R: Layout algorithms based on bi- or other partitions

partition_layouts {manynet}

R Documentation

Layout algorithms based on bi- or other partitions

Description

These algorithms layout networks based on two or more partitions, and are recommended for use with graphr() or {ggraph}. Note that these layout algorithms use {Rgraphviz}, a package that is only available on Bioconductor. It will first need to be downloaded using BiocManager::install("Rgraphviz"). If it has not already been installed, there is a prompt the first time these functions are used though.

The "hierarchy" layout layers the first node set along the bottom, and the second node set along the top, sequenced and spaced as necessary to minimise edge overlap. The "alluvial" layout is similar to "hierarchy", but places successive layers horizontally rather than vertically. The "railway" layout is similar to "hierarchy", but nodes are aligned across the layers. The "ladder" layout is similar to "railway", but places successive layers horizontally rather than vertically. The "concentric" layout places a "hierarchy" layout around a circle, with successive layers appearing as concentric circles. The "multilevel" layout places successive layers as multiple levels. The "lineage" layout ranks nodes in Y axis according to values.

Usage

layout_tbl_graph_hierarchy(
  .data,
  center = NULL,
  circular = FALSE,
  times = 1000
)

layout_tbl_graph_alluvial(.data, circular = FALSE, times = 1000)

layout_tbl_graph_railway(.data, circular = FALSE, times = 1000)

layout_tbl_graph_ladder(.data, circular = FALSE, times = 1000)

layout_tbl_graph_concentric(
  .data,
  membership,
  radius = NULL,
  order.by = NULL,
  circular = FALSE,
  times = 1000
)

layout_tbl_graph_multilevel(.data, level, circular = FALSE)

layout_tbl_graph_lineage(.data, rank, circular = FALSE)

Arguments

`.data`	An object of a manynet-consistent class: matrix (adjacency or incidence) from `{base}` R edgelist, a data frame from `{base}` R or tibble from `{tibble}` igraph, from the `{igraph}` package network, from the `{network}` package tbl_graph, from the `{tidygraph}` package
`center`	Further split "hierarchical" layouts by declaring the "center" argument as the "events", "actors", or by declaring a node name in hierarchy layout. Defaults to NULL.
`circular`	Should the layout be transformed into a radial representation. Only possible for some layouts. Defaults to FALSE.
`times`	Maximum number of iterations, where appropriate
`membership`	A node attribute or a vector to draw concentric circles for "concentric" layout.
`radius`	A vector of radii at which the concentric circles should be located for "concentric" layout. By default this is equal placement around an empty centre, unless one (the core) is a single node, in which case this node occupies the centre of the graph.
`order.by`	An attribute label indicating the (decreasing) order for the nodes around the circles for "concentric" layout. By default ordering is given by a bipartite placement that reduces the number of edge crossings.
`level`	A node attribute or a vector to hierarchically order levels for "multilevel" layout.
`rank`	A numerical node attribute to place nodes in Y axis according to values for "lineage" layout.

Source

Diego Diez, Andrew P. Hutchins and Diego Miranda-Saavedra. 2014. "Systematic identification of transcriptional regulatory modules from protein-protein interaction networks". Nucleic Acids Research, 42 (1) e6.

Examples

#graphr(ison_southern_women, layout = "hierarchy", center = "events",
#           node_color = "type", node_size = 3)
#graphr(ison_southern_women, layout = "alluvial")
#graphr(ison_southern_women, layout = "concentric", membership = "type",
#           node_color = "type", node_size = 3)
#graphr(ison_lotr, layout = "multilevel",
#           node_color = "Race", level = "Race", node_size = 3)
# ison_adolescents %>%
#   mutate(year = rep(c(1985, 1990, 1995, 2000), times = 2),
#          cut = node_is_cutpoint(ison_adolescents)) %>%
#   graphr(layout = "lineage", rank = "year", node_color = "cut",
#              node_size = migraph::node_degree(ison_adolescents)*10)