Package ontologyplot

Transcription

1 Type Package Package Plot October 28, 2016 Title Functions for Visualising Sets of Ontological Terms Version 1.4 Date Author Daniel Greene Maintainer Daniel Greene Functions for visualising sets of ontological using the 'graphviz' layout system. License GPL (>= 2) Depends R (>= 3.0.0) Imports methods, Index, paintmap, Rgraphviz Suggests knitr VignetteBuilder knitr RoxygenNote NeedsCompilation no Repository CRAN Date/Publication :13:50 R topics documented: annotation_grid calibrate_sizes colour_by_frequency colour_by_population_frequency colour_by_term_set dot_string get_adjacency_matrix get_node_friendly_long_names get plot get_pseudo_adjacency_matrix get_shortened_names grid_

2 2 annotation_grid label_by_frequency label_by_term_set long_labels n_most_frequent_ official_labels Plot onto_plot plot._plot plot_annotation_grid print._plot p_values_for_occurrence_of_term_in_group remove_links remove with_less_than_n_occurrences remove_uninformative_ simple_cap simple_labels to_svg_string width_by_frequency width_by_significance write_dot Index 24 annotation_grid Get logical matrix of term annotation for group of cases Get logical matrix of term annotation for group of cases annotation_grid(,, all_ = grid_(, ), remove_unanimous = FALSE, cluster_rows = TRUE, cluster_cols = TRUE) _index object all_ Character vector giving to use in annotation. remove_unanimous Logical value determining whether to remove present in all. cluster_rows cluster_cols Logical value rows determining whether to use hclust to cluster. Logical value rows determining whether to use hclust to cluster (based on correlation of inclusion in ).

3 calibrate_sizes 3 Logical matrix. calibrate_sizes Function to scale values between two given limits Could be useful to modify a vector of sizes to between, say 1 and 3, before passing to onto_plot. calibrate_sizes(x, high, low) x high low Numeric vector Numeric value of largest size Numeric value of smallest size Numeric vector Examples calibrate_sizes(c("hp: "=10, "HP: "=5), high=3, low=1) colour_by_frequency Function to assign colours to based on frequency with which appear in Function to assign colours to based on frequency with which appear in colour_by_frequency(,,, colour_func = colorramppalette(c("yellow", "Green", "#0099FF")))

4 4 colour_by_population_frequency colour_func _index object Character vector of ontological Function capable of returning a set of colours, given the number of colours it needs to return Character vector of colours, named by term colour_by_term_set, colour_by_population_frequency colour_by_population_frequency Function to assign colours to based on population frequency of Function to assign colours to based on population frequency of colour_by_population_frequency(,, frequencies, colour_palette = colorramppalette(c("yellow", "Green", "#0099FF"))(10), max_colour_freq = max(_freq), min_colour_freq = min(_freq)) frequencies _index object Character vector of ontological Numeric vector of term frequencies named by term IDs colour_palette Character vector of colours for the different information contents of the to be plotted, going from rare to common max_colour_freq Numeric value in [0, 1] giving the maximum frequency (to which the dullest color will be assigned) min_colour_freq Numeric value in [0, 1] giving the minimum frequency (to which the brightest color will be assigned)

5 colour_by_term_set 5 Character vector of colours, named by term colour_by_term_set, colour_by_frequency colour_by_term_set Function to set colours of nodes in plot to distinguish belonging to different term sets Function to set colours of nodes in plot to distinguish belonging to different term sets colour_by_term_set(,,, colour_generator = rainbow, alpha = 0.5) _index object Character vector of ontological colour_generator Function which returns a vector of colours, e.g. rainbow or heat.colors. alpha alpha parameter to pass to colour_generator. Character vector of colours, named by term. colour_by_frequency, colour_by_population_frequency

6 6 get_adjacency_matrix dot_string _plot object to dot string _plot object to dot string dot_string(_plot) _plot Object of class _plot to export. String onto_plot get_adjacency_matrix Get an adjacency matrix for a set of ontological Get an adjacency matrix for a set of ontological get_adjacency_matrix(, ) _index object Character vector of ontological A logical matrix representing the adjacency matrix of based on the directed acyclic graph of. A TRUE entry means the term correspnding to the column is a parent of the row term in.

7 get_node_friendly_long_names 7 get_pseudo_adjacency_matrix Examples library(index) data(hpo) get_adjacency_matrix(hpo, c("hp: ", "HP: ", "HP: ")) get_node_friendly_long_names Split up node labels across lines so they fit in nodes better Split up node labels across lines so they fit in nodes better get_node_friendly_long_names(,, official_names = FALSE) _index object Character vector of ontological official_names Logical value indicating whether to use the exact names from the. Otherwise, shortened, capitalised names are used. Character vector. Examples library(index) data(hpo) get_node_friendly_long_names(hpo, c("hp: ", "HP: "))

