NIPTeR: an R package for fast and accurate trisomy prediction in non-invasive prenatal testing

Johansson, Lennart; Weerd, Hendrik A de; Boer, Eddy N. de; Dijk, Freerk van; Meerman, Gerard J. te; Sijmons, Rolf H.; Sikkema‐Raddatz, Birgit; Swertz, Morris A.

doi:10.1186/s12859-018-2557-8

Cited by 8 publications

(17 citation statements)

References 15 publications

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“…The training samples were classified as case/control based on chromosomal Z-scores. We used the R-package NIPTer [24] to perform a variation reduction (peak, GC, and chi-squared corrections), match QC, and calculate the Z-score.…”

Section: Statisticsmentioning

confidence: 99%

NIPT Technique Based on the Use of Long Chimeric DNA Reads

Belova

Plakhina²,

Evfratov³

et al. 2020

Genes

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Non-invasive prenatal testing (NIPT) for aneuploidy on Chromosomes 21 (T21), 18 (T18) and 13 (T13) is actively used in clinical practice around the world. One of the limitations of the wider implementation of this test is the high cost of the analysis itself, as high-throughput sequencing is still relatively expensive. At the same time, there is an increasing trend in the length of reads yielded by sequencers. Since extracellular DNA is short, in the order of 140–160 bp, it is not possible to effectively use long reads. The authors used high-performance sequencing of cell-free DNA (cfDNA) libraries that went through additional stages of enzymatic fragmentation and random ligation of the resulting products to create long chimeric reads. The authors used a controlled set of samples to analyze a set of cfDNA samples from pregnant women with a high risk of fetus aneuploidy according to the results of the first trimester screening and confirmed by invasive karyotyping of the fetus using laboratory and analytical approaches developed by the authors. They evaluated the sensitivity, specificity, PPV (positive predictive value), and NPV (negative predictive value) of the results. The authors developed a technique for constructing long chimeric reads from short cfDNA fragments and validated the test using a control set of extracellular DNA samples obtained from pregnant women. The obtained sensitivity and specificity parameters of the NIPT developed by the authors corresponded to the approaches proposed earlier (99.93% and 99.14% for T21; 100% and 98.34% for T18; 100% and 99.17% for T13, respectively).

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Section: Statisticsmentioning

confidence: 99%

NIPT Technique Based on the Use of Long Chimeric DNA Reads

Belova

Plakhina²,

Evfratov³

et al. 2020

Genes

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“…To date, several computational NIPT analysis tools for WGS-based NIPT have been examined in the literature. These include GIPseq [ 3 ], NIPTmer [ 5 ], NIPTeR [ 6 ], RAPIDR [ 7 ], DASAF R [ 8 ], Wisecondor [ 9 ], and WisecondorX [ 9 , 10 ]. However, while these computational tools are commonly used, no head-to-head evaluation studies of these NIPT tools on the same clinically validated samples is available.…”

Section: Introductionmentioning

confidence: 99%

Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

et al. 2021

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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.

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“…To date, several computational NIPT analysis tools for WGS-based NIPT have been published. These include GIPseq (3), NIPTmer (5), NIPTeR (6), RAPIDR (7), DASAF R (8), Wisecondor (9), and WisecondorX (9, 10). However, while these computational tools are widely used, no head-to-head evaluation of these NIPT tools on the same clinically validated samples is available.…”

Section: Introductionmentioning

confidence: 99%

“…A second relevant aspect of the computational NIPT aneuploidy detection is the analytical interpretation of the computational tool output. Commonly used NIPT tools output a per chromosome metric describing the difference (or similarity) of the sample of interest compared to reference group samples, representing the NIPT data of known/validated euploid samples (3, 5, 6, 9, 10). While some tools do provide explicit guidelines for interpreting the output (6), in general, the NIPT software output and analytical interpretation are not well standardised and tend to be highly dependent of the software, laboratory protocols, sample pre-processing and also reference group utilised in the process.…”

Section: Introductionmentioning

confidence: 99%

“…The proportion of fetal DNA fraction (FF), generating the signal of interest, is a critical sample-level quality control determinant, allowing to detect samples with too low FF, for which the computational aneuploidy calling nor euploidy confirmation cannot be performed confidently. As low-coverage WGS-based NIPT assays and the following computational analyses mostly do not distinguish between fetal and maternally originating sequencing reads (but analyse them as a whole), a sufficient proportion of fetal DNA fraction is crucial (3, 5, 6, 9, 10, 13).…”

Section: Introductionmentioning

confidence: 99%

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Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

Paluoja

Teder

Ardeshirdavani³

et al. 2021

Preprint

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Motivation: 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 comprehensive and direct accuracy comparison of these tools is published. Here, we evaluate and determine the precision of five commonly used computational NIPT aneuploidy analysis tools, considering diverse sequencing depth (coverage) and fetal DNA fraction (FF) on clinically validated NIPT samples. Methods: We evaluated computational NIPT aneuploidy analysis tools WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq, on the same set of clinically validated samples, subsampled to different sequencing coverages between 1.25-20M reads per sample (RPS). These clinically validated samples consisted of 423 samples, including 19 samples with fetal chromosome 21 trisomy (T21, Down syndrome), eight trisomy 18 (T18, Edwards syndrome) and three trisomy 13 (T13, Patau syndrome) samples. For each software and sequencing coverage, we determined the number of false-negative and false-positive trisomy/euploidy calls. For a uniform trisomy detection interpretation, we defined a framework based on the percent-point function for determining the cut-off threshold for calling aneuploidy based on the sample Z-score and the reference group Z-score distribution. We also determined the effect of the naturally occurring arbitrary read placement driven uncertainty on T21 detection at very low sequencing coverage and the effect of cell-free fetal DNA fraction (FF) on the accuracy of these computational tools in the case of various sequencing coverages. Results: This is the first head-to-head comparison of NIPT aneuploidy detection tools for the low-coverage whole-genome sequencing approach. We determined that, with the currently available software tools, the minimum sequencing coverage with no false-negative trisomic cases was 5M RPS. Secondly, for these compared tools, the number of false-negative trisomic cases could be reduced if the trisomy call cut-off threshold considers the Z-score distribution of euploid reference samples. Thirdly, we observed that in the case of low FF, both aneuploidy Z-score and FF inference was considerably less accurate, especially in NIPT assays with 5M RPS or lower coverage. Conclusions: We determined that all compared computational NIPT tools were affected by lower sequencing depth, resulting in systematically increasing the proportions of false-negative trisomy results as the sequencing depth decreased. Trisomy detection for lower coverage NIPT samples (e.g. 2.5M RPS) is technically possible but can increase the proportion of false-positive and false-negative trisomic cases, especially in the case of low FF.

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NIPTeR: an R package for fast and accurate trisomy prediction in non-invasive prenatal testing

Cited by 8 publications

References 15 publications

NIPT Technique Based on the Use of Long Chimeric DNA Reads

NIPT Technique Based on the Use of Long Chimeric DNA Reads

Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

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