License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.WABI.2020.12
URN: urn:nbn:de:0030-drops-128013
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Ma, Cong ; Zheng, Hongyu ; Kingsford, Carl

Exact Transcript Quantification Over Splice Graphs

LIPIcs-WABI-2020-12.pdf (0.6 MB)


The probability of sequencing a set of RNA-seq reads can be directly modeled using the abundances of splice junctions in splice graphs instead of the abundances of a list of transcripts. We call this model graph quantification, which was first proposed by Bernard et al. (2014). The model can be viewed as a generalization of transcript expression quantification where every full path in the splice graph is a possible transcript. However, the previous graph quantification model assumes the length of single-end reads or paired-end fragments is fixed. We provide an improvement of this model to handle variable-length reads or fragments and incorporate bias correction. We prove that our model is equivalent to running a transcript quantifier with exactly the set of all compatible transcripts. The key to our method is constructing an extension of the splice graph based on Aho-Corasick automata. The proof of equivalence is based on a novel reparameterization of the read generation model of a state-of-art transcript quantification method. This new approach is useful for modeling scenarios where reference transcriptome is incomplete or not available and can be further used in transcriptome assembly or alternative splicing analysis.

BibTeX - Entry

  author =	{Cong Ma and Hongyu Zheng and Carl Kingsford},
  title =	{{Exact Transcript Quantification Over Splice Graphs}},
  booktitle =	{20th International Workshop on Algorithms in Bioinformatics (WABI 2020)},
  pages =	{12:1--12:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-161-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{172},
  editor =	{Carl Kingsford and Nadia Pisanti},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-128013},
  doi =		{10.4230/LIPIcs.WABI.2020.12},
  annote =	{Keywords: RNA-seq, alternative splicing, transcript quantification, splice graph, network flow}

Keywords: RNA-seq, alternative splicing, transcript quantification, splice graph, network flow
Collection: 20th International Workshop on Algorithms in Bioinformatics (WABI 2020)
Issue Date: 2020
Date of publication: 25.08.2020
Supplementary Material: The source code is available at

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