nichenet_networks {OmnipathR} | R Documentation

## Builds NicheNet network prior knowledge

### Description

Builds network knowledge required by NicheNet. For this it calls a multitude of methods to download and combine data from various databases according to the settings. The content of the prior knowledge data is highly customizable, see the documentation of the related functions.

### Usage

    nichenet_networks(
      signaling_network = list(),
      lr_network = list(),
      gr_network = list(),
      only_omnipath = FALSE,
      small = FALSE,
      tiny = FALSE,
      quality_filter_param = list()
    )

### Arguments

`signaling_network` | A list of parameters for building the signaling network, passed to `nichenet_signaling_network`
`lr_network` | A list of parameters for building the ligand-receptor network, passed to `nichenet_lr_network`
`gr_network` | A list of parameters for building the gene regulatory network, passed to `nichenet_gr_network`
`only_omnipath` | Logical: a shortcut to use only OmniPath as network resource.
`small` | Logical: build a small network for testing purposes, using only OmniPath data. It is also a high quality network, it is reasonable to try the analysis with this small network.
`tiny` | Logical: build an even smaller network for testing purposes. As this involves random subsetting, it's not recommended to use this network for analysis.
`quality_filter_param` | Arguments for `filter_intercell_network` (quality filtering of the OmniPath ligand-receptor network). It is recommended to check these parameters and apply some quality filtering. The defaults already ensure certain filtering, but you might want more relaxed or stringent options.

### Value

A named list with three network data frames (tibbles): the signaling, the ligand-receptor (lr) and the gene regulatory (gr) networks.

### See Also

- `nichenet_signaling_network`

- `nichenet_lr_network`

- `nichenet_gr_network`

### Examples

    networks <- nichenet_networks()
    dplyr::sample_n(networks$gr_network, 10)
    # # A tibble: 10 x 4
    #    from    to       source               database
    #    <chr>   <chr>    <chr>                <chr>
    #  1 MAX     ALG3     harmonizome_ENCODE   harmonizome
    #  2 MAX     IMPDH1   harmonizome_ENCODE   harmonizome
    #  3 SMAD5   LCP1     Remap_5              Remap
    #  4 HNF4A   TNFRSF19 harmonizome_CHEA     harmonizome
    #  5 SMC3    FAP      harmonizome_ENCODE   harmonizome
    #  6 E2F6    HIST1H1B harmonizome_ENCODE   harmonizome
    #  7 TFAP2C  MAT2B    harmonizome_ENCODE   harmonizome
    #  8 USF1    TBX4     harmonizome_TRANSFAC harmonizome
    #  9 MIR133B FETUB    harmonizome_TRANSFAC harmonizome
    # 10 SP4     HNRNPH2  harmonizome_ENCODE   harmonizome

    # use only OmniPath:
    omnipath_networks <- nichenet_networks(only_omnipath = TRUE)

[Package OmnipathR version 3.2.0 Index]