Tools and best practices for data processing in allelic expression analysis

@inproceedings{Castel2015ToolsAB,
  title={Tools and best practices for data processing in allelic expression analysis},
  author={Stephane E Castel and Ami Levy-Moonshine and Pejman Mohammadi and Eric D. Banks and Tuuli Lappalainen},
  booktitle={Genome Biology},
  year={2015}
}
Allelic expression analysis has become important for integrating genome and transcriptome data to characterize various biological phenomena such as cis-regulatory variation and nonsense-mediated decay. We analyze the properties of allelic expression read count data and technical sources of error, such as low-quality or double-counted RNA-seq reads, genotyping errors, allelic mapping bias, and technical covariates due to sample preparation and sequencing, and variation in total read depth. We… CONTINUE READING
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