn_bundle.Rd
+++ b/man/geom_conn_bundle.Rd
@@ -119,7 +119,7 @@ automatically set, but can be overwritten.
 \examples{
 # Create a graph of the flare class system
 library(tidygraph)
-flareGraph <- tbl_graph(flare$vertices, flare$edges) \%>\%
+flareGraph <- tbl_graph(flare$vertices, flare$edges) |>
   mutate(
     class = map_bfs_chr(node_is_root(), .f = function(node, dist, path, ...) {
       if (dist <= 1) {
diff --git a/man/geom_edge_arc.Rd b/man/geom_edge_arc.Rd
index 08304490..410e06c5 100644
--- a/man/geom_edge_arc.Rd
+++ b/man/geom_edge_arc.Rd
@@ -255,14 +255,14 @@ automatically be renamed appropriately.
 \examples{
 require(tidygraph)
 # Make a graph with different directions of edges
-gr <- create_notable('Meredith') \%>\%
-  convert(to_directed) \%>\%
-  mutate(class = sample(letters[1:3], n(), replace = TRUE)) \%>\%
-  activate(edges) \%>\%
+gr <- create_notable('Meredith') |>
+  convert(to_directed) |>
+  mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+  activate(edges) |>
   mutate(
     class = sample(letters[1:3], n(), replace = TRUE),
     switch = sample(c(TRUE, FALSE), n(), replace = TRUE)
-  ) \%>\%
+  ) |>
   reroute(from = to, to = from, subset = switch)
 
 ggraph(gr, 'linear') +
diff --git a/man/geom_edge_bend.Rd b/man/geom_edge_bend.Rd
index 3690cc5a..979554b9 100644
--- a/man/geom_edge_bend.Rd
+++ b/man/geom_edge_bend.Rd
@@ -243,9 +243,9 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-gr <- create_tree(20, 4) \%>\%
-  mutate(class = sample(letters[1:3], n(), replace = TRUE)) \%>\%
-  activate(edges) \%>\%
+gr <- create_tree(20, 4) |>
+  mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+  activate(edges) |>
   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 
 ggraph(gr, 'tree') +
diff --git a/man/geom_edge_density.Rd b/man/geom_edge_density.Rd
index 33f0dfa9..cf2e5925 100644
--- a/man/geom_edge_density.Rd
+++ b/man/geom_edge_density.Rd
@@ -81,8 +81,8 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('bull') \%>\%
-  activate(edges) \%>\%
+gr <- create_notable('bull') |>
+  activate(edges) |>
   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 
 ggraph(gr, 'stress') +
diff --git a/man/geom_edge_diagonal.Rd b/man/geom_edge_diagonal.Rd
index 9f329e9d..e21da91e 100644
--- a/man/geom_edge_diagonal.Rd
+++ b/man/geom_edge_diagonal.Rd
@@ -247,9 +247,9 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-gr <- create_tree(20, 4) \%>\%
-  mutate(class = sample(letters[1:3], n(), replace = TRUE)) \%>\%
-  activate(edges) \%>\%
+gr <- create_tree(20, 4) |>
+  mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+  activate(edges) |>
   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 
 ggraph(gr, 'tree') +
diff --git a/man/geom_edge_elbow.Rd b/man/geom_edge_elbow.Rd
index 6390a9fd..0da0063d 100644
--- a/man/geom_edge_elbow.Rd
+++ b/man/geom_edge_elbow.Rd
@@ -248,10 +248,10 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-irisDen <- hclust(dist(iris[1:4], method = 'euclidean'), method = 'ward.D2') \%>\%
-  as_tbl_graph() \%>\%
-  mutate(class = sample(letters[1:3], n(), TRUE)) \%>\%
-  activate(edges) \%>\%
+irisDen <- hclust(dist(iris[1:4], method = 'euclidean'), method = 'ward.D2') |>
+  as_tbl_graph() |>
+  mutate(class = sample(letters[1:3], n(), TRUE)) |>
+  activate(edges) |>
   mutate(class = sample(letters[1:3], n(), TRUE))
 
