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metagenomeSeq (version 1.10.0)

MRcoefs: Table of top-ranked microbial marker gene from linear model fit

Description

Extract a table of the top-ranked features from a linear model fit. This function will be updated soon to provide better flexibility similar to limma's topTable.

Usage

MRcoefs(obj, by = 2, coef = NULL, number = 10, taxa = obj$taxa, uniqueNames = FALSE, adjust.method = "fdr", group = 0, eff = 0, numberEff = FALSE, counts = 0, file = NULL)

Arguments

obj
A list containing the linear model fit produced by lmFit through fitZig.
by
Column number or column name specifying which coefficient or contrast of the linear model is of interest.
coef
Column number(s) or column name(s) specifying which coefficient or contrast of the linear model to display.
number
The number of bacterial features to pick out.
taxa
Taxa list.
uniqueNames
Number the various taxa.
adjust.method
Method to adjust p-values by. Default is "FDR". Options include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". See p.adjust for more details.
group
One of five choices, 0,1,2,3,4. 0: the sort is ordered by a decreasing absolute value coefficient fit. 1: the sort is ordered by the raw coefficient fit in decreasing order. 2: the sort is ordered by the raw coefficient fit in increasing order. 3: the sort is ordered by the p-value of the coefficient fit in increasing order. 4: no sorting.
eff
Filter features to have at least a "eff" quantile or number of effective samples.
numberEff
Boolean, whether eff should represent quantile (default/FALSE) or number.
counts
Filter features to have at least 'counts' counts.
file
Name of output file, including location, to save the table.

Value

Table of the top-ranked features determined by the linear fit's coefficient.

See Also

fitZig MRtable

Examples

Run this code
data(lungData)
k = grep("Extraction.Control",pData(lungData)$SampleType)
lungTrim = lungData[,-k]
k = which(rowSums(MRcounts(lungTrim)>0)<10)
lungTrim = lungTrim[-k,]
cumNorm(lungTrim)
smokingStatus = pData(lungTrim)$SmokingStatus
mod = model.matrix(~smokingStatus)
settings = zigControl(maxit=1,verbose=FALSE)
fit = fitZig(obj = lungTrim,mod=mod,control=settings)
head(MRcoefs(fit))

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