HTqPCR: high-throughput analysis and visualization of quantitative real-time PCR data in R
HTqPCR: high-throughput analysis and visualization of quantitative real-time PCR data in R
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DOI：
10.1093/bioinformatics/btp578
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发表时间：
2009-12-15
期刊：
影响因子：
5.8
通讯作者：
Bertone, Paul
中科院分区：
文献类型：
--
作者：
Dvinge, Heidi;Bertone, Paul
动机：定量实时聚合酶链式反应(QPCR)通常用于RNA表达谱分析、微阵列杂交数据验证和临床诊断分析。尽管在公共领域中有许多统计工具可用于分析微阵列实验，但对于定量聚合酶链式反应却不是这样。专利软件通常由仪器制造商提供，但这些解决方案不适用于多个化验的串联分析。当一项实验不仅仅涉及对照和处理样本之间的简单比较时，或者当许多qPCR数据集要在高通量设备中进行分析时，这是有问题的。结果：我们开发了一个用于R统计计算环境的软件包HTqPCR，可以跨多个条件和重复处理和分析qPCR数据。
Motivation: Quantitative real-time polymerase chain reaction (qPCR) is routinely used for RNA expression profiling, validation of microarray hybridization data and clinical diagnostic assays. Although numerous statistical tools are available in the public domain for the analysis of microarray experiments, this is not the case for qPCR. Proprietary software is typically provided by instrument manufacturers, but these solutions are not amenable to the tandem analysis of multiple assays. This is problematic when an experiment involves more than a simple comparison between a control and treatment sample, or when many qPCR datasets are to be analyzed in a high-throughput facility.Results: We have developed HTqPCR, a package for the R statistical computing environment, to enable the processing and analysis of qPCR data across multiple conditions and replicates.