8 8 get_pseudo_adjacency_matrix get plot Get _plot object Function to create _plot objects where all graphical parameters to be used must be specified. get plot(,, edge_attributes = list(color = "#000000", lty = "solid"),...) _index object Character vector of ontological edge_attributes List of properties to set for arrows (note, these properties will be used for all arrow).... Named graphical parameters. These must either be vectors of values the same length as, or of length 1 if they should be used for all. _plot object. get_pseudo_adjacency_matrix Get an adjacency matrix for a set of ontological Get an adjacency matrix for a set of ontological get_pseudo_adjacency_matrix(, ) _index object Character vector of ontological

9 get_shortened_names 9 A logical matrix representing the adjacency matrix of based on the directed acyclic graph of. A TRUE entry means the term correspnding to the column is a parent of the row term within. get_adjacency_matrix Examples library(index) data(hpo) get_pseudo_adjacency_matrix(hpo, c("hp: ", "HP: ", "HP: ")) get_shortened_names Get human readable, shortened (where possible) ontological term names Get human readable, shortened (where possible) ontological term names get_shortened_names(, ) _index object Character vector of ontological Character vector Examples library(index) data(hpo) get_shortened_names(hpo, c("hp: ", "HP: "))

10 10 label_by_frequency grid_ Get set of HPO appropriate for showing in a grid Get set of HPO appropriate for showing in a grid grid_(, ) _index object Character vector of terme IDs. label_by_frequency Function to get plot labels for based on frequency in Function to get plot labels for based on frequency in label_by_frequency(,, ) _index object Character vector of ontological Character vector of labels, named by term. simple_labels, long_labels

11 label_by_term_set 11 label_by_term_set Function to label nodes by term_set Function to label nodes by term_set label_by_term_set(,, ) _index object Character vector of ontological Character vector of colours, named by term. simple_labels, label_by_frequency, long_labels long_labels Function to assign detailed node labels to Label includes term ID, term name, number of instances of term amongst and percentage frequency in population. long_labels(,,, frequencies) frequencies _index object Character vector of ontological Numeric vector of term frequencies named by term IDs

12 12 n_most_frequent_ Character vector of labels, named by term. simple_labels, label_by_frequency, label_by_term_set n_most_frequent_ Select n most prevalent in Selects n most prevalent in set of term sets/annotations including implicit. If more than one term are tied at the nth position, all are included in the result. n_most_frequent_(,, n, = unique(unlist())) n _index object Integer Character vector of ontological Character vector of length at most n remove with_less_than_n_occurrences Examples library(index) data(hpo) n_most_frequent_(hpo, c("hp: "), list(=list("hp: ", "HP: ")), n=2)

13 Plot 13 official_labels Get official names for Get official names for official_labels(, ) _index object Character vector of ontological Character vector of labels, named by term. simple_labels Plot Functions for Visualising Sets of Ontological Terms Details Functions for visualising sets of ontological using the graphviz layout system. Package: Plot Type: Package Version: 1.0 Date: License: GPL (>= 2) This package succeeds the package hpoplot with an improved interface and focusing on general ontologies. The key function is onto_plot, which creates an object of class _plot which can be displayed as a graph or exported to dot format.

14 14 onto_plot Author(s) Daniel Greene Maintainer: Daniel Greene References The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data, Nucl. Acids Res. (1 January 2014) 42 (D1): D966-D974 doi: /nar/gkt1026 Westbury, S. K. et al. (2015). Human Phenotype Ontology annotation and cluster analysis to un- ravel genetic defects in 707 cases with unexplained bleeding and platelet disorders. Genome Medicine. 7 (2015) onto_plot Get _plot object A convenience wrapper for the get plot function, enabling functions to be passed to generate graphical parameters for automatically. onto_plot(, = NULL, frequencies = NULL, = remove_uninformative_(, ), edge_attributes = list(color = "#000000", lty = "solid"), fillcolor = "powderblue", label = simple_labels, color = "transparent", width = 0.75, fontsize = 30, style = "filled", fixedsize = "true", shape = "circle",...) frequencies _index object Numeric vector of term frequencies named by term IDs Character vector of ontological edge_attributes List of properties to set for arrows (note, these properties will be used for all arrow). fillcolor label color width Character vector of colours to fill nodes corresponding to with. Alternatively a function to set the colours of the nodes in the graph based on. Character vector of labels (or function to set them). Character vector of colours for borders of nodes representing (or function to set them). Numeric vector of widths for nodes (of function to set them).

15 plot._plot 15 fontsize style fixedsize shape Numeric vector of font sizes for the text to be placed in the nodes (or function to set them). Display style for nodes, defaults to "filled". Character indicating whether nodes should be fixed size, "true", or adjusted to fit around the contained text, "false". Character vector of shape names for nodes (or function to set them). Defaults to "circle".... Other node attributes for dot format. _plot object. get plot, write_dot Examples library(index) data(hpo) hpo_phenotypes <- c( A=c("HP: ","HP: ","HP: ","HP: ","HP: "), B=c("HP: ","HP: ","HP: ","HP: ","HP: "), C=c("HP: ","HP: ","HP: ","HP: ","HP: "), D=c("HP: ","HP: ","HP: ","HP: ","HP: "), E=c("HP: ","HP: ","HP: ","HP: ","HP: ") ) onto_plot( =hpo, =hpo_phenotypes ) plot._plot Plotting function for _plot object Plotting function for _plot object ## S3 method for class '_plot' plot(x,...)

