KF-NIPT: K-mer and fetal fraction-based estimation of chromosomal anomaly from NIPT data
We found that using k-mer and fetal fraction reduces errors in NIPT and have integrated this into a pipeline, showing that the traditional read count-based z-score method can be improved. KF-NIPT is implemented in the R and Python environment. The source code is available at https://github.com/eastbrain/KF-NIPT . KF-NIPT has been tested on Ubuntu Linux-64 server and Linux-64 on Windows using a WSL (Windows Subsystem for Linux).
Authors
- Jin-Hee Cho (ORCID: https://orcid.org/0000-0002-5908-4662)
- Jungsan Sohn (ORCID: https://orcid.org/0000-0002-9570-2544)
- Hyun Goo Woo (ORCID: https://orcid.org/0000-0002-0916-893X)
- G. Oh (ORCID: https://orcid.org/0000-0003-0744-1063)
- Ji Hye Choi (ORCID: https://orcid.org/0000-0002-0914-2174)
- Dong In Kim (ORCID: https://orcid.org/0009-0004-8530-6291)
Institutions
- Incheon National University (KR)
- Ajou University (KR)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-05-22
- DOI
- https://doi.org/10.1186/s12859-025-06127-y
- Citations
- 2
- Primary Topic
- Prenatal Screening and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 6.99
Funders
- Ajou University
- Korea Health Industry Development Institute