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Computational and statistical approaches to analyzing variants identified by exome sequencing
New sequencing technology has enabled the identification of thousands of single nucleotide polymorphisms in the exome, and many computational and statistical approaches to identify disease-association signals have emerged.
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2011
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3308043/ https://www.ncbi.nlm.nih.gov/pubmed/21920052 http://dx.doi.org/10.1186/gb-2011-12-9-227 |
| _version_ | 1782227383569350656 |
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| author | Stitziel, Nathan O Kiezun, Adam Sunyaev, Shamil |
| author_facet | Stitziel, Nathan O Kiezun, Adam Sunyaev, Shamil |
| author_sort | Stitziel, Nathan O |
| collection | PubMed |
| description | New sequencing technology has enabled the identification of thousands of single nucleotide polymorphisms in the exome, and many computational and statistical approaches to identify disease-association signals have emerged. |
| format | Online Article Text |
| id | pubmed-3308043 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2011 |
| publisher | BioMed Central |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-33080432012-09-14 Computational and statistical approaches to analyzing variants identified by exome sequencing Stitziel, Nathan O Kiezun, Adam Sunyaev, Shamil Genome Biol Review New sequencing technology has enabled the identification of thousands of single nucleotide polymorphisms in the exome, and many computational and statistical approaches to identify disease-association signals have emerged. BioMed Central 2011 2011-09-14 /pmc/articles/PMC3308043/ /pubmed/21920052 http://dx.doi.org/10.1186/gb-2011-12-9-227 Text en Copyright ©2011 BioMed Central Ltd. |
| spellingShingle | Review Stitziel, Nathan O Kiezun, Adam Sunyaev, Shamil Computational and statistical approaches to analyzing variants identified by exome sequencing |
| title | Computational and statistical approaches to analyzing variants identified by exome sequencing |
| title_full | Computational and statistical approaches to analyzing variants identified by exome sequencing |
| title_fullStr | Computational and statistical approaches to analyzing variants identified by exome sequencing |
| title_full_unstemmed | Computational and statistical approaches to analyzing variants identified by exome sequencing |
| title_short | Computational and statistical approaches to analyzing variants identified by exome sequencing |
| title_sort | computational and statistical approaches to analyzing variants identified by exome sequencing |
| topic | Review |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3308043/ https://www.ncbi.nlm.nih.gov/pubmed/21920052 http://dx.doi.org/10.1186/gb-2011-12-9-227 |
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