Associated Papers
Spectrum of Genetic Variants in the Most Common Genes Causing Inherited Retinal Disease in a Large Molecularly Characterized United Kingdom Cohort.
Lin S et al.
Ophthalmology. Retina, 2024
38219857 (PubMed )
Supplement: mmc1.pdf
Compendium of Clinical Variant Classification for 2,246 Unique ABCA4 Variants to Clarify Variant Pathogenicity in Stargardt Disease Using a Modified ACMG/AMP Framework.
Cornelis SS et al.
Human Mutation, 2023
40225145 (PubMed )
Supplement: 6815504.f1.zip › S10_PS3_BS3.xlsx › Functional_data_overview
Phenotyping of ABCA4 Retinopathy by Machine Learning Analysis of Full-Field Electroretinography.
Glinton SL et al.
Translational Vision Science & Technology, 2022
36178783 (PubMed )
Supplement: tvst-11-9-34_s002.pdf
Benchmarking deep learning splice prediction tools using functional splice assays.
Riepe TV et al.
Human Mutation, 2021
33942434 (PubMed )
Supplement: HUMU-42-799-s001.xlsx › ABCA4_NCSS
A novel statistical method for interpreting the pathogenicity of rare variants.
Wang J et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2021
32884132 (PubMed )
Supplement: NIHMS1630822-supplement-Supplementary_Tables.xlsx › S6_ABCA4_variants
Clinical spectrum, genetic complexity and therapeutic approaches for retinal disease caused by ABCA4 mutations.
Cremers FPM et al.
Progress in Retinal and Eye Research, 2020
Cost-effective molecular inversion probe-based ABCA4 sequencing reveals deep-intronic variants in Stargardt disease.
Khan M et al.
Human Mutation, 2019
MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing.
Mort M et al.
Genome Biology, 2014
24451234 (PubMed )
Supplement: gb-2014-15-1-r19-S1.pdf
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