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Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research

Sequencing the exome is quickly becoming the preferred method for discovering disease-inducing mutations. While obtaining data sets is a straightforward procedure, the subsequent analysis and interpretation of the data is a limiting step for clinical applications. Thus, while the initial mutation an...

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Detalles Bibliográficos
Autores principales: Hansen, Marcus Celik, Nederby, Line, Roug, Anne, Villesen, Palle, Kjeldsen, Eigil, Nyvold, Charlotte Guldborg, Hokland, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4487347/
https://www.ncbi.nlm.nih.gov/pubmed/26150983
http://dx.doi.org/10.1016/j.mex.2015.03.003
Descripción
Sumario:Sequencing the exome is quickly becoming the preferred method for discovering disease-inducing mutations. While obtaining data sets is a straightforward procedure, the subsequent analysis and interpretation of the data is a limiting step for clinical applications. Thus, while the initial mutation and variant calling can be performed by a bioinformatician or trained researcher, the output from robust packages such as MuTect and GATK is not directly informative for the general life scientists. In attempt to obviate this problem we have created complementary Wolfram scripts, which enable easy downstream annotation and selection, presented here in the perspective of hematological relevance. It also provides the researcher with the opportunity to extend the analysis by having a full-fledged programming and analysis environment of Mathematica at hand. In brief, post-processing is performed by: • Mapping of germ line and somatic variants to coding regions, and defining variant sets within Mathematica. • Processing of variants in variant effect predictor. • Extended annotation, relevance scoring and defining focus areas through the provided functions.