Dataset Information
MultiBaC: an R package to remove batch effects in multi-omic experiments.
Ontology highlight
ABSTRACT: Motivation
Batch effects in omics datasets are usually a source of technical noise that masks the biological signal and hampers data analysis. Batch effect removal has been widely addressed for individual omics technologies. However, multi-omic datasets may combine data obtained in different batches where omics type and batch are often confounded. Moreover, systematic biases may be introduced without notice during data acquisition, which creates a hidden batch effect. Current methods fail to address batch effect correction in these cases.Results
In this article, we introduce the MultiBaC R package, a tool for batch effect removal in multi-omics and hidden batch effect scenarios. The package includes a diversity of graphical outputs for model validation and assessment of the batch effect correction.Availability and implementation
MultiBaC package is available on Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/MultiBaC.html) and GitHub (https://github.com/ConesaLab/MultiBaC.git). The data underlying this article are available in Gene Expression Omnibus repository (accession numbers GSE11521, GSE1002, GSE56622 and GSE43747).Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Ugidos M
PROVIDER: S-EPMC9048667 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
MultiBaC: an R package to remove batch effects in multi-omic experiments.
Bioinformatics (Oxford, England) 20220401 9
<h4>Motivation</h4>Batch effects in omics datasets are usually a source of technical noise that masks the biological signal and hampers data analysis. Batch effect removal has been widely addressed for individual omics technologies. However, multi-omic datasets may combine data obtained in different batches where omics type and batch are often confounded. Moreover, systematic biases may be introduced without notice during data acquisition, which creates a hidden batch effect. Current methods fai ...[more]