Bianca K Stöcker1, Johannes Köster2, Sven Rahmann1. 1. Genome Informatics, Institute of Human Genetics, University of Duisburg-Essen, Essen, 45147, Germany. 2. Life Sciences, Centrum Wiskunde & Informatica (CWI), Amsterdam 1098 XG, The Netherlands Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA.
Abstract
MOTIVATION: 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. RESULTS: 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. AVAILABILITY AND IMPLEMENTATION: SimLoRD is available open source at http://bitbucket.org/genomeinformatics/simlord/ and installable via Bioconda (http://bioconda.github.io). CONTACT: Bianca.Stoecker@uni-due.de or Sven.Rahmann@uni-due.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: 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. RESULTS: 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. AVAILABILITY AND IMPLEMENTATION: SimLoRD is available open source at http://bitbucket.org/genomeinformatics/simlord/ and installable via Bioconda (http://bioconda.github.io). CONTACT: Bianca.Stoecker@uni-due.de or Sven.Rahmann@uni-due.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Illyoung Choi; Alise J Ponsero; Matthew Bomhoff; Ken Youens-Clark; John H Hartman; Bonnie L Hurwitz Journal: Gigascience Date: 2019-02-01 Impact factor: 6.524
Authors: Ahmed Al Qaffas; Jenna Nichols; Andrew J Davison; Amine Ourahmane; Laura Hertel; Michael A McVoy; Salvatore Camiolo Journal: Virus Evol Date: 2021-04-23