Personalised analytics for rare disease diagnostics
Genome sequencing is being widely adopted for diagnosis of genetic diseases, but identifying the causal variants remains challenging. Here, the authors introduce a tool that incorporates tissue-specific gene expression data into predicting variant pathogenicity, improving accuracy.
Main Authors: | Denise Anderson, Gareth Baynam, Jenefer M. Blackwell, Timo Lassmann |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2019-11-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-019-13345-5 |
Similar Items
-
SMART Work Design: Accelerating the Diagnosis of Rare Diseases in the Western Australian Undiagnosed Diseases Program
by: Georgia J. Hay, et al.
Published: (2020-09-01) -
Barriers and Considerations for Diagnosing Rare Diseases in Indigenous Populations
by: Carla S. D'Angelo, et al.
Published: (2020-12-01) -
Demystifying Learning Analytics in Personalised Learning
by: Maseleno, Andino, et al.
Published: (2018) -
Digit-all: Rare Diseases
by: Gareth Baynam, et al.
Published: (2020-09-01) -
Editorial: Public Health Genomics
by: Paul Lacaze, et al.
Published: (2019-06-01)