Consensus rules in variant detection from next-generation sequencing data.
A critical step in detecting variants from next-generation sequencing data is post hoc filtering of putative variants called or predicted by computational tools. Here, we highlight four critical parameters that could enhance the accuracy of called single nucleotide variants and insertions/deletions:...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2012-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3371040?pdf=render |
| _version_ | 1818476957235412992 |
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| author | Peilin Jia Fei Li Jufeng Xia Haiquan Chen Hongbin Ji William Pao Zhongming Zhao |
| author_facet | Peilin Jia Fei Li Jufeng Xia Haiquan Chen Hongbin Ji William Pao Zhongming Zhao |
| author_sort | Peilin Jia |
| collection | DOAJ |
| description | A critical step in detecting variants from next-generation sequencing data is post hoc filtering of putative variants called or predicted by computational tools. Here, we highlight four critical parameters that could enhance the accuracy of called single nucleotide variants and insertions/deletions: quality and deepness, refinement and improvement of initial mapping, allele/strand balance, and examination of spurious genes. Use of these sequence features appropriately in variant filtering could greatly improve validation rates, thereby saving time and costs in next-generation sequencing projects. |
| first_indexed | 2024-12-10T09:31:58Z |
| format | Article |
| id | doaj.art-d76a254535dd4708b12c9c98e35aa639 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-10T09:31:58Z |
| publishDate | 2012-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-d76a254535dd4708b12c9c98e35aa6392022-12-22T01:54:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0176e3847010.1371/journal.pone.0038470Consensus rules in variant detection from next-generation sequencing data.Peilin JiaFei LiJufeng XiaHaiquan ChenHongbin JiWilliam PaoZhongming ZhaoA critical step in detecting variants from next-generation sequencing data is post hoc filtering of putative variants called or predicted by computational tools. Here, we highlight four critical parameters that could enhance the accuracy of called single nucleotide variants and insertions/deletions: quality and deepness, refinement and improvement of initial mapping, allele/strand balance, and examination of spurious genes. Use of these sequence features appropriately in variant filtering could greatly improve validation rates, thereby saving time and costs in next-generation sequencing projects.http://europepmc.org/articles/PMC3371040?pdf=render |
| spellingShingle | Peilin Jia Fei Li Jufeng Xia Haiquan Chen Hongbin Ji William Pao Zhongming Zhao Consensus rules in variant detection from next-generation sequencing data. PLoS ONE |
| title | Consensus rules in variant detection from next-generation sequencing data. |
| title_full | Consensus rules in variant detection from next-generation sequencing data. |
| title_fullStr | Consensus rules in variant detection from next-generation sequencing data. |
| title_full_unstemmed | Consensus rules in variant detection from next-generation sequencing data. |
| title_short | Consensus rules in variant detection from next-generation sequencing data. |
| title_sort | consensus rules in variant detection from next generation sequencing data |
| url | http://europepmc.org/articles/PMC3371040?pdf=render |
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