make_network: Make microbiome network (igraph)

In joey711/phyloseq: Handling and analysis of high-throughput microbiome census data

Make microbiome network (igraph)

Description

A specialized function for creating a network representation of microbiomes, sample-wise or taxa-wise, based on a user-defined ecological distance and (potentially arbitrary) threshold. The graph is ultimately represented using the igraph-package.

Usage

make_network(physeq, type="samples", distance="jaccard", max.dist = 0.4, 
    keep.isolates=FALSE, ...)

Arguments

physeq	(Required). Default NULL. A phyloseq-class object, or otu_table-class object, on which g is based. phyloseq-class recommended.
type	(Optional). Default "samples". Whether the network should be samples or taxa/OTUs. Supported arguments are "samples", "taxa", where "taxa" indicates using the OTUs/taxaindices, whether they actually represent species or some other taxonomic rank. NOTE: not all distance methods are supported if "taxa" selected for type. For example, the UniFrac distance and DPCoA cannot be calculated for taxa-wise distances, because they use a taxa-wise tree as part of their calculation between samples, and there is no transpose-equivalent for this tree.
distance	(Optional). Default "jaccard". Any supported argument to the method parameter of the distance function is supported here. Some distance methods, like "unifrac", may take a non-trivial amount of time to calculate, in which case you probably want to calculate the distance matrix separately, save, and then provide it as the argument to distance instead. See below for alternatives). Alternatively, if you have already calculated the sample-wise distance object, the resulting dist-class object can be provided as distance instead (see examples). A third alternative is to provide a function that takes a sample-by-taxa matrix (typical vegan orientation) and returns a sample-wise distance matrix.
max.dist	(Optional). Default 0.4. The maximum ecological distance (as defined by distance) allowed between two samples to still consider them “connected” by an edge in the graphical model.
keep.isolates	(Optional). Default FALSE. Logical. Whether to keep isolates (un-connected samples, not microbial isolates) in the graphical model that is returned. Default results in isolates being removed from the object.
...	(Optional). Additional parameters passed on to distance.

Value

A igraph-class object.

See Also

plot_network

Examples

# # Example plots with Enterotype Dataset
data(enterotype)
ig <- make_network(enterotype, max.dist=0.3)
plot_network(ig, enterotype, color="SeqTech", shape="Enterotype", line_weight=0.3, label=NULL)
# 
ig1 <- make_network(enterotype, max.dist=0.2)
plot_network(ig1, enterotype, color="SeqTech", shape="Enterotype", line_weight=0.3, label=NULL)
# 
# # Three methods of choosing/providing distance/distance-method
# Provide method name available to distance() function
ig <- make_network(enterotype, max.dist=0.3, distance="jaccard")
# Provide distance object, already computed
jaccdist <- distance(enterotype, "jaccard")
ih <- make_network(enterotype, max.dist=0.3, distance=jaccdist)
# Provide "custom" function.
ii <- make_network(enterotype, max.dist=0.3, distance=function(x){vegan::vegdist(x, "jaccard")})
# The have equal results:		
all.equal(ig, ih)
all.equal(ig, ii)
# 
# Try out making a trivial "network" of the 3-sample esophagus data,
# with weighted-UniFrac as distance
data(esophagus)
ij <- make_network(esophagus, "samples", "unifrac", weighted=TRUE)

joey711/phyloseq documentation built on Nov. 4, 2022, 1:16 a.m.