Guidelines for investigating causality of sequence variants in human disease

Guidelines for investigating causality of sequence variants in human disease

24 APRIL 2014 | D. G. MacArthur, T. A. Manolio, D. P. Dimmock, H. L. Rehm, J. Shendure, G. R. Abecasis, D. R. Adams, R. B. Altman, S. E. Antonarakis, E. A. Ashley, J. C. Barrett, L. G. Biesecker, D. F. Conrad, G. M. Cooper, N. J. Cox, M. J. Daly, M. B. Gerstein, D. B. Goldstein, J. N. Hirschhorn, S. M. Leal, L. A. Pennacchio, J. A. Stamatoyannopoulos, S. R. Sunyaev, D. Valle, B. F. Voight, W. Winckler, C. Gunter
The article provides guidelines for investigating the causality of sequence variants in human disease, emphasizing the need for rigorous standards to distinguish disease-causing variants from non-pathogenic ones. It highlights the challenges in assessing sequence variants, particularly in rare and complex diseases, and proposes a two-step process for evaluating evidence of causality: gene-level implication and variant-level implication. The guidelines stress the importance of statistical support, functional studies, and experimental evidence, while also advocating for the use of quantitative frameworks to assess the strength of evidence. The article calls for improved public databases, data sharing, and standardized methods to enhance the reliability and reproducibility of findings. It also addresses the clinical implications of these guidelines, emphasizing the need for responsible interpretation and reporting of results in diagnostic settings.The article provides guidelines for investigating the causality of sequence variants in human disease, emphasizing the need for rigorous standards to distinguish disease-causing variants from non-pathogenic ones. It highlights the challenges in assessing sequence variants, particularly in rare and complex diseases, and proposes a two-step process for evaluating evidence of causality: gene-level implication and variant-level implication. The guidelines stress the importance of statistical support, functional studies, and experimental evidence, while also advocating for the use of quantitative frameworks to assess the strength of evidence. The article calls for improved public databases, data sharing, and standardized methods to enhance the reliability and reproducibility of findings. It also addresses the clinical implications of these guidelines, emphasizing the need for responsible interpretation and reporting of results in diagnostic settings.
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