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

heatmapdmn {DirichletMultinomial}

R Documentation

Heatmap representation of samples assigned to Dirichlet components.

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:mtmorgan@fhcrc.org

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)

[Package DirichletMultinomial version 1.24.1 Index]