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Your search keyword '"Boutry-Kryza N"' showing total 3 results
Start Over Author "Boutry-Kryza N" Journal nucleic acids research
3 results on '"Boutry-Kryza N"'

1. Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.

Author

Leman R, Gaildrat P, Le Gac G, Ka C, Fichou Y, Audrezet MP, Caux-Moncoutier V, Caputo SM, Boutry-Kryza N, Léone M, Mazoyer S, Bonnet-Dorion F, Sevenet N, Guillaud-Bataille M, Rouleau E, Bressac-de Paillerets B, Wappenschmidt B, Rossing M, Muller D, Bourdon V, Revillon F, Parsons MT, Rousselin A, Davy G, Castelain G, Castéra L, Sokolowska J, Coulet F, Delnatte C, Férec C, Spurdle AB, Martins A, Krieger S, and Houdayer C

Published
2020
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2. 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.

Author

Leman R, Gaildrat P, Gac GL, Ka C, Fichou Y, Audrezet MP, Caux-Moncoutier V, Caputo SM, Boutry-Kryza N, Léone M, Mazoyer S, Bonnet-Dorion F, Sevenet N, Guillaud-Bataille M, Rouleau E, Paillerets BB, Wappenschmidt B, Rossing M, Muller D, Bourdon V, Revillon F, Parsons MT, Rousselin A, Davy G, Castelain G, Castéra L, Sokolowska J, Coulet F, Delnatte C, Férec C, Spurdle AB, Martins A, Krieger S, and Houdayer C

Published
2018
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3. Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.

Author

Leman R, Gaildrat P, Le Gac G, Ka C, Fichou Y, Audrezet MP, Caux-Moncoutier V, Caputo SM, Boutry-Kryza N, Léone M, Mazoyer S, Bonnet-Dorion F, Sevenet N, Guillaud-Bataille M, Rouleau E, Bressac-de Paillerets B, Wappenschmidt B, Rossing M, Muller D, Bourdon V, Revillon F, Parsons MT, Rousselin A, Davy G, Castelain G, Castéra L, Sokolowska J, Coulet F, Delnatte C, Férec C, Spurdle AB, Martins A, Krieger S, and Houdayer C

Subjects
BRCA1 Protein genetics, BRCA2 Protein genetics, Breast Neoplasms diagnosis, Breast Neoplasms genetics, Female, Humans, International Cooperation, Internet, Ovarian Neoplasms diagnosis, Ovarian Neoplasms genetics, Reproducibility of Results, Sensitivity and Specificity, Computational Biology methods, Computer Simulation, Genetic Variation, RNA Splice Sites genetics, RNA Splicing
Abstract

Variant interpretation is the key issue in molecular diagnosis. Spliceogenic variants exemplify this issue as each nucleotide variant can be deleterious via disruption or creation of splice site consensus sequences. Consequently, reliable in silico prediction of variant spliceogenicity would be a major improvement. Thanks to an international effort, a set of 395 variants studied at the mRNA level and occurring in 5' and 3' consensus regions (defined as the 11 and 14 bases surrounding the exon/intron junction, respectively) was collected for 11 different genes, including BRCA1, BRCA2, CFTR and RHD, and used to train and validate a new prediction protocol named Splicing Prediction in Consensus Elements (SPiCE). SPiCE combines in silico predictions from SpliceSiteFinder-like and MaxEntScan and uses logistic regression to define optimal decision thresholds. It revealed an unprecedented sensitivity and specificity of 99.5 and 95.2%, respectively, and the impact on splicing was correctly predicted for 98.8% of variants. We therefore propose SPiCE as the new tool for predicting variant spliceogenicity. It could be easily implemented in any diagnostic laboratory as a routine decision making tool to help geneticists to face the deluge of variants in the next-generation sequencing era. SPiCE is accessible at (https://sourceforge.net/projects/spicev2-1/).

Published
2018
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