 ggraph(irisDen, 'dendrogram', circular = TRUE) +
diff --git a/man/geom_edge_fan.Rd b/man/geom_edge_fan.Rd
index c2228201..2c8168e1 100644
--- a/man/geom_edge_fan.Rd
+++ b/man/geom_edge_fan.Rd
@@ -249,8 +249,8 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('bull') \%>\%
-  convert(to_directed) \%>\%
+gr <- create_notable('bull') |>
+  convert(to_directed) |>
   bind_edges(data.frame(from = c(1, 2, 2, 3), to = c(2, 1, 3, 2))) \%E>\%
   mutate(class = sample(letters[1:3], 9, TRUE)) \%N>\%
   mutate(class = sample(c('x', 'y'), 5, TRUE))
diff --git a/man/geom_edge_hive.Rd b/man/geom_edge_hive.Rd
index a07559ee..8e221cbe 100644
--- a/man/geom_edge_hive.Rd
+++ b/man/geom_edge_hive.Rd
@@ -245,15 +245,15 @@ automatically be renamed appropriately.
 \examples{
 # Plot the flare import graph as a hive plot
 library(tidygraph)
-flareGr <- as_tbl_graph(flare$imports) \%>\%
+flareGr <- as_tbl_graph(flare$imports) |>
   mutate(
     type = dplyr::case_when(
       centrality_degree(mode = 'in') == 0 ~ 'Source',
       centrality_degree(mode = 'out') == 0 ~ 'Sink',
       TRUE ~ 'Both'
     )
-  ) \%>\%
-  activate(edges) \%>\%
+  ) |>
+  activate(edges) |>
   mutate(
     type = dplyr::case_when(
       grepl('flare.analytics', paste(.N()$name[from], .N()$name[to])) ~ 'Analytics',
diff --git a/man/geom_edge_link.Rd b/man/geom_edge_link.Rd
index 0ca72b18..e83093e4 100644
--- a/man/geom_edge_link.Rd
+++ b/man/geom_edge_link.Rd
@@ -228,9 +228,9 @@ aesthetics.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('bull') \%>\%
-  mutate(class = sample(letters[1:3], n(), replace = TRUE)) \%>\%
-  activate(edges) \%>\%
+gr <- create_notable('bull') |>
+  mutate(class = sample(letters[1:3], n(), replace = TRUE)) |>
+  activate(edges) |>
   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 
 ggraph(gr, 'stress') +
diff --git a/man/geom_edge_parallel.Rd b/man/geom_edge_parallel.Rd
index 119a2d6e..6737bede 100644
--- a/man/geom_edge_parallel.Rd
+++ b/man/geom_edge_parallel.Rd
@@ -237,8 +237,8 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('bull') \%>\%
-  convert(to_directed) \%>\%
+gr <- create_notable('bull') |>
+  convert(to_directed) |>
   bind_edges(data.frame(from = c(1, 2, 2, 3), to = c(2, 1, 3, 2))) \%E>\%
   mutate(class = sample(letters[1:3], 9, TRUE)) \%N>\%
   mutate(class = sample(c('x', 'y'), 5, TRUE))
diff --git a/man/geom_edge_point.Rd b/man/geom_edge_point.Rd
index de6533c6..29dafda0 100644
--- a/man/geom_edge_point.Rd
+++ b/man/geom_edge_point.Rd
@@ -73,11 +73,11 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('zachary') \%>\%
-  mutate(group = group_infomap()) \%>\%
-  morph(to_split, group) \%>\%
-  activate(edges) \%>\%
-  mutate(edge_group = as.character(.N()$group[1])) \%>\%
+gr <- create_notable('zachary') |>
+  mutate(group = group_infomap()) |>
+  morph(to_split, group) |>
+  activate(edges) |>
+  mutate(edge_group = as.character(.N()$group[1])) |>
   unmorph()
 
