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BioProject ID : PRJKA220469

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Project title : Non-invasive prenatal test sequencing

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Name Lee Junnam
Organization GC Genome
Department Genome Research Center

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Registration Date 2022-09-26

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NTIS Number -
Project Title Non-invasive prenatal test sequencing
Relevance medical
Description We developed a novel algorithm for non-invasive prenatal testing (NIPT) to detect fetal chromosome aneuploidy using the DNA fragment distance concept and an AI algorithm. The novel NIPT is the first algorithm to apply the DNA fragment distance concept in an AI algorithm. This algorithm showed better performance than the conventional Z-test algorithms that apply the mean and standard deviation of a reference set. We believe that our study makes a significant contribution to the literature because to date, no study has reported the use of deep learning in the screening of chromosomal aneuploidy. AI algorithms that apply the fragment distance and target repeat stacking (TRS) image generation similar to the one developed in this study are expected to be useful in the future for applications in other fields, including early cancer diagnosis and minimal residual cancer detection.
Project Data Type * Whole Genome sequencing
Sample Scope * Multiisolate

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Sample Group

BioSample
Accession ID
Project Title Sample Type Registration Date
GSAMK220814 Human sample Human sample 2022-10-25

Submitters’s Submissions

BioProject
Accession ID
Project Title Sample Scope Project Data Type Registration
Date
PRJKA220469 Non-invasive prenatal test sequencing Multiisolate Whole Genome sequencing 2022-09-26

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