Associated Papers
Pathogenic Germline Variants in Patients With Metaplastic Breast Cancer.
Demarest K et al.
Jama Network Open, 2025
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
Polygenic risk scores indicate extreme ages at onset of breast cancer in female BRCA1/2 pathogenic variant carriers.
Borde J et al.
Bmc Cancer, 2022
35761208 (PubMed )
Supplement: 12885_2022_9780_MOESM5_ESM.xlsx › Tabelle1
Human BRCA pathogenic variants were originated during recent human history.
Li J et al.
Life Science Alliance, 2022
35165121 (PubMed )
Supplement: LSA-2021-01263_TableS2.xlsx › BRCA1
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
Analysis of 30 putative BRCA1 splicing mutations in hereditary breast and ovarian cancer families identifies exonic splice site mutations that escape in silico prediction.
Wappenschmidt B et al.
Plos One, 2012
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