Associated Papers
Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.
Padigepati SR et al.
Human Genetics, 2024
39085601 (PubMed )
Supplement: 439_2024_2691_MOESM2_ESM.xlsx › MSH2
Evolutionary origin of germline pathogenic variants in human DNA mismatch repair genes.
Lei H et al.
Human Genomics, 2024
38287404 (PubMed )
Supplement: 40246_2024_573_MOESM3_ESM.xls › MSH2
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
Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.
Keskin Karakoyun H et al.
Frontiers in Genetics, 2023
36896237 (PubMed )
Supplement: Table1.xlsx › clinvar_breastcancer_allvariant
Whole-exome Sequencing of Nigerian Prostate Tumors from the Prostate Cancer Transatlantic Consortium (CaPTC) Reveals DNA Repair Genes Associated with African Ancestry.
White JA et al.
Cancer Research Communications, 2022
36922933 (PubMed )
Supplement: crc-22-0136-s01.xlsx › ST1_Known_Germline_Variants
Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants.
Loong L et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2022
34906453 (PubMed )
Supplement: mmc1.xlsx › Sup_Table2_Assay_ClinVar
Disease variant prediction with deep generative models of evolutionary data.
Frazer J et al.
Nature, 2021
Contribution of mRNA Splicing to Mismatch Repair Gene Sequence Variant Interpretation.
Thompson BA et al.
Frontiers in Genetics, 2020
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
MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing.
Mort M et al.
Genome Biology, 2014
24451234 (PubMed )
Supplement: gb-2014-15-1-r19-S1.pdf
Current clinical criteria for Lynch syndrome are not sensitive enough to identify MSH6 mutation carriers.
Sjursen W et al.
Journal of Medical Genetics, 2010
Genomic deletions in MSH2 or MLH1 are a frequent cause of hereditary non-polyposis colorectal cancer: identification of novel and recurrent deletions by MLPA.
Taylor CF et al.
Human Mutation, 2003
Select a paper to view details