Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses

@article{Stegle2012UsingPE,
  title={Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses},
  author={Oliver Stegle and Leopold Parts and Matias Piipari and John L Winn and Richard Durbin},
  journal={Nature Protocols},
  year={2012},
  volume={7},
  pages={500-507}
}
We present PEER (probabilistic estimation of expression residuals), a software package implementing statistical models that improve the sensitivity and interpretability of genetic associations in population-scale expression data. This approach builds on factor analysis methods that infer broad variance components in the measurements. PEER takes as input transcript profiles and covariates from a set of individuals, and then outputs hidden factors that explain much of the expression variability… CONTINUE READING
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