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
Analyzing the effects of BRCA1/2 variants on mRNA splicing by minigene assay.
Dong Z et al.
Journal of Human Genetics, 2023
MARGINAL: An Automatic Classification of Variants in BRCA1 and BRCA2 Genes Using a Machine Learning Model.
Karalidou V et al.
Biomolecules, 2022
36358902 (PubMed )
Supplement: biomolecules-12-01552-s001.zip › final_annotation_file_CanVaS.xlsx › Sheet1
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 › DBASS3_index
Transposon clusters as substrates for aberrant splice-site activation.
Alvarez MEV et al.
Rna Biology, 2021
32965162 (PubMed )
Supplement: KRNB_A_1805909_SM0818.zip › Supplementary_information › Supplementary_Table_S1.pdf
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_7
Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels.
LaDuca H et al.
Plos One, 2017
28152038 (PubMed )
Supplement: pone.0170843.s003.xlsx › S3_Table
Next-generation sequencing of the BRCA1 and BRCA2 genes for the genetic diagnostics of hereditary breast and/or ovarian cancer.
Trujillano D et al.
The Journal of Molecular Diagnostics : Jmd, 2015
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
Comprehensive splicing functional analysis of DNA variants of the BRCA2 gene by hybrid minigenes.
Acedo A et al.
Breast Cancer Research : Bcr, 2012
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