EMASE (Expectation-Maximization for Allele-Specific Expression) is a tool for estimating total gene expression, isoform usage, and allele-specific expression in RNA-seq data. The EMASE algorithm approaches the problem hierarchically by first resolving uncertainties between genes secondly between isoforms, and finally between alleles. EMASE is a prototype implementation in Python language, and EMASE-Zero is a C++ version.
Genetic variation; RNA-seq
Raghupathy N, Choi K, Vincent MJ, Beane GL, Sheppard KS, Munger SC, Korstanje R, Pardo-Manual de Villena F, Churchill GA "Hierarchical analysis of RNA-seq reads improves the accuracy of allele-specific expression." Bioinformatics. 2018 Jul 1;34(13):2177-2184. https://doi.org/10.1093/bioinformatics/bty078
PMID: 29444201
PMCID: PMC6022640
Baker CL, Kajita S, Walker M, Saxl RL, Raghupathy N, Choi K, Petkov PM, Paigen K "PRDM9 drives evolutionary erosion of hotspots in Mus musculus through haplotype-specific initiation of meiotic recombination." PLoS Genet. 2015 Jan 8;11(1):e1004916. https://doi.org/10.1371/journal.pgen.1004916
PMID: 25568937
PMCID: PMC4287450
Munger SC, Raghupathy N, Choi K, Simons AK, Gatti DM, Hinerfeld DA, Svenson KL, Keller MP, Attie AD, Hibbs MA, Graber JH, Chesler EJ, Churchill GA "RNA-Seq alignment to individualized genomes improves transcript abundance estimates in multiparent populations." Genetics. 2014 Sep;198(1):59-73. https://doi.org/10.1534/genetics.114.165886
PMID: 25236449
PMCID: PMC4174954
If you find errors, please report here.
SECTIONS
TutorialsFind thousands of Bioinformatics and Life Science software tools and databases in the newly launched
Ads