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NIPTeR: an R package for fast and accurate trisomy prediction in non-invasive prenatal testing
University Medical Center Groningen, The Netherlands.
University of Skövde, School of Bioscience. University of Skövde, The Systems Biology Research Centre. University Medical Center Groningen, The Netherlands. (Bioinformatics, Bioinformatik)ORCID iD: 0000-0001-7804-1177
University Medical Center Groningen, The Netherlands.
University Medical Center Groningen, The Netherlands.
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2018 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 19, no 1, article id 531Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Various algorithms have been developed to predict fetal trisomies using cell-free DNA in non-invasive prenatal testing (NIPT). As basis for prediction, a control group of non-trisomy samples is needed. Prediction accuracy is dependent on the characteristics of this group and can be improved by reducing variability between samples and by ensuring the control group is representative for the sample analyzed.

RESULTS: NIPTeR is an open-source R Package that enables fast NIPT analysis and simple but flexible workflow creation, including variation reduction, trisomy prediction algorithms and quality control. This broad range of functions allows users to account for variability in NIPT data, calculate control group statistics and predict the presence of trisomies.

CONCLUSION: NIPTeR supports laboratories processing next-generation sequencing data for NIPT in assessing data quality and determining whether a fetal trisomy is present. NIPTeR is available under the GNU LGPL v3 license and can be freely downloaded from https://github.com/molgenis/NIPTeR or CRAN.

Place, publisher, year, edition, pages
BioMed Central , 2018. Vol. 19, no 1, article id 531
Keywords [en]
NIPT, Next-generation sequencing, Trisomy prediction
National Category
Bioinformatics and Systems Biology
Research subject
Bioinformatics; INF502 Biomarkers
Identifiers
URN: urn:nbn:se:his:diva-16515DOI: 10.1186/s12859-018-2557-8ISI: 000453523600001PubMedID: 30558531Scopus ID: 2-s2.0-85058624897OAI: oai:DiVA.org:his-16515DiVA, id: diva2:1272623
Available from: 2018-12-19 Created: 2018-12-19 Last updated: 2019-11-20Bibliographically approved

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de Weerd, Hendrik A.

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CiteExportLink to record
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