enrichWiki {TimiRGeN} | R Documentation

## enrichWiki

### Description

Finds which wikipathways are enriched within the data. This function uses gene set enrichment analysis from clusterProfiler to find enriched signalling pathways. Each time point is analysed individually. In the case of separated TimiRGeN analysis, each gene type and time point are analysed individually.

### Usage

    enrichWiki(MAE, method = '', ID_list, orgDB, path_gene, path_name,
                      ID = '', universe, pvalcutoff, qvaluecutoff,
                      padjustmethod)

### Arguments

`MAE` | MultiAssayExperiment which will store the output from enrichWiki. It is recommended to use the MAE object which stores the output from the dloadGmt function.
`method` | Either 'c' or 's', respectively for combined or separated analysis.
`ID_list` | List of ensembl or entrez IDs for each sample. This is the output from eNames function. This will be found as metadata within the MAE used in the eNames function.
`orgDB` | DB package of the species being analysed. e.g. org.Mm.eg.db if mouse miR-mRNA data is being looked into.
`path_gene` | Dataframe containing pathway ID - gene ID information. This is output from either dloadGmt or gmtEnsembl. It will be stored as an assay within the MAE used in dloadGmt or gmtEnsembl.
`path_name` | Dataframe containing pathway ID - pathway names information. This is output from dloadGmt. It will be stored as an assay within the MAE used in dloadGmt.
`ID` | Either "ENTREZID" or "ENSEMBL". This should be the same as the ID type used for ID_list. dloadGmt loads data as entrez gene IDs and gmtEnsembl converts this to ensembl gene IDs.
`universe` | A column of gene IDs to be used as the background for gene set enrichment. IDs should be stored as characters. It is recommended to use all genes found within the wikipathways of the species being analysed as background i.e. path_gene$gene or universe = assay(MAE, i)[[2]]/ MAE[[i]][2]. To add a unique universe, create a list of gene IDs (entrezID or ensembl) which are classed as characters.
`pvalcutoff` | Default is 0.05. P value cut-off point.
`qvaluecutoff` | Default is 0.2. q value cut-off point.
`padjustmethod` | Default is 'BH'. This sets the pvalue adjustment method. Look into the enricher function from clusterProfiler for more info.

### Value

A large list which identifies which wikipathways are most enriched at each time point of the input data. Output will be stored as metadata in the input MAE.

### Examples

    library(org.Mm.eg.db)

    MAE <- MultiAssayExperiment()

    metadata(MAE)[["e_list"]] <- e_list_mouse

    MAE <- dloadGmt(MAE, species = "Mus musculus")

    MAE <- enrichWiki(MAE = MAE, method = 'c', ID_list = metadata(MAE)[[1]],
                      orgDB = org.Mm.eg.db, path_gene = assay(MAE, 1),
                      path_name = assay(MAE, 2), ID = "ENTREZID",
                      universe = assay(MAE, 1)[[2]])

[Package TimiRGeN version 1.0.6 Index]