Sentence examples for batch effects can increase from inspiring English sources

Surrogate variable analysis (SVA), which is a method for modeling the potential confounding factors that may or may not be known, including technical factors such as batch effects, can increase the biological accuracy and reproducibility of analyses in microarray studies [ 23, 24].

Our results show that batch effects can be attenuated statistically when proper experimental design is used.

Although batch effects can be reduced by careful experimental design, they cannot be eliminated unless the whole study is done in a single batch.

Batch effects can be a problem with RNAseq data [ 26].

However for the design in Table 4, the batch effects are nested within sex and time effects and the result of disregarding batch effects can easily be evaluated.

Combining data from different batches without removing batch effects can give rise to misleading results, since the bias introduced by the non-biological nature of the batch effects can be strong enough to mask and/or confound true biological differences.

Although some of these batch effects can be minimized or even prevented with appropriate precautions and experimental design, certain batch effects are unavoidable.

Nevertheless, batch effects can generate artifacts that only affect a subset of probes.

As other L/S adjustments, ComBat assumes that the batch effects can be modeled by standardizing means and variances across batches.

Since batch effects can affect different probes in different ways, they often can not be corrected through routine normalization methods and special techniques are needed [ 2, 11].

For example, in observational studies the effects of potentially confounding factors such as batch effects can be alleviated via careful use of randomisation.