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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2015-01-01
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| Series: | MethodsX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016115000175 |
| _version_ | 1819160165200429056 |
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| author | Marcus Celik Hansen Line Nederby Anne Roug Palle Villesen Eigil Kjeldsen Charlotte Guldborg Nyvold Peter Hokland |
| author_facet | Marcus Celik Hansen Line Nederby Anne Roug Palle Villesen Eigil Kjeldsen Charlotte Guldborg Nyvold Peter Hokland |
| author_sort | Marcus Celik Hansen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T16:52:06Z |
| format | Article |
| id | doaj.art-5316969cb95147378e0dc20890aeed15 |
| institution | Directory Open Access Journal |
| issn | 2215-0161 |
| language | English |
| last_indexed | 2024-12-22T16:52:06Z |
| publishDate | 2015-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | MethodsX |
| spelling | doaj.art-5316969cb95147378e0dc20890aeed152022-12-21T18:19:34ZengElsevierMethodsX2215-01612015-01-012C14515310.1016/j.mex.2015.03.003Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer researchMarcus Celik Hansen0Line Nederby1Anne Roug2Palle Villesen3Eigil Kjeldsen4Charlotte Guldborg Nyvold5Peter Hokland6Department of Hematology, Aarhus University Hospital, Aarhus, DenmarkDepartment of Hematology, Aarhus University Hospital, Aarhus, DenmarkDepartment of Hematology, Aarhus University Hospital, Aarhus, DenmarkBioinformatics Research Centre, Aarhus University, DenmarkBioinformatics Research Centre, Aarhus University, DenmarkBioinformatics Research Centre, Aarhus University, DenmarkDepartment of Hematology, Aarhus University Hospital, Aarhus, DenmarkSequencing 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.http://www.sciencedirect.com/science/article/pii/S2215016115000175Extended variation annotation |
| spellingShingle | Marcus Celik Hansen Line Nederby Anne Roug Palle Villesen Eigil Kjeldsen Charlotte Guldborg Nyvold Peter Hokland Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research MethodsX Extended variation annotation |
| title | Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research |
| title_full | Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research |
| title_fullStr | Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research |
| title_full_unstemmed | Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research |
| title_short | Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research |
| title_sort | novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research |
| topic | Extended variation annotation |
| url | http://www.sciencedirect.com/science/article/pii/S2215016115000175 |
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