 ggraph(gr, 'matrix', sort.by = node_rank_hclust()) +
diff --git a/man/geom_edge_tile.Rd b/man/geom_edge_tile.Rd
index 4f9d48a6..5d537eee 100644
--- a/man/geom_edge_tile.Rd
+++ b/man/geom_edge_tile.Rd
@@ -73,11 +73,11 @@ automatically be renamed appropriately.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('zachary') \%>\%
-  mutate(group = group_infomap()) \%>\%
-  morph(to_split, group) \%>\%
-  activate(edges) \%>\%
-  mutate(edge_group = as.character(.N()$group[1])) \%>\%
+gr <- create_notable('zachary') |>
+  mutate(group = group_infomap()) |>
+  morph(to_split, group) |>
+  activate(edges) |>
+  mutate(edge_group = as.character(.N()$group[1])) |>
   unmorph()
 
 ggraph(gr, 'matrix', sort.by = node_rank_hclust()) +
diff --git a/man/geom_node_point.Rd b/man/geom_node_point.Rd
index 9fde81c2..77367a6c 100644
--- a/man/geom_node_point.Rd
+++ b/man/geom_node_point.Rd
@@ -71,7 +71,7 @@ automatically set, but can be overwritten.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('bull') \%>\%
+gr <- create_notable('bull') |>
   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 
 ggraph(gr, 'stress') + geom_node_point()
diff --git a/man/geom_node_text.Rd b/man/geom_node_text.Rd
index a2d8e49c..28673d4c 100644
--- a/man/geom_node_text.Rd
+++ b/man/geom_node_text.Rd
@@ -117,7 +117,7 @@ not set by default
 
 \examples{
 require(tidygraph)
-gr <- create_notable('bull') \%>\%
+gr <- create_notable('bull') |>
   mutate(class = sample(letters[1:3], n(), replace = TRUE))
 
 ggraph(gr, 'stress') +
diff --git a/man/geom_node_tile.Rd b/man/geom_node_tile.Rd
index efbf7d3d..433af3d8 100644
--- a/man/geom_node_tile.Rd
+++ b/man/geom_node_tile.Rd
@@ -76,7 +76,7 @@ automatically set, but can be overwritten.
 \examples{
 # Create a graph of the flare class system
 library(tidygraph)
-flareGraph <- tbl_graph(flare$vertices, flare$edges) \%>\%
+flareGraph <- tbl_graph(flare$vertices, flare$edges) |>
   mutate(
     class = map_bfs_chr(node_is_root(), .f = function(node, dist, path, ...) {
       if (dist <= 1) {
diff --git a/man/geom_node_voronoi.Rd b/man/geom_node_voronoi.Rd
index d50ba31b..1674d0f5 100644
--- a/man/geom_node_voronoi.Rd
+++ b/man/geom_node_voronoi.Rd
@@ -114,7 +114,7 @@ automatically set, but can be overwritten.
 
 \examples{
 require(tidygraph)
-gr <- create_notable('meredith') \%>\%
+gr <- create_notable('meredith') |>
   mutate(group = sample(letters[1:4], n(), TRUE))
 
 ggraph(gr) +
diff --git a/vignettes/Edges.Rmd b/vignettes/Edges.Rmd
index 1a90fe40..9904f8de 100644
--- a/vignettes/Edges.Rmd
+++ b/vignettes/Edges.Rmd
@@ -43,7 +43,7 @@ library(purrr)
 library(rlang)
 
 set_graph_style(plot_margin = margin(1,1,1,1))
-hierarchy <- as_tbl_graph(hclust(dist(iris[, 1:4]))) %>% 
+hierarchy <- as_tbl_graph(hclust(dist(iris[, 1:4]))) |> 
   mutate(Class = map_bfs_back_chr(node_is_root(), .f = function(node, path, ...) {
     if (leaf[node]) {
       as.character(iris$Species[as.integer(label[node])])
@@ -57,10 +57,10 @@ hierarchy <- as_tbl_graph(hclust(dist(iris[, 1:4]))) %>%
     }
   }))
 
