Associated Papers
Reclassification of VUS in BRCA1 and BRCA2 using the new BRCA1/BRCA2 ENIGMA track set demonstrates the superiority of ClinGen ENIGMA Expert Panel specifications over the standard ACMG/AMP classification system.
Benet-Pagès A et al.
Genetics in Medicine Open, 2025
SpliceAI-10k calculator for the prediction of pseudoexonization, intron retention, and exon deletion.
Canson DM et al.
Bioinformatics (oxford, England), 2023
37021934 (PubMed )
Supplement: btad179_supplementary_data.zip › SAI10kcalc_supp_tables_final.xlsx › S1.variants
APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP.
Walker LC et al.
Medrxiv : the Preprint Server for Health Sciences, 2023
36865205 (PubMed )
Supplement: media-10.xlsx › Table_S2
Prognostic value of baseline genetic features and newly identified TP53 mutations in advanced breast cancer.
Zhang L et al.
Molecular Oncology, 2022
35971249 (PubMed )
Supplement: MOL2-16-3689-s005.xlsx › Table_S3
Background splicing as a predictor of aberrant splicing in genetic disease.
Alexieva D et al.
Rna Biology, 2022
35188075 (PubMed )
Supplement: KRNB_A_2024031_SM7960.zip › Supplementary_information › Table_S2_css.xlsx › Table_S2_DBASS5_index
A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity.
Shamsani J et al.
Bioinformatics (oxford, England), 2019
30475984 (PubMed )
Supplement: bty960_supplementary_data.zip › bty960-Suppl_data › Supplementary_Table_S1.xlsx › Sheet1
Corrigendum: Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.
Leman R et al.
Nucleic Acids Research, 2018
30321405 (PubMed )
Supplement: gky979_supplemental_files.zip › Corrigendum_supplementary_table.xlsx › AllData
Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.
Leman R et al.
Nucleic Acids Research, 2018
29750258 (PubMed )
Supplement: gky372_supplemental_files.zip › SPiCE_table_supp.R2.xlsx › Table_S2
Computational Tools for Splicing Defect Prediction in Breast/Ovarian Cancer Genes: How Efficient Are They at Predicting RNA Alterations?
Moles-Fernández A et al.
Frontiers in Genetics, 2018
30233647 (PubMed )
Supplement: Table_1.XLSX › Supplem_Table_6
Interpretation of mRNA splicing mutations in genetic disease: review of the literature and guidelines for information-theoretical analysis.
Caminsky N et al.
F1000research, 2014
25717368 (PubMed )
Supplement: f1000research-3-6038-s0000.tgz › e0d3facd-5877-477e-9217-8c5aa68746f2_Supplementary-Tables-11112014.zip › Supplementary-Tables-and-Figures-11112014 › Supplementary_Table_10._Splicing_Mutation_Calculator_Source_Datav2.xlsx › Supplementary_Table_10
Intronic variants in BRCA1 and BRCA2 that affect RNA splicing can be reliably selected by splice-site prediction programs.
Vreeswijk MP et al.
Human Mutation, 2009
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