Richards S, Aziz N, Bale S et al (2015) Standards and guidelines for the interpretation of sequence variants: a Joint Consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 17:405
Article PubMed PubMed Central Google Scholar
Jain A, Bhoyar RC, Pandhare K et al (2020) IndiGenomes: a comprehensive resource of genetic variants from over 1000 Indian genomes. Nucleic Acids Res 49:D1225–D1232
Landrum MJ, Lee JM, Riley GR et al (2014) ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 42:D980
Article CAS PubMed Google Scholar
Freeman PJ, Hart RK, Gretton LJ et al (2018) VariantValidator: accurate validation, mapping, and formatting of sequence variation descriptions. Hum Mutat 39:61–68
Wang K, Li M, Hakonarson H (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38:e164
Article PubMed PubMed Central Google Scholar
Karolchik D, Hinrichs AS, James Kent W (2009) The UCSC Genome Browser. Curr Protoc Bioinformatics CHAPTER:Unit1.4
Punta M, Coggill PC, Eberhardt RY et al (2012) The pfam protein families database. Nucleic Acids Res 40:D290–301
Article CAS PubMed Google Scholar
Lek M, Karczewski KJ, Minikel EV et al (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature 536:285–291
Article CAS PubMed PubMed Central Google Scholar
(2015) A global reference for human genetic variation. Nature 526:68–74
Fu W, O’Connor TD, Jun G et al (2013) Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 493:216–220
Article CAS PubMed Google Scholar
Ng PC, Henikoff S (2003) SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res 31:3812–3814
Article CAS PubMed PubMed Central Google Scholar
Adzhubei I, Jordan DM, Sunyaev SR (2013) Predicting functional effect of human missense mutations using PolyPhen-2. Curr Protoc Hum Genet Chap. 7:Unit7.20
Rentzsch P, Witten D, Cooper GM et al (2018) CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res 47:D886–D894
Article PubMed Central Google Scholar
Xiang J, Peng J, Baxter S, Peng Z (2020) AutoPVS1: an automatic classification tool for PVS1 interpretation of null variants. Hum Mutat 41:1488–1498
Article CAS PubMed Google Scholar
Parsons MT, de la Hoya M, Richardson ME et al (2024) Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 variant Curation Expert Panel. medRxiv 2024.01.22.24301588
Liu X, Li C, Mou C et al (2020) dbNSFP v4: a comprehensive database of transcript-specific functional predictions and annotations for human nonsynonymous and splice-site SNVs. Genome Med 12:1–8
Cline MS, Liao RG, Parsons MT et al (2018) BRCA challenge: BRCA Exchange as a global resource for variants in BRCA1 and BRCA2. PLoS Genet 14:e1007752
Article PubMed PubMed Central Google Scholar
Fokkema IFAC, Taschner PEM, Schaafsma GCP et al (2011) LOVD v.2.0: the next generation in gene variant databases. Hum Mutat 32:557–563
Article CAS PubMed Google Scholar
ARUP Scientific Resource for Research and Education BRCA Database. https://arup.utah.edu/database/BRCA/index.php. Accessed 4 Jan 2023
Béroud C, Letovsky SI, Braastad CD et al (2016) BRCA share: a Collection of clinical BRCA gene variants. Hum Mutat 37:1318–1328
Findlay GM, Daza RM, Martin B et al (2018) Accurate classification of BRCA1 variants with saturation genome editing. Nature 562:217–222
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