title: TIGAR2: sensitive and accurate estimation of transcript isoform expression with longer RNA-Seq reads.
abstract: BACKGROUND
  High-throughput RNA sequencing (RNA-Seq) enables quantification and identification of transcripts at single-base resolution. Recently, longer sequence reads become available thanks to the development of new types of sequencing technologies as well as improvements in chemical reagents for the Next Generation Sequencers. Although several computational methods have been proposed for quantifying gene expression levels from RNA-Seq data, they are not sufficiently optimized for longer reads (e.g. >250 bp).
  
  
  RESULTS
  We propose TIGAR2, a statistical method for quantifying transcript isoforms from fixed and variable length RNA-Seq data. Our method models substitution, deletion, and insertion errors of sequencers based on gapped-alignments of reads to the reference cDNA sequences so that sensitive read-aligners such as Bowtie2 and BWA-MEM are effectively incorporated in our pipeline. Also, a heuristic algorithm is implemented in variational Bayesian inference for faster computation. We apply TIGAR2 to both simulation data and real data of human samples and evaluate performance of transcript quantification with TIGAR2 in comparison to existing methods.
  
  
  CONCLUSIONS
  TIGAR2 is a sensitive and accurate tool for quantifying transcript isoform abundances from RNA-Seq data. Our method performs better than existing methods for the fixed-length reads (100 bp, 250 bp, 500 bp, and 1000 bp of both single-end and paired-end) and variable-length reads, especially for reads longer than 250 bp.
authors.forename: Naoki
authors.initials: N
authors.lastname: Nariai
authors.forename: Kaname
authors.initials: K
authors.lastname: Kojima
authors.forename: Takahiro
authors.initials: T
authors.lastname: Mimori
authors.forename: Yukuto
authors.initials: Y
authors.lastname: Sato
authors.forename: Yosuke
authors.initials: Y
authors.lastname: Kawai
authors.forename: Yumi
authors.initials: Y
authors.lastname: Yamaguchi-Kabata
authors.forename: Masao
authors.initials: M
authors.lastname: Nagasaki
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D014644:Genetic Variation; D006367:HeLa Cells; D006801:Humans; D059368:RNA Isoforms / Q000235:genetics*; D012333:RNA, Messenger / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software
chemical_list: D059368:RNA Isoforms; D012333:RNA, Messenger