Abstract
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.
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