z-transform-sample: transform from raw counts to Poisson-lognormal-based metrics

In almlab/texmexseq: Treatment Effect eXplorer for Microbial Ecology eXperiments (using Sequence Counts)

Description

Functions for transforming raw read counts into rescaled reads (z) and theoretical cumulative distribution function values (f).

Usage

    z.transform.sample(n)
    z.transform.table(otu)
    f.transform.sample(n)
    f.transform.table(otu)

Arguments

n	vector of observed counts
otu	data frame OTU table

Details

z.transform.sample fits the Poisson lognormal distribution to the count data and uses that fit to transform those raw read counts into rescaled reads. z.transform.table performs the same function on an OTU table (which should have one sample per column and should have the OTU IDs as rownames). This second function is just for convenience: it applies z.transform.sample to each column, packages the result into a data frame, and keeps the old rownames.

f.transform.sample and f.transform.table are analogous to the z functions, only they return theoretical cumulative distribution function values.

The resulting tables could be used on their own for analysis, but texmexseq is designed to slice that data into smaller “quads” (using quad.table).

Value

z.transform.sample	returns a vector of transformed values
z.transform.table	returns a data frame of transformed values

Author(s)

Scott Olesen [e-mail]

See Also

texmex.fit quad.table

Examples

# make up a table of data
sim.data <- function() rpoilog(100, 1.0, 1.0, condS=TRUE)
sample1 <- sim.data()

# transform it
hist(f.transform.sample(sample1))

# make up a table of data
sample2 <- sim.data()
otu.table <- data.frame(sample1=sample1, sample2=sample2)
otu.ids <- paste('otu', seq(1, 100), sep='')
rownames(otu.table) <- otu.ids

# make a new table from those fitted values
f.table <- f.transform.table(otu.table)
hist(f.table$sample1)

almlab/texmexseq documentation built on May 10, 2019, 10:25 a.m.