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permubiome (version 1.3.2)

A Permutation Based Test for Biomarker Discovery in Microbiome Data

Description

The permubiome R package was created to perform a permutation-based non-parametric analysis on microbiome data for biomarker discovery aims. This test executes thousands of comparisons in a pairwise manner, after a random shuffling of data into the different groups of study with a prior selection of the microbiome features with the largest variation among groups. Previous to the permutation test itself, data can be normalized according to different methods proposed to handle microbiome data ('proportions' or 'Anders'). The median-based differences between groups resulting from the multiple simulations are fitted to a normal distribution with the aim to calculate their significance. A multiple testing correction based on Benjamini-Hochberg method (fdr) is finally applied to extract the differentially presented features between groups of your dataset. LATEST UPDATES: v1.1 and olders incorporates function to parse COLUMN format; v1.2 and olders incorporates -optimize- function to maximize evaluation of features with largest inter-class variation; v1.3 and olders includes the -size.effect- function to perform estimation statistics using the bootstrap-coupled approach implemented in the 'dabestr' (>=0.3.0) R package. Current v1.3.2 fixed bug with "Class" recognition and updated 'dabestr' functions.

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Version

Install

install.packages('permubiome')

Monthly Downloads

187

Version

1.3.2

License

GPL-3

Maintainer

Alfonso Benitez-Paez

Last Published

October 16th, 2023

Functions in permubiome (1.3.2)

optimize

Optimization for detection of features with larger variation between classes
plots

Plotting the features with differential abundance.
normalize

Normalize the microbiome dataset prior to perform the permutation test.
size.effect

Executing estimation statistics based on bootstrap-coupled approach
permutation

Permutation-based non-parametric analysis to infer differential abundance of features between groups.
get.data

Parsing the data file.