enrichment.list.factor.minimal {netresponse} | R Documentation

## enrichment.list.factor

### Description

Orders the responses by association strength (enrichment score) to a given sample set. For instance, if the samples correspond to a particular experimental factor, this function can be used to prioritize the responses according to their association strength to this factor.

### Usage

    enrichment.list.factor.minimal(
      groupings,
      method,
      verbose = FALSE,
      annotation.vector,
      level
    )

### Arguments

`groupings` | List of groupings. Each model should have a sample-cluster assignment matrix qofz.
`method` | 'hypergeometric' measures enrichment of factor levels in this response; 'precision' measures response purity for each factor level; 'dependency' measures logarithm of the joint density between response and factor level vs. their marginal densities: log(P(r,s)/(P(r)P(s)))
`verbose` | Follow progress by intermediate messages.
`annotation.vector` | annotation vector
`level` | level

### Value

A data frame which gives a data frame of responses ordered by enrichment score for the investigated sample. The model, response id and enrichment score are shown. The method field indicates the enrichment calculation method. The sample field lists the samples et for which the enrichments were calculated. The info field lists additional information on enrichment statistics.

### Author(s)

Leo Lahti leo.lahti@iki.fi

### References

See citation('netresponse') for citation details.

### Examples

    res <- enrichment.list.factor.minimal(groupings = NULL,
        method = NULL,
        annotation.vector = NULL,
        level = NULL)

[Package netresponse version 1.50.0 Index]