A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data
High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the var...
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| Format: | Article |
| Language: | English |
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BioMed Central
2013-12-01
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| Series: | Genomics & Informatics |
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| Online Access: | http://genominfo.org/upload/pdf/gni-11-191.pdf |
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| author | Shuoguo Wang Jinchuan Xing |
| author_facet | Shuoguo Wang Jinchuan Xing |
| author_sort | Shuoguo Wang |
| collection | DOAJ |
| description | High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification. |
| format | Article |
| id | doaj-art-338c1d6df727414485b75642a790a9e6 |
| institution | Kabale University |
| issn | 1598-866X 2234-0742 |
| language | English |
| publishDate | 2013-12-01 |
| publisher | BioMed Central |
| record_format | Article |
| series | Genomics & Informatics |
| spelling | doaj-art-338c1d6df727414485b75642a790a9e62025-02-03T02:40:44ZengBioMed CentralGenomics & Informatics1598-866X2234-07422013-12-0111419119910.5808/GI.2013.11.4.19161A Primer for Disease Gene Prioritization Using Next-Generation Sequencing DataShuoguo Wang0Jinchuan Xing1Department of Genetics, The State University of New Jersey, Piscataway, NJ 08854, USA.Department of Genetics, The State University of New Jersey, Piscataway, NJ 08854, USA.High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification.http://genominfo.org/upload/pdf/gni-11-191.pdfdisease gene prioritizationhigh-throughput DNA sequencinghuman genomesequence alignmentvariant discovery |
| spellingShingle | Shuoguo Wang Jinchuan Xing A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data Genomics & Informatics disease gene prioritization high-throughput DNA sequencing human genome sequence alignment variant discovery |
| title | A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data |
| title_full | A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data |
| title_fullStr | A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data |
| title_full_unstemmed | A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data |
| title_short | A Primer for Disease Gene Prioritization Using Next-Generation Sequencing Data |
| title_sort | primer for disease gene prioritization using next generation sequencing data |
| topic | disease gene prioritization high-throughput DNA sequencing human genome sequence alignment variant discovery |
| url | http://genominfo.org/upload/pdf/gni-11-191.pdf |
| work_keys_str_mv | AT shuoguowang aprimerfordiseasegeneprioritizationusingnextgenerationsequencingdata AT jinchuanxing aprimerfordiseasegeneprioritizationusingnextgenerationsequencingdata AT shuoguowang primerfordiseasegeneprioritizationusingnextgenerationsequencingdata AT jinchuanxing primerfordiseasegeneprioritizationusingnextgenerationsequencingdata |