Clusters: Clustering of bacterial taxa

In katrikorpela/mare: Microbiota Analysis in R Easily

Clustering of bacterial taxa

Description

Hierarchical clustering based on significant correlations between bacterial taxa.

Usage

Clusters(taxonomic.table, meta, N.taxa = NULL,  readcount.cutoff = 0,
                     minimum.correlation = 0.5, minimum.network = 1,
                      select.by = NULL, select = NULL, keep.result = F, pdf = F, relative = T)

Arguments

taxonomic.table	Name of the taxonomic table. Should be the name of a text file.
meta	Name of the metadata file containing the grouping variable. Should be the name of a text file.
N.taxa	The number of most abundant taxa to include, if you don't want to include all taxa.
readcount.cutoff	Lowest acceptable read count per sample. Samples with fewer reads are ignored.
minimum.correlation	Minimum acceptable correlation between bacterial taxa. Lower values are considered 0.
minimum.network	Minimum network size, i.e. number of correlating taxa. Taxa with smaller networks are ignored.
select.by	Name of a variable in the metadata file by which a subset will be selected for plotting.
select	Determines which value on the selection variable will be selected.
keep.result	Should the results be returned as an R object? TRUE or FALSE.
pdf	Should the figure be saved as pdf? TRUE or FALSE.
relative	Use relative abundances? Default is TRUE. FALSE will use data as is.

Value

Returns a list with two components: 1. Data frame with relative abundances of the bacterial clusters 2. Cluster assignments of the bacterial taxa

Author(s)

Katri Korpela

Examples

## Not run: 
#Select the 50 most abundant bacterial genera and calculate correlations between them.
#Set all correlation <0.5 to 0. 
#Include genera with >1 significantly correlating partners.

Clusters(taxonomic.table = "organised_genus_table.txt", 
          meta="meta.txt", N.taxa = 50, readcount.cutoff = 0,
          minimum.correlation = 0.5,  minimum.network = 1)

	

## End(Not run)

katrikorpela/mare documentation built on July 17, 2022, 2:49 a.m.