topKnet: Return consensus ranks from a matrix containing ranks

In MetNet: Inferring metabolic networks from untargeted high-resolution mass spectrometry data

Description

'topKnet' returns consensus ranks depending on the 'type' argument from 'ranks', a matrix containing the ranks per statistical 'model'.

Usage

topKnet(ranks, type)

Arguments

ranks	'matrix' containing the ranks per statistical model (in columns) and per feature pair (in rows)
type	'character', either '"top1"', '"top2"' or '"mean"'

Details

See Hase et al. (2014) for further details.

Value

'numeric' 'vector“ with consensus ranks

Author(s)

Thomas Naake, [e-mail]

References

Hase et al. (2014): Harnessing Diversity towards the Reconstructing of Large Scale Gene Regulatory Networks. PLoS Computational Biology, 2013, e1003361, doi: [10.1371/journal.pcbi.1003361](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003361)

Examples

ranks <- matrix(c(c(1, 2, 3), c(2, 1, 3)), ncol = 2)

## type = "top1"
MetNet:::topKnet(ranks = ranks, type = "top1")

## type = "top2"
MetNet:::topKnet(ranks = ranks, type = "top2")

## type = "mean"
MetNet:::topKnet(ranks = ranks, type = "mean")

MetNet documentation built on Nov. 8, 2020, 7:34 p.m.