Associated Papers
Routine RNA-based analysis of potential splicing variants facilitates genomic diagnostics and reveals limitations of in silico prediction tools.
Drost M et al.
Hgg Advances, 2026
40988334 (PubMed )
Supplement: mmc2.xlsx › Table_S2
Predicting the impact of rare variants on RNA splicing in CAGI6.
Lord J et al.
Human Genetics, 2025
38170232 (PubMed )
Supplement: 439_2023_2624_MOESM2_ESM.xlsx › SupplementaryTable1
Large-scale application of ClinGen-InSiGHT APC-specific ACMG/AMP variant classification criteria leads to substantial reduction in VUS.
Yin X et al.
American Journal of Human Genetics, 2024
39357517 (PubMed )
Supplement: mmc2.xlsx › c_Pred-data
Genome-wide detection of human intronic AG-gain variants located between splicing branchpoints and canonical splice acceptor sites.
Zhang P et al.
Proceedings of the National Academy of Sciences of the United States of America, 2023
37931111 (PubMed )
Supplement: pnas.2314225120.sd01.xlsx › Dataset_S1._patho_AG-gain_var
SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing.
Leman R et al.
Human Mutation, 2022
36273432 (PubMed )
Supplement: HUMU-43-2308-s002.xlsx › Feuil1
Identification of a Novel Splice Variant (c.423-8A>G) of APC by RNA Sequencing.
Kim A et al.
Annals of Laboratory Medicine, 2020
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