ArticleBMC bioinformatics2025
KF-NIPT: K-mer and fetal fraction-based estimation of chromosomal anomaly from NIPT data.
Article in BMC bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A comprehensive analysis of the impact of genomic imbalance on gene expression in a poplar aneuploidy population.Communications biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-Invasive Prenatal Testing (NIPT) is a technique that allows pregnant women to screen for chromosomal abnormalities in their developing fetus without the need for invasive procedures like amniocentesis or chorionic villus sampling. However, current methods to detect anomaly from maternal cell-free DNAs (cfDNAs) that are based on the sequence read counts calculating z-scores face challenges with false positives and negatives. To address these challenges, we aimed to develop a novel NIPT algorithm named KF-NIPT, which is derived from the initials of k-mer and fetal fraction used in its development with the goal of significantly improving accuracy.
resultsWe developed a KF-NIPT, a new algorithm that estimate chromosomal anomaly by calculating K-mer-based sequence depth and fetal fraction from the whole genome sequencing (WGS) data. Moreover, we implemented a modified preprocessing pipeline for the WGS data, correcting the biases of the genomic mapping quality and the GC contents. The performance of our method was evaluated using publicly available NIPT data. We could demonstrate that our method has better accuracy and sensitivity compared to those of the previous methods.
conclusionsWe 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).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.