title: Rcount: simple and flexible RNA-Seq read counting.
abstract: CONCLUSIONS
  Analysis of differential gene expression by RNA sequencing (RNA-Seq) is frequently done using feature counts, i.e. the number of reads mapping to a gene. However, commonly used count algorithms (e.g. HTSeq) do not address the problem of reads aligning with multiple locations in the genome (multireads) or reads aligning with positions where two or more genes overlap (ambiguous reads). Rcount specifically addresses these issues. Furthermore, Rcount allows the user to assign priorities to certain feature types (e.g. higher priority for protein-coding genes compared to rRNA-coding genes) or to add flanking regions.
  
  
  METHODS
  Rcount provides a fast and easy-to-use graphical user interface requiring no command line or programming skills. It is implemented in C++ using the SeqAn (www.seqan.de) and the Qt libraries (qt-project.org). Source code and 64 bit binaries for (Ubuntu) Linux, Windows (7) and MacOSX are released under the GPLv3 license and are freely available on github.com/MWSchmid/Rcount.
  
  
  BACKGROUND
  marcschmid@gmx.ch
  
  
  BACKGROUND
  Test data, genome annotation files, useful Python and R scripts and a step-by-step user guide (including run-time and memory usage tests) are available on github.com/MWSchmid/Rcount.
authors.affiliation: Institute of Plant Biology and Zürich-Basel Plant Science Center, University of Zurich, 8008 Zürich, Switzerland.
authors.forename: Marc W
authors.initials: MW
authors.lastname: Schmid
authors.affiliation: Institute of Plant Biology and Zürich-Basel Plant Science Center, University of Zurich, 8008 Zürich, Switzerland.
authors.forename: Ueli
authors.initials: U
authors.lastname: Grossniklaus
mesh_terms: D000465:Algorithms; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software