Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples.
Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-12-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1009684 |
| _version_ | 1818284992564822016 |
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| author | Priit Paluoja Hindrek Teder Amin Ardeshirdavani Baran Bayindir Joris Vermeesch Andres Salumets Kaarel Krjutškov Priit Palta |
| author_facet | Priit Paluoja Hindrek Teder Amin Ardeshirdavani Baran Bayindir Joris Vermeesch Andres Salumets Kaarel Krjutškov Priit Palta |
| author_sort | Priit Paluoja |
| collection | DOAJ |
| description | Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison of the various tools has been published. Here, we compared the outcome accuracies obtained for clinically validated samples with five commonly used computational NIPT aneuploidy analysis tools (WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq) across various sequencing depths (coverage) and fetal DNA fractions. The sample set included cases of fetal trisomy 21 (Down syndrome), trisomy 18 (Edwards syndrome), and trisomy 13 (Patau syndrome). We determined that all of the compared tools were considerably affected by lower sequencing depths, such that increasing proportions of undetected trisomy cases (false negatives) were observed as the sequencing depth decreased. We summarised our benchmarking results and highlighted the advantages and disadvantages of each computational NIPT software. To conclude, trisomy detection for lower coverage NIPT samples (e.g. 2.5M reads per sample) is technically possible but can, with some NIPT tools, produce troubling rates of inaccurate trisomy detection, especially in low-FF samples. |
| first_indexed | 2024-12-13T01:01:37Z |
| format | Article |
| id | doaj.art-9502a8a197d9486dbd7940f103034e13 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-13T01:01:37Z |
| publishDate | 2021-12-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-9502a8a197d9486dbd7940f103034e132022-12-22T00:04:39ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-12-011712e100968410.1371/journal.pcbi.1009684Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples.Priit PaluojaHindrek TederAmin ArdeshirdavaniBaran BayindirJoris VermeeschAndres SalumetsKaarel KrjutškovPriit PaltaNon-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison of the various tools has been published. Here, we compared the outcome accuracies obtained for clinically validated samples with five commonly used computational NIPT aneuploidy analysis tools (WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq) across various sequencing depths (coverage) and fetal DNA fractions. The sample set included cases of fetal trisomy 21 (Down syndrome), trisomy 18 (Edwards syndrome), and trisomy 13 (Patau syndrome). We determined that all of the compared tools were considerably affected by lower sequencing depths, such that increasing proportions of undetected trisomy cases (false negatives) were observed as the sequencing depth decreased. We summarised our benchmarking results and highlighted the advantages and disadvantages of each computational NIPT software. To conclude, trisomy detection for lower coverage NIPT samples (e.g. 2.5M reads per sample) is technically possible but can, with some NIPT tools, produce troubling rates of inaccurate trisomy detection, especially in low-FF samples.https://doi.org/10.1371/journal.pcbi.1009684 |
| spellingShingle | Priit Paluoja Hindrek Teder Amin Ardeshirdavani Baran Bayindir Joris Vermeesch Andres Salumets Kaarel Krjutškov Priit Palta Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples. PLoS Computational Biology |
| title | Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples. |
| title_full | Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples. |
| title_fullStr | Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples. |
| title_full_unstemmed | Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples. |
| title_short | Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples. |
| title_sort | systematic evaluation of nipt aneuploidy detection software tools with clinically validated nipt samples |
| url | https://doi.org/10.1371/journal.pcbi.1009684 |
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