fitPA: Wrapper to run fisher's test on presence/absence of a...

In metagenomeSeq: Statistical analysis for sparse high-throughput sequencing

Description

This function returns a data frame of p-values, odds ratios, lower and upper confidence limits for every row of a matrix.

Usage

fitPA(obj, cl, thres = 0, adjust.method = "fdr", cores = 1, ...)

Arguments

obj	A MRexperiment object with a count matrix, or a simple count matrix.
cl	Group comparison
thres	Threshold for defining presence/absence.
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.
cores	Number of cores to use.
...	Extra parameters for makeCluster

Value

Matrix of odds ratios, p-values, lower and upper confidence intervals

See Also

cumNorm fitZig fitDO fitMeta

Examples

data(lungData)
k = grep("Extraction.Control",pData(lungData)$SampleType)
lungTrim = lungData[,-k]
lungTrim = lungTrim[-which(rowSums(MRcounts(lungTrim)>0)<20),]
res = fitPA(lungTrim,pData(lungTrim)$SmokingStatus);
head(res)

metagenomeSeq documentation built on Nov. 8, 2020, 5:34 p.m.