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Journal article

SV-AUTOPILOT: optimized, automated construction of structural variation discovery and benchmarking pipelines

  • Leung, Wai Yi Sequencing Analysis Support Core, Leiden University Medical Center, Leiden, The Netherlands
  • Marschall, Tobias Center for Bioinformatics, Saarland University, Saarbrücken, Germany - Max Planck Institute for Informatics, Saarbrücken, Germany - Centrum Wiskunde and Informatica, Amsterdam, The Netherlands
  • Paudel, Yogesh Animal Breeding and Genomics Centre, Wageningen University, Wageningen, The Netherlands
  • Falquet, Laurent University of Fribourg and Swiss Institute of Bioinformatics, Fribourg Switzerland
  • Mei, Hailiang Sequencing Analysis Support Core, Leiden University Medical Center, Leiden, The Netherlands
  • Schönhuth, Alexander Centrum Wiskunde and Informatica, Amsterdam, The Netherlands
  • Maoz, Tiffanie Yael Weizmann Institute of Science, Rehovot, Israel
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    25.03.2015
Published in:
  • BMC Genomics. - 2016, vol. 16, p. 238
Structural variation
SV tool
Meta-tool
Non-human genome
Standardized pipeline
SV prediction
Benchmarking
Next-generation sequencing analysis
SV tool development
English Many tools exist to predict structural variants (SVs), utilizing a variety of algorithms. However, they have largely been developed and tested on human germline or somatic (e.g. cancer) variation. It seems appropriate to exploit this wealth of technology available for humans also for other species. Objectives of this work included: a) Creating an automated, standardized pipeline for SV prediction. b) Identifying the best tool(s) for SV prediction through benchmarking. c) Providing a statistically sound method for merging SV calls.
Faculty
Faculté des sciences et de médecine
Department
Département de Biologie
Language
  • English
Classification
Biological sciences
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/304756
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