NPEBseq: nonparametric empirical bayesian-based procedure for differential expression analysis of RNA-seq data

@inproceedings{Bi2013NPEBseqNE,
  title={NPEBseq: nonparametric empirical bayesian-based procedure for differential expression analysis of RNA-seq data},
  author={Yingtao Bi and Ramana V. Davuluri},
  booktitle={BMC Bioinformatics},
  year={2013}
}
RNA-seq, a massive parallel-sequencing-based transcriptome profiling method, provides digital data in the form of aligned sequence read counts. The comparative analyses of the data require appropriate statistical methods to estimate the differential expression of transcript variants across different cell/tissue types and disease conditions. We developed a novel nonparametric empirical Bayesian-based approach (NPEBseq) to model the RNA-seq data. The prior distribution of the Bayesian model is… CONTINUE READING
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