• Medientyp: E-Artikel
  • Titel: SangeR: the high-throughput Sanger sequencing analysis pipeline
  • Beteiligte: Schmid, Kai; Dohmen, Hildegard; Ritschel, Nadja; Selignow, Carmen; Zohner, Jochen; Sehring, Jannik; Acker, Till; Amsel, Daniel
  • Erschienen: Oxford University Press (OUP), 2022
  • Erschienen in: Bioinformatics Advances
  • Sprache: Englisch
  • DOI: 10.1093/bioadv/vbac009
  • ISSN: 2635-0041
  • Schlagwörter: General Medicine
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Summary</jats:title> <jats:p>In the era of next generation sequencing and beyond, the Sanger technique is still widely used for variant verification of inconclusive or ambiguous high-throughput sequencing results or as a low-cost molecular genetical analysis tool for single targets in many fields of study. Many analysis steps need time-consuming manual intervention. Therefore, we present here a pipeline-capable high-throughput solution with an optional Shiny web interface, that provides a binary mutation decision of hotspots together with plotted chromatograms including annotations via flat files.</jats:p> </jats:sec> <jats:sec> <jats:title>Availability and implementation</jats:title> <jats:p>SangeR is freely available at https://github.com/Neuropathology-Giessen/SangeR and https://hub.docker.com/repository/docker/kaischmid/sange_r</jats:p> </jats:sec> <jats:sec> <jats:title>Contact</jats:title> <jats:p>Kai.Schmid@patho.med.uni-giessen.de or Daniel.Amsel@patho.med.uni-giessen.de</jats:p> </jats:sec> <jats:sec> <jats:title>Supplementary information</jats:title> <jats:p>Supplementary data are available at Bioinformatics online.</jats:p> </jats:sec>
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