Associated Papers
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
Study of the Genetic Variants in BRCA1/2 and Non-BRCA Genes in a Population-Based Cohort of 2155 Breast/Ovary Cancer Patients, Including 443 Triple-Negative Breast Cancer Patients, in Argentina.
Solano AR et al.
Cancers, 2021
34072659 (PubMed )
Supplement: cancers-13-02711-s001.zip › cancers-1233266-supplementary.pdf
Systematic misclassification of missense variants in BRCA1 and BRCA2 "coldspots".
Dines JN et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2020
31911673 (PubMed )
Supplement: 41436_2019_740_MOESM2_ESM.xlsx › 1._Used_in_analysis
Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort.
Li H et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2020
31853058 (PubMed )
Supplement: 41436_2019_729_MOESM2_ESM.xls › Sheet1
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
Finding driver mutations in cancer: Elucidating the role of background mutational processes.
Brown AL et al.
Plos Computational Biology, 2019
31034466 (PubMed )
Supplement: pcbi.1006981.s010.xlsx › final_benchmark
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_7
Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations.
Martelotto LG et al.
Genome Biology, 2014
25348012 (PubMed )
Supplement: 13059_2014_484_MOESM2_ESM.xlsx › Additional_file_2
BRCA1/2 mutation analysis in 41 ovarian cell lines reveals only one functionally deleterious BRCA1 mutation.
Stordal B et al.
Molecular Oncology, 2013
Comparative in vitro and in silico analyses of variants in splicing regions of BRCA1 and BRCA2 genes and characterization of novel pathogenic mutations.
Colombo M et al.
Plos One, 2013
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