Publications by authors named "G Genchev"
Article Synopsis
- Methylmalonic acidemia (MMA) is a rare genetic disorder with a high false-positive rate in initial diagnostic tests, prompting the need for more accurate screening methods.* -
- The researchers developed advanced machine learning models using mass spectrometry data from neonatal blood samples to effectively reduce false positives while maintaining high sensitivity and specificity.* -
- The best-performing model demonstrated impressive accuracy, achieving a 97% area under the curve and minimizing false-positive rates, thereby enhancing the diagnostic process for clinicians identifying MMA in children.*
Background: Pitt-Hopkins syndrome (PTHS) is a neurodevelopmental disorder that remains underdiagnosed and its clinical presentations and mutation profiles in a diverse population are yet to be evaluated. This retrospective study aims to investigate the clinical and genetic characteristics of Chinese patients with PTHS.
Methods: The clinical, biochemical, genetic, therapeutic, and follow-up data of 47 pediatric patients diagnosed with PTHS between 2018 and 2021 were retrospectively analyzed.
Article Synopsis
- The study investigates the role of metabolites in peroxisomal disorders, specifically X-linked adrenoleukodystrophy and Zellweger syndrome, using advanced statistical methods and mass spectrometry data from various patient groups.
- The research utilized techniques like T-SNE, PCA, and sparse PLS-DA to analyze the data and successfully developed reliable classification models to distinguish these disorders from healthy controls.
- Findings indicate significant metabolic differences among groups and highlight hexacosanoylcarnitine as a potential screening marker for diagnosing peroxisomal disorders in Chinese patients.
The quality control of variants from whole-genome sequencing data is vital in clinical diagnosis and human genetics research. However, current filtering methods (Frequency, Hard-Filter, VQSR, GARFIELD, and VEF) were developed to be utilized on particular variant callers and have certain limitations. Especially, the number of eliminated true variants far exceeds the number of removed false variants using these methods.
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