netresponse (version 1.32.2)

order.responses: order.responses

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

order.responses(models, sample, method = "hypergeometric", min.size = 2,
  max.size = Inf, min.responses = 2, subnet.ids = NULL, verbose = FALSE,
  data = NULL)

Arguments

models

List of models. Each model should have a sample-cluster assignment matrix qofz.

sample

Measure enrichment of this sample (set) across the observed responses.

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)))

min.size, max.size, min.responses

Optional parameters to filter the results based on subnet size and number of responses.

subnet.ids

Specify subnets for which the responses shall be ordered. By default, use all subnets.

verbose

Follow progress by intermediate messages.

data

data (samples x features; or a vector in univariate case)

Value

• A data frame with elements 'ordered.responses' which gives a data frame of responses ordered by enrichment score for the investigated sample. The subnetwork, 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.

References

See citation("netresponse") for citation details.

Examples

#
# - for given sample/s (factor level), 
#     order responses (across all subnets) by association strength 
#     (enrichment score); overrepresentation
# order.responses(model, sample, method  = "hypergeometric")