heatmapdmn: Heatmap representation of samples assigned to Dirichlet...

In DirichletMultinomial: Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

Description

Produce a heat map summarizing count data, grouped by Dirichlet component.

Usage

heatmapdmn(count, fit1, fitN, ntaxa = 30, ...,
    transform = sqrt, lblwidth = 0.2 * nrow(count), col = .gradient)

Arguments

count	A matrix of sample x taxon counts, as supplied to dmn.
fit1	An instance of class dmn, from a model fit to a single Dirichlet component, k=1 in dmn.
fitN	An instance of class dmn, from a model fit to N != 1 components, k=N in dmn.
ntaxa	The ntaxa most numerous taxa to display counts for.
...	Additional arguments, ignored.
transform	Transformation to apply to count data prior to visualization; this does not influence mixture membership or taxnomic ordering.
lblwidth	The proportion of the plot to dedicate to taxanomic labels, as a fraction of the number of samples to be plotted.
col	The colors used to display (possibly transformed, by transform) count data, as used by image.

Details

Columns of the heat map correspond to samples. Samples are grouped by Dirichlet component, with average (Dirichlet) components summarized as a separate wide column. Rows correspond to taxonomic groups, ordered based on contribution to Dirichlet components.

Author(s)

Martin Morgan mailto:[e-mail]

Examples

## counts
fl <- system.file(package="DirichletMultinomial", "extdata",
                  "Twins.csv")
count <- t(as.matrix(read.csv(fl, row.names=1)))

## all and best-fit clustering
data(fit)
lplc <- sapply(fit, laplace)
best <- fit[[which.min(lplc)]]

heatmapdmn(count, fit[[1]], best, 30)

Example output

Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which.max, which.min


Attaching package: ‘S4Vectors’

The following object is masked from ‘package:base’:

    expand.grid

Loading required package: IRanges

DirichletMultinomial documentation built on Nov. 8, 2020, 7 p.m.