Associated Papers
Phenotypic evaluation of deep learning models for classifying germline variant pathogenicity.
Chow RD et al.
Npj Precision Oncology, 2024
39427061 (PubMed )
Supplement: 41698_2024_710_MOESM2_ESM.xlsx › S3
The Potential of Genetics in Identifying Women at Lower Risk of Breast Cancer.
Bolze A et al.
Jama Oncology, 2024
38153744 (PubMed )
Supplement: jamaoncol-e235468-s002.xlsx › eTable_4
Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry.
Dumont M et al.
Cancers, 2022
35884425 (PubMed )
Supplement: cancers-14-03363-s001.zip › Table_S3-final_16052022.xlsx › Table_S3B
Breast cancer risks associated with missense variants in breast cancer susceptibility genes.
Dorling L et al.
Genome Medicine, 2022
35585550 (PubMed )
Supplement: 13073_2022_1052_MOESM2_ESM.xlsx › Table_S14
Pathogenic genetic variants from highly connected cancer susceptibility genes confer the loss of structural stability.
Reza MN et al.
Scientific Reports, 2021
34584144 (PubMed )
Supplement: 41598_2021_98547_MOESM1_ESM.zip › Supplementary_files-5-8-21 › Supplementary_file_2.xlsx › Sheet1
Analysis of Sequence and Copy Number Variants in Canadian Patient Cohort With Familial Cancer Syndromes Using a Unique Next Generation Sequencing Based Approach.
Bhai P et al.
Frontiers in Genetics, 2021
34326862 (PubMed )
Supplement: Data_Sheet_1.zip › Supplementary_files › Supplementary_Table_S4.xlsx › Variant_summary
Germline mutations in candidate predisposition genes in individuals with cutaneous melanoma and at least two independent additional primary cancers.
Pritchard AL et al.
Plos One, 2018
29641532 (PubMed )
Supplement: pone.0194098.s003.xlsx › UK10K_AR
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