REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

Journal: Molecular genetics & genomic medicine
PMID: 32961042

Abstract

BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an automated software package for accurate and direct generation of clinical diagnostic reports for prenatal and products of conception (POC) samples.

Authors

  • Mengmeng Liu
    Department of First Hospital, Jilin University, Changchun, China.
  • Yunshan Zhong
    Berry Genomics Corporation, Beijing, China.
  • Hongqian Liu
    Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu.
  • Desheng Liang
    Center for Medical Genetics, School of Life Sciences, Central South University, Changsha, China.
  • Erhong Liu
    Berry Genomics Corporation, Beijing, China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Feng Tian
    Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston. University, 24 Cummington Mall, Boston, MA 02215, USA.
  • Qiaowei Liang
    Hunan Jiahui Genetics Hospital, Changsha, China.
  • David S Cram
    Berry Genomics Corporation, Beijing, China.
  • Hua Wang
    Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Lingqian Wu
  • Fuli Yu
    Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.

Keywords

External Resources

Popular Topics
Recent Journals