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Ranking of non-coding pathogenic variants and putative essential regions of the human genome
- Source :
- Nature Communications, Vol 10, Iss 1, Pp 1-9 (2019)
- Publication Year :
- 2019
- Publisher :
- Nature Portfolio, 2019.
-
Abstract
- Whole genome sequencing (WGS) holds promise to solve a subset of Mendelian disease cases for which exome sequencing did not provide a genetic diagnosis. Here, Wells et al. report a supervised machine learning model trained on functional, mutational and structural features for rank-scoring and interpreting variants in non-coding regions from WGS.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 10
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.55b664ef26374b7793165c7ee6e62223
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-019-13212-3