Title |
Comparison of mRNA Splicing Assay Protocols across Multiple Laboratories: Recommendations for Best Practice in Standardized Clinical Testing
|
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Published in |
Clinical Chemistry, February 2014
|
DOI | 10.1373/clinchem.2013.210658 |
Pubmed ID | |
Authors |
Phillip J. Whiley, Miguel de la Hoya, Mads Thomassen, Alexandra Becker, Rita Brandão, Inge Sokilde Pedersen, Marco Montagna, Mireia Menéndez, Francisco Quiles, Sara Gutiérrez-Enríquez, Kim De Leeneer, Anna Tenés, Gemma Montalban, Demis Tserpelis, Toshio Yoshimatsu, Carole Tirapo, Michela Raponi, Trinidad Caldes, Ana Blanco, Marta Santamariña, Lucia Guidugli, Gorka Ruiz de Garibay, Ming Wong, Mariella Tancredi, Laura Fachal, Yuan Chun Ding, Torben Kruse, Vanessa Lattimore, Ava Kwong, Tsun Leung Chan, Mara Colombo, Giovanni De Vecchi, Maria Caligo, Diana Baralle, Conxi Lázaro, Fergus Couch, Paolo Radice, Melissa C. Southey, Susan Neuhausen, Claude Houdayer, Jim Fackenthal, Thomas Van Overeem Hansen, Ana Vega, Orland Diez, Rien Blok, Kathleen Claes, Barbara Wappenschmidt, Logan Walker, Amanda B. Spurdle, Melissa A. Brown |
Abstract |
Accurate evaluation of unclassified sequence variants in cancer predisposition genes is essential for clinical management and depends on a multifactorial analysis of clinical, genetic, pathologic, and bioinformatic variables and assays of transcript length and abundance. The integrity of assay data in turn relies on appropriate assay design, interpretation, and reporting. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 98 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 19 | 19% |
Researcher | 19 | 19% |
Student > Master | 15 | 15% |
Student > Doctoral Student | 10 | 10% |
Student > Bachelor | 8 | 8% |
Other | 12 | 12% |
Unknown | 15 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 33 | 34% |
Agricultural and Biological Sciences | 19 | 19% |
Medicine and Dentistry | 17 | 17% |
Chemistry | 4 | 4% |
Immunology and Microbiology | 2 | 2% |
Other | 8 | 8% |
Unknown | 15 | 15% |