Combined genetic and splicing analysis of BRCA1 c.[594-2A>C; 641A>G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms.

de la Hoya, M; Soukarieh, O; López-Perolio, I; Vega, A; Walker, LC; van Ierland, Y; Baralle, D; Santamariña, M; Lattimore, V; Wijnen, J; +65 more... Whiley, P; Blanco, A; Raponi, M; Hauke, J; Wappenschmidt, B; Becker, A; Hansen, TV; Behar, R; KConFaB investigators; Niederacher, D; Arnold, N; Dworniczak, B; Steinemann, D; Faust, U; Rubinstein, W; Hulick, PJ; Houdayer, C; Caputo, SM; Castera, L; Pesaran, T; Chao, E; Brewer, C; Southey, MC; van Asperen, CJ; Singer, CF; Sullivan, J; Poplawski, N; Mai, P; Peto, J; Johnson, N; Burwinkel, B; Surowy, H; Bojesen, SE; Flyger, H; Lindblom, A; Margolin, S; Chang-Claude, J; Rudolph, A; Radice, P; Galastri, L; Olson, JE; Hallberg, E; Giles, GG; Milne, RL; Andrulis, IL; Glendon, G; Hall, P; Czene, K; Blows, F; Shah, M; Wang, Q; Dennis, J; Michailidou, K; McGuffog, L; Bolla, MK; Antoniou, AC; Easton, DF; Couch, FJ; Tavtigian, S; Vreeswijk, M; Parsons, M; Meeks, H; Martins, A; Goldgar, DE; Spurdle, AB; (2016) Combined genetic and splicing analysis of BRCA1 c.[594-2A>C; 641A>G] highlights the relevance of naturally occurring in-frame transcripts for developing disease gene variant classification algorithms. Human molecular genetics. ISSN 0964-6906 DOI: https://doi.org/10.1093/hmg/ddw094

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