node_color_per_de {hipathia} | R Documentation

## Colors of the nodes by its differential expression

### Description

Performs a differential expression on the nodes and computes the colors of the nodes depending on it_ Significant up- and down-regulated nodes are depicted with the selected color, with a gradient towards the non-significant color depending on the value of the p-value. Smaller p-values give rise to purer colors than higher p-values.

### Usage

    node_color_per_de(results, metaginfo, group, g1, g2, group_by = "pathway",
      colors = "classic", conf = 0.05)

### Arguments

`results` | Object of results as provided by the `hipathia` function_
`metaginfo` | Object of pathways_
`group` | Character indicating the column in which the group variable is stored, in case the object provided to `hipathia` was a SummarizedExperiment, or a vector with the class to which each sample belongs. Samples must be ordered as in `results`.
`g1` | String, label of the first group to be compared
`g2` | String, label of the second group to be compared
`group_by` | How to group the subpathways to be visualized. By default they are grouped by the pathway to which they belong. Available groupings include "uniprot", to group subpathways by their annotated Uniprot functions, "GO", to group subpathways by their annotated GO terms, and "genes", to group subpathways by the genes they include. Default is set to "pathway".
`colors` | Either a character vector with 3 colors (indicating, in this order, down-regulation, non-significance and up-regulation colors) or a key name indicating the color scheme to be used. Options are:
`conf` | Level of significance of the comparison for the adjusted p-value

### Value

List of color vectors, named by the pathways to which they belong. The color vectors represent the differential expression of the nodes in each pathway.

### Slots

`classic`

  ColorBrewer blue, white and colorBrewer red.

`hipathia`

  Hipathia predefined color scheme: Green, white and orange. By default `classic` color scheme is applied.

### Examples

    data(results)
    data(brca)
    pathways <- load_pathways(species = "hsa", pathways_list = c("hsa03320",
    "hsa04012"))
    sample_group <- colData(brca)[,1]
    colors_de <- node_color_per_de(results, pathways,
    sample_group, "Tumor", "Normal")

[Package hipathia version 1.0.0 Index]