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Sagot :
The peaks for the amelogenin gene were used to infer the gender. The gender was classified as female if just one peak at the amelogenin locus was seen. The gender was classified as male if the amelogenin locus showed two separate peaks that differed by 6 bp.
Checking the agreement between amelogenin self-reported gender and genotype-inferred gender from genomic data is an important quality control measure in clinical genetic testing because gender mismatches caused by sex chromosomal abnormalities or inaccurate clinical data can have a significant impact on molecular diagnosis and treatment choices. In clinical genetic testing, targeted gene sequencing (TGS) is frequently advised as the initial diagnostic step. However, the current gender-inference methods are insufficient and inaccurate for evaluating TGS data because they are designed for whole genome and whole exome data. In this study, we validated a novel tool called seGMM that infers the gender of a sample using unsupervised clustering (Gaussian mixture model). By aligning the sequencing reads from the samples, the seGMM programme can also find sex chromosomal abnormalities.
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