Matrix eQTL: ultra fast eQTL analysis via large matrix operations
Matrix eQTL: ultra fast eQTL analysis via large matrix operations
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DOI：
10.1093/bioinformatics/bts163
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发表时间：
2012-05-15
期刊：
影响因子：
5.8
通讯作者：
Shabalin, Andrey A.
中科院分区：
文献类型：
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作者：
Shabalin, Andrey A.
结果：我们开发了一种新的计算效率高的eQTL分析软件，称为矩阵eQTL。在大数据集上的测试中，它比现有流行的QTL/eQTL分析工具快2-3个数量级，同时找到相同的eQTL。快速的性能是通过特殊的预处理和表达的大矩阵运算方面的算法的计算最密集的部分。矩阵eQTL支持具有协变量的加性线性和ANOVA模型，包括具有相关和异方差误差的模型。多重检验的问题通过计算错误发现率来解决;这可以针对顺式和反式eQTL单独进行。
Results: We have developed a new software for computationally efficient eQTL analysis called Matrix eQTL. In tests on large datasets, it was 2-3 orders of magnitude faster than existing popular tools for QTL/eQTL analysis, while finding the same eQTLs. The fast performance is achieved by special preprocessing and expressing the most computationally intensive part of the algorithm in terms of large matrix operations. Matrix eQTL supports additive linear and ANOVA models with covariates, including models with correlated and heteroskedastic errors. The issue of multiple testing is addressed by calculating false discovery rate; this can be done separately for cis- and trans-eQTLs.