ClinVar data parsing

Xiaolei Zhang; Eric V Minikel; Anne H O'Donnell-Luria; Daniel G MacArthur; James S Ware; Ben Weisburd

doi:10.12688/wellcomeopenres.11640.1

ClinVar data parsing

Wellcome Open Res. 2017 May 23:2:33. doi: 10.12688/wellcomeopenres.11640.1. eCollection 2017.

Authors

Xiaolei Zhang^#^{1

2}, Eric V Minikel^#^{3

4}, Anne H O'Donnell-Luria^{3

4

5}, Daniel G MacArthur^{3

4}, James S Ware^{1

2

6}, Ben Weisburd^{3

4}

Affiliations

¹ National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK.
² Royal Brompton Cardiovascular Research Centre, Royal Brompton & Harefield Hospitals NHS Trust, London, SW3 6NP, UK.
³ Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, 02114, USA.
⁴ Program in Medical and Population Genetics,, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, USA.
⁵ Boston Children's Hospital, Boston, Massachusetts, 02115, USA.
⁶ MRC London Institute of Medical Sciences, Imperial College London, London, W12 0NN, UK.

^# Contributed equally.

Abstract

This software repository provides a pipeline for converting raw ClinVar data files into analysis-friendly tab-delimited tables, and also provides these tables for the most recent ClinVar release. Separate tables are generated for genome builds GRCh37 and GRCh38 as well as for mono-allelic variants and complex multi-allelic variants. Additionally, the tables are augmented with allele frequencies from the ExAC and gnomAD datasets as these are often consulted when analyzing ClinVar variants. Overall, this work provides ClinVar data in a format that is easier to work with and can be directly loaded into a variety of popular analysis tools such as R, python pandas, and SQL databases.

Keywords: ClinVar; Mendelian disease; XML parsing; pathogenic variants; variant interpretation.

Abstract

Grants and funding