Authors: Junghyun Namkung
Addresses: AI/DT Centre SK Telecom, 65 Eulji-ro, Myeong-dong, Jung-gu, 04539, South Korea
Abstract: Non-Invasive Prenatal Testings (NIPT) for chromosomal aneuploidy are widely applied but not yet for monogenic diseases. In this study, we have developed new analysis algorithms for detecting foetal single gene mutations that are linked to a mendelian disease by sequencing maternal blood samples. The proposed algorithm used two approaches to determine the foetal mutation status. If the mutation type is a duplication, we use the allele frequency of the heterozygous site, and if the mutation is a deletion, we use the ratio of the relative read depth of cell-free DNA to the parent genomic DNA. The algorithms were applied to real data consisting of four pairs of sequencing results generated using peripheral blood samples from two pregnant women. Both sample providers have their first child with Duchene Muscular Dystrophy (DMD) disease, a typical X-linked recessive disorder. Sequences were generated using massively parallel sequencing technologies with a targeted sequencing approach.
Keywords: non-invasive prenatal testing; NIPT; cffDNA; monogenic disease.
International Journal of Data Mining and Bioinformatics, 2021 Vol.25 No.1/2, pp.53 - 64
Received: 23 Mar 2021
Accepted: 05 Apr 2021
Published online: 05 Aug 2021 *