A systematic strategy for large-scale analysis of genotype phenotype correlations: identification of candidate genes involved in African trypanosomiasis.
A systematic strategy for large-scale analysis of genotype phenotype correlations: identification of candidate genes involved in African trypanosomiasis.
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DOI：
10.1093/nar/gkm623
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发表时间：
2007
影响因子：
14.9
通讯作者：
Brass A
中科院分区：
文献类型：
--
作者：
Fisher P;Hedeler C;Wolstencroft K;Hulme H;Noyes H;Kemp S;Stevens R;Brass A
将微阵列和定量性状基因座数据结合在一起，以帮助搜索负责表型变化的候选基因。在本文中，我们强调了微阵列的手动分析和QTL数据，以发现复杂表型的候选基因。在结果中对非洲锥虫病的抗性。在DAXX – P53蛋白质结合区域中，这支持了最近的实验证据，表明凋亡可能在锥虫病耐药性表型中发挥作用。 http://workflows.mygrid.org.uk/repository/mygrid/paulfisher/。
It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. In this article, we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes. We show how automated approaches provide a systematic means to investigate genotype–phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region. Subsequent re-sequencing in Daxx identified a deletion of an amino acid, identified in susceptible mouse strains, in the Daxx–p53 protein-binding region. This supports recent experimental evidence that apoptosis could be playing a role in the trypanosomiasis resistance phenotype. Workflows developed in this investigation, including a guide to loading and executing them with example data, are available at http://workflows.mygrid.org.uk/repository/myGrid/PaulFisher/.
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影响因子：
2.4
作者：
Schadt, E E
通讯作者：
Schadt, E E
DOI：
10.1073/pnas.1232392100
发表时间：
2003-06-24
影响因子：
11.1
作者：
Hanotte, O;Ronin, Y;Teale, A
通讯作者：
Teale, A
影响因子：
2.1
作者：
Irizarry, RA;Hobbs, B;Speed, TP
通讯作者：
Speed, TP
影响因子：
14.9
作者：
Maglott, Donna;Ostell, Jim;Pruitt, Kim D;Tatusova, Tatiana
通讯作者：
Tatusova, Tatiana
影响因子：
5.8
作者：
Oinn, T;Addis, M;Li, P
通讯作者：
Li, P