title: MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples.
abstract: BACKGROUND
  High-throughput sequencing of mRNA (RNA-Seq) has led to tremendous improvements in the detection of expressed genes and reconstruction of RNA transcripts. However, the extensive dynamic range of gene expression, technical limitations and biases, as well as the observed complexity of the transcriptional landscape, pose profound computational challenges for transcriptome reconstruction.
  
  
  RESULTS
  We present the novel framework MITIE (Mixed Integer Transcript IdEntification) for simultaneous transcript reconstruction and quantification. We define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data and show how to find the optimal solution using Mixed Integer Programming. MITIE can (i) take advantage of known transcripts, (ii) reconstruct and quantify transcripts simultaneously in multiple samples, and (iii) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction. We present an extensive study based on realistic simulated RNA-Seq data. When compared with state-of-the-art approaches, MITIE proves to be significantly more sensitive and overall more accurate. Moreover, MITIE yields substantial performance gains when used with multiple samples. We applied our system to 38 Drosophila melanogaster modENCODE RNA-Seq libraries and estimated the sensitivity of reconstructing omitted transcript annotations and the specificity with respect to annotated transcripts. Our results corroborate that a well-motivated objective paired with appropriate optimization techniques lead to significant improvements over the state-of-the-art in transcriptome reconstruction.
  
  
  BACKGROUND
  MITIE is implemented in C++ and is available from http://bioweb.me/mitie under the GPL license.
authors: Computational Biology Center, Sloan-Kettering Institute, 1275 York Avenue, New York, NY 10065, USA and Friedrich Miescher Laboratory, Max Planck Society, Spemannstr. 39, 72076 Tübingen, Germany.
authors: Jonas
authors: J
authors: Behr
authors: André
authors: A
authors: Kahles
authors: Yi
authors: Y
authors: Zhong
authors: Vipin T
authors: VT
authors: Sreedharan
authors: Philipp
authors: P
authors: Drewe
authors: Gunnar
authors: G
authors: Rätsch
mesh_terms: D000818:Animals; D004331:Drosophila melanogaster; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D020407:Internet; D012313:RNA / Q000032:analysis* / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D014158:Transcription, Genetic
chemical_list: D012313:RNA
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