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RExPRT: a machine learning tool to predict pathogenicity of tandem repeat loci

Authors :
Sarah Fazal
Matt C. Danzi
Isaac Xu
Shilpa Nadimpalli Kobren
Shamil Sunyaev
Chloe Reuter
Shruti Marwaha
Matthew Wheeler
Egor Dolzhenko
Francesca Lucas
Stefan Wuchty
Mustafa Tekin
Stephan Züchner
Vanessa Aguiar-Pulido
Publication Year :
2023
Publisher :
Cold Spring Harbor Laboratory, 2023.

Abstract

Tandem repeats (TRs) are polymorphic sequences of DNA that are composed of repeating units of motifs, whose lengths can vary depending on the type of TR. Expansions of TRs are responsible for approximately 50 monogenic diseases, compared to over 4,300 disease causing genes disrupted by single nucleotide variants and small indels. It appears thus reasonable to expect the discovery of additional pathogenic repeat expansions, which has the potential of significantly narrowing the current diagnostic gap in many diseases. Recently, short and long-read whole genome sequencing with the use of advanced bioinformatics tools, have identified a growing number of TR expansions in the human population. The majority of these loci are expanded in

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........3d5659c05866d6bcab29a2087f056101
Full Text :
https://doi.org/10.1101/2023.03.22.533484