ContextMap 2: Fast and accurate context-based RNA-seq mapping

  • Thomas Bonfert
  • , Evelyn Kirner
  • , Gergely Csaba
  • , Ralf Zimmer
  • , Caroline C. Friedel*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Background: Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes. Results: In this article, we present ContextMap 2, a new and improved version of ContextMap. Its key novel features are: (i) a plug-in structure that allows easily integrating novel short read alignment programs with improved accuracy and runtime; (ii) context-based identification of insertions and deletions (indels); (iii) mapping of reads spanning an arbitrary number of exons and indels. ContextMap 2 using Bowtie, Bowtie 2 or BWA was evaluated on both simulated and real-life data from the recently published RGASP study. Conclusions: We show that ContextMap 2 generally combines similar or higher recall compared to other state-of-the-art approaches with significantly higher precision in read placement and junction and indel prediction. Furthermore, runtime was significantly lower than for the best competing approaches. ContextMap 2 is freely available at http://www.bio.ifi.lmu.de/ContextMap .

Original languageEnglish
Article number122
JournalBMC Bioinformatics
Volume16
Issue number1
DOIs
StatePublished - 12 Dec 2015
Externally publishedYes

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