Many rare genetic diseases are associated with recognizable craniofacial features. However, traditional approaches for describing facial morphology rely largely on qualitative clinical observation and free-text descriptions, which are often subjective, non-standardized, and difficult to reproduce across observers and i...
Hong-Zhuo Chen, Zhanliang Wang, Florent Pollet et al.· 0 citations
Background: Large-scale mitochondrial DNA (mtDNA) rearrangement, including deletion or duplication, is one of the important causes of primary mitochondrial disease. In clinical practice, short-read sequencing (SRS)-based assays typically detect these rearrangements by identifying regional mtDNA copy-number changes but...
Jing Wang, Joe Chan, Mian Umair Ahsan et al.· Genes· 0 citations
ContextSV, a framework that integrates alignment evidence with copy number predictions derived from sequencing coverage and single-nucleotide variant allele frequencies to improve SV detection, serves as a valuable complement to existing long-read SV detection approaches by improving sensitivity for large and clinicall...
J. E. Perdomo, Mian Umair Ahsan, Jasmine Akoto et al.· NAR Genomics and Bioinformat...· 0 citations
A machine learning algorithm called RankVar is developed to prioritize causative variants for rare diseases, based on clinical notes and genome/exome sequencing profiles, and may provide a useful framework for prioritizing variants in monogenic or oligogenic diseases.
Yuan Zhang, Mian Umair Ahsan, Peng Wang et al.· Genome Medicine· 1 citation
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