consensus_SFT_fit: Pick power to fit networks to scale-free topology

In almeidasilvaf/BioNERO: Biological Network Reconstruction Omnibus

Pick power to fit networks to scale-free topology

Description

Pick power to fit networks to scale-free topology

Usage

consensus_SFT_fit(
  exp_list,
  setLabels = NULL,
  metadata = NULL,
  cor_method = "spearman",
  net_type = "signed hybrid",
  rsquared = 0.8
)

Arguments

exp_list	A list of expression data frames or SummarizedExperiment objects. If input is a list of data frames, row names must correspond to gene IDs and column names to samples. The list can be created with list(exp1, exp2, ..., expn).
setLabels	Character vector containing labels for each expression set.
metadata	A data frame containing sample names in row names and sample annotation in the first column. Ignored if 'exp_list' is a list of 'SummarizedExperiment' objects, since the function will extract colData.
cor_method	Correlation method used for network reconstruction. One of "spearman" (default), "biweight", or "pearson".
net_type	Network type. One of "signed hybrid" (default), "signed" or "unsigned".
rsquared	Minimum R squared to consider the network similar to a scale-free topology. Default is 0.8.

Value

A list of 2 elements:

power

Numeric vector of optimal beta powers to fit networks to SFT

plot

A ggplot object displaying main statistics of the SFT fit test

Examples

set.seed(12)
data(zma.se)
filt.zma <- filter_by_variance(zma.se, n=500)
zma.set1 <- filt.zma[, sample(colnames(filt.zma), size=20, replace=FALSE)]
zma.set2 <- filt.zma[, sample(colnames(filt.zma), size=20, replace=FALSE)]
list.sets <- list(zma.set1, zma.set2)
cons_sft <- consensus_SFT_fit(list.sets, setLabels = c("Maize1", "Maize2"),
                              cor_method = "pearson")

almeidasilvaf/BioNERO documentation built on Oct. 9, 2024, 1:49 a.m.