title: SimLoRD: Simulation of Long Read Data.
abstract: Third generation sequencing methods provide longer reads than second generation methods and have distinct error characteristics. While there exist many read simulators for second generation data, there is a very limited choice for third generation data.
  
  
  
  We analyzed public data from Pacific Biosciences (PacBio) SMRT sequencing, developed an error model and implemented it in a new read simulator called SimLoRD. It offers options to choose the read length distribution and to model error probabilities depending on the number of passes through the sequencer. The new error model makes SimLoRD the most realistic SMRT read simulator available.
  
  
  
  SimLoRD is available open source at http://bitbucket.org/genomeinformatics/simlord/ and installable via Bioconda (http://bioconda.github.io).
  
  
  
  Bianca.Stoecker@uni-due.de or Sven.Rahmann@uni-due.de
  
  
  
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Genome Informatics, Institute of Human Genetics, University of Duisburg-Essen, Essen, 45147, Germany.
authors.forename: Bianca K
authors.initials: BK
authors.lastname: Stöcker
authors.affiliation: Life Sciences, Centrum Wiskunde & Informatica (CWI), Amsterdam 1098 XG, The Netherlands Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
authors.forename: Johannes
authors.initials: J
authors.lastname: Köster
authors.affiliation: Genome Informatics, Institute of Human Genetics, University of Duisburg-Essen, Essen, 45147, Germany.
authors.forename: Sven
authors.initials: S
authors.lastname: Rahmann
mesh_terms: D003198:Computer Simulation; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software