widespread and critical impact of batch effects in high-throughput data

High-throughput technologies are widely used, for example to
assay genetic variants, gene and protein expression, and
epigenetic modifications. One often overlooked complication
with such studies is batch effects, which occur because
measurements are affected by laboratory conditions, reagent
lots and personnel differences. This becomes a major problem
when batch effects are correlated with an outcome of interest
and lead to incorrect conclusions. Using both published studies
and our own analyses, we argue that batch effects (as well as
other technical and biological artefacts) are widespread and
critical to address. We review experimental and computational
approaches for doing so.



Nature Reviews Genetics 11, 733-739 (October 2010) |
doi:10.1038/nrg2825