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EMASE: Expectation-Maximization algorithm for Allele Specific Expression

Note: This is the original repository of EMASE python prototype. For performance, we implemented the same models in C++ (available at http://churchill-lab.github.io/emase-zero/).


  • [Hierarchical Analysis of RNA-Seq Reads Improves the Accuracy of Allele-specific Expression] Narayanan Raghupathy, Kwangbom Choi, Matthew J. Vincent, Glen L. Beane, Keith Sheppard, Steven C. Munger, Ron Korstanje, Fernando Pardo-Manual de Villena, and Gary A. Churchill. Bioinformatics, bty078, 2018. https://doi.org/10.1093/bioinformatics/bty078
  • [RNA-Seq Alignment to Individualized Genomes Improves Transcript Abundance Estimates in Multiparent Populations](http://www.genetics.org/content/198/1/59.short) Steven C. Munger, Narayanan Raghupathy, Kwangbom Choi, Allen K. Simons, Daniel M. Gatti, Douglas A. Hinerfeld, Karen L. Svenson, Mark P. Keller, Alan D. Attie, Matthew A. Hibbs, Joel H. Graber, Elissa J. Chesler and Gary A. Churchill. Genetics. 2014 Sep;198(1):59-73. doi: 10.1534/genetics.114.165886.
  • [PRDM9 Drives Evolutionary Erosion of Hotspots in Mus musculus through Haplotype-Specific Initiation of Meiotic Recombination](http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1004916) Christopher L. Baker, Shimpei Kajita, Michael Walker, Ruth L. Saxl, Narayanan Raghupathy, Kwangbom Choi, Petko M. Petkov, Kenneth Paigen PLOS Genetics: published 08 Jan 2015 | info:doi/10.1371/journal.pgen.1004916