title: Analyzing allele specific RNA expression using mixture models.
abstract: BACKGROUND
  Measuring allele-specific RNA expression provides valuable insights into cis-acting genetic and epigenetic regulation of gene expression. Widespread adoption of high-throughput sequencing technologies for studying RNA expression (RNA-Seq) permits measurement of allelic RNA expression imbalance (AEI) at heterozygous single nucleotide polymorphisms (SNPs) across the entire transcriptome, and this approach has become especially popular with the emergence of large databases, such as GTEx. However, the existing binomial-type methods used to model allelic expression from RNA-seq assume a strong negative correlation between reference and variant allele reads, which may not be reasonable biologically.
  
  
  RESULTS
  Here we propose a new strategy for AEI analysis using RNA-seq data. Under the null hypothesis of no AEI, a group of SNPs (possibly across multiple genes) is considered comparable if their respective total sums of the allelic reads are of similar magnitude. Within each group of "comparable" SNPs, we identify SNPs with AEI signal by fitting a mixture of folded Skellam distributions to the absolute values of read differences. By applying this methodology to RNA-Seq data from human autopsy brain tissues, we identified numerous instances of moderate to strong imbalanced allelic RNA expression at heterozygous SNPs. Findings with SLC1A3 mRNA exhibiting known expression differences are discussed as examples.
  
  
  CONCLUSIONS
  The folded Skellam mixture model searches for SNPs with significant difference between reference and variant allele reads (adjusted for different library sizes), using information from a group of "comparable" SNPs across multiple genes. This model is particularly suitable for performing AEI analysis on genes with few heterozygous SNPs available from RNA-seq, and it can fit over-dispersed read counts without specifying the direction of the correlation between reference and variant alleles.
authors.affiliation: Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Rong
authors.initials: R
authors.lastname: Lu
authors.affiliation: Center for Pharmacogenomics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Ryan M
authors.initials: RM
authors.lastname: Smith
authors.affiliation: Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, 43210, USA.|Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43201, USA.
authors.forename: Michal
authors.initials: M
authors.lastname: Seweryn
authors.affiliation: Center for Pharmacogenomics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Danxin
authors.initials: D
authors.lastname: Wang
authors.affiliation: Center for Pharmacogenomics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Katherine
authors.initials: K
authors.lastname: Hartmann
authors.affiliation: Department of Biomedical Informatics, Program in Pharmacogenomics, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
authors.forename: Amy
authors.initials: A
authors.lastname: Webb
authors.affiliation: Center for Pharmacogenomics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Sadee
authors.affiliation: Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, 43210, USA. rempala.3@osu.edu.|Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, 43201, USA. rempala.3@osu.edu.
authors.forename: Grzegorz A
authors.initials: GA
authors.lastname: Rempala
mesh_terms: D000483:Alleles; D022981:Allelic Imbalance / Q000235:genetics*; D044127:Epigenesis, Genetic; D005786:Gene Expression Regulation; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D020641:Polymorphism, Single Nucleotide; D012313:RNA / Q000235:genetics*; D017423:Sequence Analysis, RNA; D059467:Transcriptome / Q000235:genetics
chemical_list: D012313:RNA