Comparison of statistical methods and the use of quality control samples for batch effect correction in human transcriptome data

PLoS One. 2018 Aug 30;13(8):e0202947. doi: 10.1371/journal.pone.0202947. eCollection 2018.

Abstract

Batch effects are technical sources of variation introduced by the necessity of conducting gene expression analyses on different dates due to the large number of biological samples in population-based studies. The aim of this study is to evaluate the performances of linear mixed models (LMM) and Combat in batch effect removal. We also assessed the utility of adding quality control samples in the study design as technical replicates. In order to do so, we simulated gene expression data by adding "treatment" and batch effects to a real gene expression dataset. The performances of LMM and Combat, with and without quality control samples, are assessed in terms of sensitivity and specificity while correcting for the batch effect using a wide range of effect sizes, statistical noise, sample sizes and level of balanced/unbalanced designs. The simulations showed small differences among LMM and Combat. LMM identifies stronger relationships between big effect sizes and gene expression than Combat, while Combat identifies in general more true and false positives than LMM. However, these small differences can still be relevant depending on the research goal. When any of these methods are applied, quality control samples did not reduce the batch effect, showing no added value for including them in the study design.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Data Interpretation, Statistical*
  • Female
  • Gene Expression Profiling / methods*
  • Humans
  • Male
  • Middle Aged
  • Models, Biological
  • Quality Control*
  • Transcriptome

Grant support

This work was supported by EXPOsOMICS, a project supported by the grant FP7 of the European Commission ‘Enhanced exposure assessment and omic profiling for high priority environmental exposures in Europe’ (no. 308610), http://www.exposomicsproject.eu/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.