4.6 Article

CACSV: a computational web-sever that provides classification for cancer somatic genetic variants from different tissues

期刊

BMC BIOINFORMATICS
卷 24, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12859-023-05207-1

关键词

Cancer; Somatic; Genetic variants; Classification

向作者/读者索取更多资源

This study developed a computational web-server to increase the accessibility and availability of clinically relevant genetic variants. They built a database containing clinical classification for around 3 million cancer genetic variants, and provided a graphical user interface to enhance usability.
Background: Understanding the role and function of genetic variants is extremely important when analyzing and interpreting a myriad of human disease processes. For cancer in general, cell-specific genetic variants are ubiquitous and distinct tissues have significantly heterogenic genetic profiles. In clinical practice, only a few genetic variants have identifiable clinical utility. Finding clinically relevant genetic variants constitute a challenging process. In addition, there had been no reference protocol to provide guidance for cancer somatic genetic variants classification and interpretation. In 2017, the first version of a reference protocol was published by the Association for Molecular Pathology, the American Society of Clinical Oncology, and the College of American Pathologists. Previously, we incorporated the reference protocol into a computational method to expedite the process of identification of clinically relevant genetic variants. In this work, we developed a computational web-server to increase the accessibility and availability of clinically relevant genetic variants. Results: Our work provides the clinical classification for similar to 3 million cancer genetic variants that are now publicly available in a shareable database on GitHub. We have developed a graphical user interface for the database to enhance the accessibility and ease-of-use. Conclusion: CACSV provides an open-source for about 3 million cancer tissue-specific genetic variants with their assigned clinical annotations.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据