16 16 print._plot x Object of class ontologicalplot.... Other options passed to plot(). Nothing, side-effect: plots a graph. plot_annotation_grid Plot a logical matrix of term annotation Plot a logical matrix of term annotation plot_annotation_grid(..., on_colour = "#FF0000FF", off_colour = "#FFFFBFFF")... to be passed to annotation_grid. on_colour Colour to use to show presence of term. off_colour Colour to use to show absence of term. Plots heatmap. print._plot Print function for _plot object Print function for _plot object ## S3 method for class '_plot' print(x,...) x Object of class ontologicalplot.... Other options passed to be passed to plot().

17 p_values_for_occurrence_of_term_in_group 17 Nothing. Side-effect: plots graphs. p_values_for_occurrence_of_term_in_group Get p-values for observing at least as many of each term as occur in given the population frequencies of the Get p-values for observing at least as many of each term as occur in given the population frequencies of the p_values_for_occurrence_of_term_in_group(,, _freq) _freq _index object Numeric vector of population frequencies of. Numeric vector of log p-values named by correspnding term. width_by_significance remove_links Remove which just link two other together in a sub Remove which just link two other together in a sub remove_links(,, hard = FALSE)

18 18 remove with_less_than_n_occurrences _index object Character vector of ontological hard Logical value determining whether to multiple edges to leaf are kept - hard=false, or removed - hard=true. Character vector. remove_uninformative_ Examples library(index) data(hpo) remove_links(hpo, c("hp: ","hp: ","hp: ","hp: ")) remove with_less_than_n_occurrences Remove with less than certain number of occurrences Remove with less than certain number of occurrences remove with_less_than_n_occurrences(,, n, = unique(unlist())) n _index object Integer Character vector of ontological Character vector n_most_frequent_

19 remove_uninformative_ 19 Examples library(index) data(hpo) remove with_less_than_n_occurrences(hpo, =list("hp: ", "HP: "), n=2) remove_uninformative_ Remove uninformative from union of all in set of annotations For a set of ontological annotation sets, remove annotated to the same objects as all their children. Useful for selecting for summarising a set of annotation sets, as it can lead to a significant reduction in the number of. remove_uninformative_(, ) _index object Character vector of Examples library(index) data(hpo) remove_uninformative_(hpo, list(patient1=c("hp: ","hp: ")))

20 20 simple_labels simple_cap Capitalise words in character vector Capitalise words in character vector simple_cap(x) x Character vector Character vector Examples simple_cap(c("a simple test", "Another-test")) simple_labels Get simplified labels for Get simplified labels for simple_labels(, ) _index object Character vector of ontological Character vector of labels, named by term. official_labels

21 to_svg_string 21 to_svg_string Convert _plot to SVG string Note that by setting "id" and "class" attributes it enables nodes to be selected for manipulation using Javascript if interactivity is desired. to_svg_string(op) op Object of class _plot. Character vector of length 1 containing SVG representation of node. onto_plot, get plot width_by_frequency Function to get node sizes for based on frequency in Function to get node sizes for based on frequency in width_by_frequency(,, ) _index object Character vector of ontological Character vector of sizes, named by term width_by_significance

22 22 write_dot width_by_significance Function to get node sizes for based on statistical significance of seeing at least this number of each term in Function to get node sizes for based on statistical significance of seeing at least this number of each term in width_by_significance(,,, frequencies) frequencies _index object Character vector of ontological Numeric vector of term frequencies named by term IDs Character vector of sizes, named by term width_by_frequency write_dot Export _plot object as dot file Export _plot object as dot file write_dot(_plot, file) _plot file Object of class _plot to export. Character value of target file path.

23 write_dot 23 Nothing, side effect - writes to file. dot_string

24 Index Topic, HPO, MPO, GO Plot, 13 annotation_grid, 2, 16 calibrate_sizes, 3 colour_by_frequency, 3, 5 colour_by_population_frequency, 4, 4, 5 colour_by_term_set, 4, 5, 5 simple_labels, 10 13, 20 to_svg_string, 21 width_by_frequency, 21, 22 width_by_significance, 17, 21, 22 write_dot, 15, 22 dot_string, 6, 23 get_adjacency_matrix, 6, 9 get_node_friendly_long_names, 7 get plot, 8, 14, 15, 21 get_pseudo_adjacency_matrix, 7, 8 get_shortened_names, 9 grid_, 10 label_by_frequency, 10, 11, 12 label_by_term_set, 11, 12 long_labels, 10, 11, 11 n_most_frequent_, 12, 18 official_labels, 13, 20 onto_plot, 6, 13, 14, 21 Plot, 13 p_values_for_occurrence_of_term_in_group, 17 plot._plot, 15 plot_annotation_grid, 16 print._plot, 16 remove_links, 17 remove with_less_than_n_occurrences, 12, 18 remove_uninformative_, 18, 19 simple_cap, 20 24