-hairball <- as_tbl_graph(highschool) %>% 
+hairball <- as_tbl_graph(highschool) |> 
   mutate(
     year_pop = map_local(mode = 'in', .f = function(neighborhood, ...) {
-      neighborhood %E>% pull(year) %>% table() %>% sort(decreasing = TRUE)
+      neighborhood %E>% pull(year) |> table() |> sort(decreasing = TRUE)
     }),
     pop_devel = map_chr(year_pop, function(pop) {
       if (length(pop) == 0 || length(unique(pop)) == 1) return('unchanged')
@@ -69,8 +69,8 @@ hairball <- as_tbl_graph(highschool) %>%
              '1958' = 'increased')
     }),
     popularity = map_dbl(year_pop, ~ .[1]) %|% 0
-  ) %>% 
-  activate(edges) %>% 
+  ) |> 
+  activate(edges) |> 
   mutate(year = as.character(year))
 ```
 
@@ -119,7 +119,7 @@ Loops cannot be shown with regular edges as they have no length. A dedicated
 
 ```{r}
 # let's make some of the student love themselves
-loopy_hairball <- hairball %>% 
+loopy_hairball <- hairball |> 
   bind_edges(tibble::tibble(from = 1:5, to = 1:5, year = rep('1957', 5)))
 ggraph(loopy_hairball, layout = 'stress') + 
   geom_edge_link(aes(colour = year), alpha = 0.25) + 
@@ -167,6 +167,54 @@ ggraph(hairball, layout = 'linear', circular = TRUE) +
   coord_fixed()
 ```
 
+### Bundling
+Edge bundling is a technique to reduce clutter in a network visualization by
+bundling edges that flows in the same direction. There are various ways of doing
+this, many with heavy computational cost and the potential to mislead. The 
+technique were initially confined to connections between nodes with a 
+[hierarchical structure](#Connections) but has been expanded to general graphs.
+ggraph provides 3 different bundling geoms with various up- and downsides. 
+
+#### Force directed
+This is perhaps the most classic. It treats the edges as an array of points with
+the propensity to attract each other if edges are parallel. It suffers from bad
+performance (though the edge bundling geoms uses memoisation to avoid 
+recomputations) and can also be misleading as it doesn't use the underlying 
+topology of the graph to determine if edges should be bundled, only whether they
+are parallel.
+
+```{r}
+ggraph(hairball) + 
+  geom_edge_bundle_force(n_cycle = 2, threshold = 0.4)
+```
+
+#### Edge path
+An alternative is to let the edges follow the shortest paths rather than 
+attract each other. This means the topology is being used in the bundling and
+in theory lead to less misleading results. It also has the upside of being 
+faster. The algorithm is iterative so that if an edge has been bundled it is
+deleted from the graph where the shortest path is being searched in. In this
+way the edges naturally converge towards a few "highways".
+
+```{r}
+ggraph(hairball) + 
+  geom_edge_bundle_path()
+```
+
+#### Minimal
+In the same vein as edge path bundling but even simpler, you can use the minimal
+spanning tree of the graph as the scaffold to bundle edges along. As such, it 
+changes to the hierarchical edge bundling approach, just with an implicit 
+hierarchy calculated on the graph. This method is very fast but does create bias
+in the output as edges will (obviously) travel along the minimal spanning tree 
+thus amplifying that topology.
+
+```{r}
+ggraph(hairball) + 
+  geom_edge_bundle_minimal()
+```
+
+
 ### Elbow
 Aah... The classic dendrogram with its right angle bends. Of course such
 visualizations are also supported with the `geom_edge_elbow()`. It goes without
@@ -321,9 +369,9 @@ see the effect here we will use a slightly simpler graph
 
 ```{r}
 # Random names - I swear
-simple <- create_notable('bull') %>% 
-  mutate(name = c('Thomas', 'Bob', 'Hadley', 'Winston', 'Baptiste')) %>% 
-  activate(edges) %>% 
+simple <- create_notable('bull') |> 
+  mutate(name = c('Thomas', 'Bob', 'Hadley', 'Winston', 'Baptiste')) |> 
+  activate(edges) |> 
   mutate(type = sample(c('friend', 'foe'), 5, TRUE))
 ```
 
diff --git a/vignettes/Layouts.Rmd b/vignettes/Layouts.Rmd
index 390ed8f7..f8def4e8 100644
--- a/vignettes/Layouts.Rmd
+++ b/vignettes/Layouts.Rmd
@@ -176,7 +176,7 @@ Below is a sample of some of the layouts available through `igraph` applied to
 the highschool graph.
 
