enrich_mods {CEMiTool} | R Documentation

## Enriches communities

### Description

Returns enrichment of communities from edgelist created by cemoverlap function.

### Usage

    enrich_mods(community_list, analyses, comp_group = "none",
      subject_col = NULL, run_fgsea = FALSE)

### Arguments

`community_list` | Community list obtained from overlap community function
`analyses` | List of CEMiTool objects
`comp_group` | Which group will be used as base for comparison. If 'none', then all combinations of comparisons will be made
`subject_col` | Column containing subject information in sample annotation slot of CEMiTool objects
`run_fgsea` | Logical. Should fgsea be run?

### Details

This function assumes that relevant modules for a comparison in a study will have a high proportion of differentially regulated genes in a certain direction. Base assumption is that NON-relevant modules will be centered at zero.

### Value

A `data.frame` containing information of how much each comparison is enriched in each community in each CEMiTool object.

### Examples

    ## Not run:
    # Run the cemitool function twice on expr dataset. Each time, one sample will be removed
    data(expr0)
    data(sample_annot)
    set.seed(10)
    dset1 <- expr0[,-sample(1:ncol(expr0), 1)]
    dset2 <- expr0[,-sample(1:ncol(expr0), 1)]
    cem1 <- cemitool(dset1, plot=FALSE)
    cem2 <- cemitool(dset2, plot=FALSE)
    cem_overlap_df <- cem_overlap(list(cem1, cem2))

    comm_overlap <- overlap_community(cem_overlap_df)

    samples1 <- names(expr_data(cem1, filter=TRUE, apply_vst=TRUE))
    samples2 <- names(expr_data(cem2, filter=TRUE, apply_vst=TRUE))

    sample_annotation(cem1) <- sample_annot[sample_annot$SampleName %in% samples1, ]
    sample_annotation(cem2) <- sample_annot[sample_annot$SampleName %in% samples2, ]

    mod_enrich <- enrich_mods(comm_overlap, list(cem1, cem2), comp_group='g0')

    ## End(Not run)

[Package CEMiTool version 1.6.11 Index]