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Deciphering potential causative factors for undiagnosed Waardenburg syndrome through multi-data integration.

Fengying SunMinmin XiaoDong JiFeng ZhengTieliu Shi
Published in: Orphanet journal of rare diseases (2024)
Our study provides new insights into the potential causative factors of WS and an alternative way to explore clinically undiagnosed cases, which will promote clinical diagnosis and genetic counseling. However, the two potential disease-causing genes (KIT, CHD7) and 32 potential pathogenic variants (PAX3: 20, MITF: 7, SOX10: 5) predicted by multi-data integration in this study are all computational predictions and need to be further verified through experiments in follow-up research.
Keyphrases
  • genome wide
  • human health
  • electronic health record
  • copy number
  • risk assessment
  • climate change
  • deep learning
  • hepatitis c virus
  • artificial intelligence
  • data analysis
  • antiretroviral therapy