title: Two-pass alignment improves novel splice junction quantification.
abstract: BACKGROUND
  Discovery of novel splicing from RNA sequence data remains a critical and exciting focus of transcriptomics, but reduced alignment power impedes expression quantification of novel splice junctions.
  
  
  RESULTS
  Here, we profile performance characteristics of two-pass alignment, which separates splice junction discovery from quantification. Per sample, across a variety of transcriptome sequencing datasets, two-pass alignment improved quantification of at least 94% of simulated novel splice junctions, and provided as much as 1.7-fold deeper median read depth over those splice junctions. We further demonstrate that two-pass alignment works by increasing alignment of reads to splice junctions by short lengths, and that potential alignment errors are readily identifiable by simple classification. Taken together, two-pass alignment promises to advance quantification and discovery of novel splicing events.
  
  
  BACKGROUND
  arul@med.umich.edu, nesvi@med.umich.edu
  
  
  METHODS
  Two-pass alignment was implemented here as sequential alignment, genome indexing, and re-alignment steps with STAR. Full parameters are provided in Supplementary Table 2.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computational Medicine and Bioinformatics, Michigan Center for Translational Pathology.
authors.forename: Brendan A
authors.initials: BA
authors.lastname: Veeneman
authors.affiliation: Michigan Center for Translational Pathology, Department of Pathology.
authors.forename: Sudhanshu
authors.initials: S
authors.lastname: Shukla
authors.affiliation: Michigan Center for Translational Pathology, Department of Pathology.
authors.forename: Saravana M
authors.initials: SM
authors.lastname: Dhanasekaran
authors.affiliation: Department of Computational Medicine and Bioinformatics, Michigan Center for Translational Pathology, Department of Pathology, Department of Urology and Howard Hughes Medical Institute, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA.
authors.forename: Arul M
authors.initials: AM
authors.lastname: Chinnaiyan
authors.affiliation: Department of Computational Medicine and Bioinformatics, Michigan Center for Translational Pathology, Department of Pathology.
authors.forename: Alexey I
authors.initials: AI
authors.lastname: Nesvizhskii
mesh_terms: D001483:Base Sequence; D045744:Cell Line, Tumor; D030561:Databases, Nucleic Acid; D006801:Humans; D022821:RNA Splice Sites / Q000235:genetics*; D012326:RNA Splicing / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*
chemical_list: D022821:RNA Splice Sites