 ```{r, fig.show='hold', results='hide'}
-graph <- as_tbl_graph(highschool) %>% 
+graph <- as_tbl_graph(highschool) |> 
   mutate(degree = centrality_degree())
 lapply(c('stress', 'fr', 'lgl', 'graphopt'), function(layout) {
   ggraph(graph, layout = layout) + 
@@ -186,6 +186,13 @@ lapply(c('stress', 'fr', 'lgl', 'graphopt'), function(layout) {
 })
 ```
 
+The default plot is the `"stress"` layout that uses stress majorization to 
+spread out nodes. It generally does a good job and is deterministic so that it
+doesn't change upon every call (many other layouts does that as they use 
+randomisation for the initial node positions). The stress layout also makes it
+possible to fix the location of certain nodes in one or two dimensions making it
+a very versatile starting point for your visualisation.
+
 ### Hive plots
 A hive plot, while still technically a node-edge diagram, is a bit different
 from the rest as it uses information pertaining to the nodes, rather than the
@@ -195,7 +202,7 @@ graph structure. They are less common though, so use will often require some
 additional explanation.
 
 ```{r}
-graph <- graph %>% 
+graph <- graph |> 
   mutate(friends = ifelse(
     centrality_degree(mode = 'in') < 5, 'few',
     ifelse(centrality_degree(mode = 'in') >= 15, 'many', 'medium')
@@ -314,8 +321,8 @@ implicitly position a node at the root. To avoid that you can use the `unrooted`
 layout instead.
 
 ```{r}
-tree <- create_tree(100, 2, directed = FALSE) %>% 
-  activate(edges) %>% 
+tree <- create_tree(100, 2, directed = FALSE) |> 
+  activate(edges) |> 
   mutate(length = runif(n()))
 ggraph(tree, 'unrooted', length = length) + 
   geom_edge_link()
@@ -377,6 +384,39 @@ ggraph(graph, 'fabric', sort.by = node_rank_fabric(), shadow.edges =TRUE) +
   coord_fixed()
 ```
 
+### Spatial layouts
+ggraph has a few layouts aimed at data where the node has a physical location. 
+You may think this requires no layout at all and to some extent you are correct.
+
+ggraph supports spatial networks through the sfnetworks package and grabs the 
+node position and CRS from the data correctly when using the "sf" layout:
+
+```{r}
+gr <- sfnetworks::as_sfnetwork(sfnetworks::roxel)
+
+ggraph(gr, 'sf') + 
+  geom_edge_sf(aes(color = type)) + 
+  geom_node_sf(size = 0.3)
+```
+
+Another type of spatial layout is the metro layout which takes in a prior 
+position and attempts to make these positions fit into a grid-like structure,
+well known in railroad and metro maps.
+
+```{r}
+gr <- create_notable('Walther')
+# Use stress layout to come up with a initial position
+prior <- create_layout(gr, 'stress')
+
+# Optimise placement with metro layout
+ggraph(gr, 'metro', x = prior$x, y = prior$y, grid_space = 1, max_movement = 50) + 
+  geom_edge_link(width = 4) + 
+  geom_node_point(size = 10) + 
+  geom_edge_link(color = 'white', width = 1) + 
+  geom_node_point(color = 'white', size = 4)
+```
+
+
 ## Want more?
 Check out the other vignettes for more information on how to draw 
 [nodes](Nodes.html) and [edges](Edges.html)...
diff --git a/vignettes/Nodes.Rmd b/vignettes/Nodes.Rmd
index 9a2ed889..b9ae0943 100644
--- a/vignettes/Nodes.Rmd
+++ b/vignettes/Nodes.Rmd
@@ -105,7 +105,7 @@ from a voronoi tesselation. This is useful for e.g. showing dominance of certain
 node types in an area as overlapping is avoided:
 
 ```{r}
-graph <- create_notable('meredith') %>% 
+graph <- create_notable('meredith') |> 
   mutate(group = sample(c('A', 'B'), n(), TRUE))
 
 ggraph(graph, 'stress') +