hRUV is a package for normalisation of multiple batches of metabolomics data in a hierarchical strategy with use of samples replicates in a large-scale studies. The tool utilises 2 types of replicates: intra-batch and inter-batch replicates to estimate the unwatned variation within and between batches with RUV-III. We have designed the replicate embedding arrangements within and between batches from http://shiny.maths.usyd.edu.au/hRUV. Our novel tool is a novel hierarchical approach to removing unwanted variation by harnessing information from sample replicates embedded in the seequence of experimental runs/batches and applying signal drift correction with robust linear or non-linear smoothers.

hRUV overview

Software requirements

This package has been tested for macOS Big Sur (11.1) and Linux Debian 10 (buster) with R version 4.0.3.

R package dependecies

CRAN

dplyr
tidyr
rlang
ggplot2
plotly
S4Vectors
tibble
DMwR2
MASS

Bioconductor

SummarizedExperiment
impute

Installation

Install the R package from GitHub using the devtools package:

if (!("devtools" %in% rownames(installed.packages())))
    install.packages("devtools")

# Tested on devtools version 2.3.2.
library(devtools)
devtools::install_github("SydneyBioX/hRUV", build_vignettes=TRUE, dependencies = TRUE)

Vignette

The vignette is available at https://sydneybiox.github.io/hRUV/. Alternatively, it can be accessed with browseVignettes("hRUV") in your R console.

Contact us

If you have any enquiries, especially about performing hRUV to integrate your metabolomics data, please contact . We are also happy to receive any suggestions and comments.