Study
BinDel: software tool for detecting clinically significant microdeletions in low-coverage WGS-based NIPT samples
Study ID | Alternative Stable ID | Type |
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EGAS00001006663 | Other |
Study Description
Clinically pathogenic chromosomal microdeletions causing genetic disorders such as DiGeorge syndrome are rare genetic aberrations that can cause clinically relevant fetal and childhood developmental deficiencies. Clinical severity of such deficiencies depend on the exact genomic location and genes affected by the fetal chromosomal aberration.
Here we present the BinDel, a novel region-aware microdeletion detection software package developed to infer clinically relevant microdeletion risk in low-coverage whole-genome sequencing NIPT data. To test BinDel, we quantified the impact of sequencing coverage, fetal DNA fraction, and region length on microdeletion risk detection accuracy. We also estimated BinDel accuracy on known microdeletion samples and clinically validated aneuploidy samples.
BinDel identified each positive control sample as high risk. We also determined that it is critical to take into account that the sample with a detected high microdeletion risk does not have a full chromosome aneuploidy, as the latter can cause erroneous high microdeletion risk findings. We ... (Show More)
Study Datasets 1 dataset.
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Dataset ID | Description | Technology | Samples |
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EGAD00001009512 |
This dataset contains three sets of samples.
The first sample set contains euploid fetus pregnancies reported by NIPTIFY screening test and postnatal evaluation. Dataset was processed similarly to previously published guidelines from KU Leuven, with modifications [1]. Briefly, peripheral blood samples were collected in cell-free DNA BCT tubes (Streck, USA), and plasma was separated with standard dual centrifugation. Cell-free DNA was extracted from 3 ml plasma using MagMAX Cell-Free DNA ... (Show More)
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NextSeq 550 | 377 |
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