GTB - an online genome tolerance browser.

GTB - an online genome tolerance browser.
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DOI:
10.1186/s12859-016-1436-4
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发表时间:
2017-01-06
期刊:
影响因子:
3
通讯作者:
Gaunt TR
Gaunt TR
中科院分区:
生物学4区
文献类型:
--
作者:
Shihab HA;Rogers MF;Ferlaino M;Campbell C;Gaunt TR

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能够预测单核苷酸变异 (SNV) 影响的准确方法变得越来越重要。存在大量的计算机算法,旨在帮助识别人类基因组中的 SNV 并对其进行优先级排序,以供进一步研究。然而,没有工具可以可视化基因组对突变的预测耐受性或这些方法之间的相似性。我们推出了基因组耐受性浏览器(GTB,http://gtb.biocompute.org.uk):一种在线基因组浏览器,用于可视化基因组对突变的预测耐受性。该服务器总结了几种计算机预测算法和保守分数:包括 13 种全基因组预测算法和保守分数、12 种非同义预测算法和 4 种癌症特定算法。 GTB 使用户能够可视化几种预测算法之间的异同,并上传自己的数据作为附加轨迹;从而促进快速识别潜在的感兴趣区域。本文的在线版本 (doi:10.1186/s12859-016-1436-4) 包含补充材料,可供授权用户使用。
Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation. However, no tool exists to visualize the predicted tolerance of the genome to mutation, or the similarities between these methods. We present the Genome Tolerance Browser (GTB, http://gtb.biocompute.org.uk): an online genome browser for visualizing the predicted tolerance of the genome to mutation. The server summarizes several in silico prediction algorithms and conservation scores: including 13 genome-wide prediction algorithms and conservation scores, 12 non-synonymous prediction algorithms and four cancer-specific algorithms. The GTB enables users to visualize the similarities and differences between several prediction algorithms and to upload their own data as additional tracks; thereby facilitating the rapid identification of potential regions of interest. The online version of this article (doi:10.1186/s12859-016-1436-4) contains supplementary material, which is available to authorized users.
来自1,092个人基因组的遗传变异的综合图。
DOI: 10.1038/nature11632
发表时间: 2012-11-01
期刊: Nature
影响因子: 64.8
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期刊: HUMAN MUTATION
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发表时间: 2001-05-01
期刊: GENOME RESEARCH
影响因子: 7
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DOI: 10.1186/gm390
发表时间: 2012
期刊: Genome medicine
影响因子: 12.3
作者:
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通讯作者: Lopez-Bigas N