katiasmirn/PERFect: Permutation filtration for microbiome data

PERFect is a novel permutation filtering approach designed to address two unsolved problems in microbiome data processing: (i) define and quantify loss due to filtering by implementing thresholds, and (ii) introduce and evaluate a permutation test for filtering loss to provide a measure of excessive filtering. Methods are assessed on two `mock' experiment data sets, where the true taxa compositions are known, and are applied to a publicly available vaginal microbiome data set. The method correctly removes contaminant taxa in `mock' data sets, quantifies and visualizes the corresponding filtering loss, and provides a uniform data-driven filtering criteria for real microbiome data sets.

Getting started

Package details

AuthorEkaterina Smirnova [aut, cre] Quy Cao [cre]
MaintainerQuy Cao <[email protected]>
LicenseGPL (>= 3)
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
katiasmirn/PERFect documentation built on Aug. 26, 2018, 4:52 a.m.