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Sci Rep. 2018 Apr 4;8(1):5616. doi: 10.1038/s41598-018-23589-8.

NIPTmer: rapid k-mer-based software package for detection of fetal aneuploidies.

Author information

1
Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
2
Department of Obstetrics and Gynaecology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.
3
Women's Clinic, Tartu University Hospital, Tartu, Estonia.
4
Competence Centre on Health Technologies, Tartu, Estonia.
5
Department of Biomedicine, Institute of Bio- and Translational Medicine, University of Tartu, Tartu, Estonia.
6
Estonian Genome Center, University of Tartu, Tartu, Estonia.
7
Center for Human Genetics, KU Leuven, Leuven, Belgium.
8
Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.
9
Molecular Neurology Research Program, University of Helsinki and Folkhälsan Institute of Genetics, Helsinki, Finland.
10
Department of Obstetrics and Gynaecology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia. andres.salumets@ccht.ee.
11
Competence Centre on Health Technologies, Tartu, Estonia. andres.salumets@ccht.ee.
12
Department of Biomedicine, Institute of Bio- and Translational Medicine, University of Tartu, Tartu, Estonia. andres.salumets@ccht.ee.
13
Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland. andres.salumets@ccht.ee.
14
Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia. lauris.kaplinski@ut.ee.

Abstract

Non-invasive prenatal testing (NIPT) is a recent and rapidly evolving method for detecting genetic lesions, such as aneuploidies, of a fetus. However, there is a need for faster and cheaper laboratory and analysis methods to make NIPT more widely accessible. We have developed a novel software package for detection of fetal aneuploidies from next-generation low-coverage whole genome sequencing data. Our tool - NIPTmer - is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data, and applying linear regression model on the counts. Additionally, the filtering process used for k-mer list creation allows one to take into account the genetic variance in a specific sample, thus reducing the source of uncertainty. The processing time of one sample is less than 10 CPU-minutes on a high-end workstation. NIPTmer was validated on a cohort of 583 NIPT samples and it correctly predicted 37 non-mosaic fetal aneuploidies. NIPTmer has the potential to reduce significantly the time and complexity of NIPT post-sequencing analysis compared to mapping-based methods. For non-commercial users the software package is freely available at http://bioinfo.ut.ee/NIPTMer/ .

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