apQuant: Accurate Label-Free Quantification by Quality Filtering
apQuant: Accurate Label-Free Quantification by Quality Filtering
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DOI：
10.1021/acs.jproteome.8b00113
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发表时间：
2019-01-01
影响因子：
4.4
通讯作者：
Duernberger, Gerhard
中科院分区：
文献类型：
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作者：
Doblmann, Johannes;Dusberger, Frederico;Duernberger, Gerhard
鸟枪法蛋白质组学数据的无标记定量是一种常用的策略，提供高动态范围，灵敏度和比较大量样品的能力，而无需额外的标记工作。在这里，我们提出了一种生物信息学方法，显着提高无标记的定量结果。我们采用Percolator来评估定量肽的质量。这允许基于错误发现率提取准确和可靠的定量结果。根据之前发布的公共数据对我们的方法进行基准测试表明，它的性能大大优于当前可用的算法。apQuant作为Proteome Discoverer的节点免费提供。
Label-free quantification of shotgun proteomics data is a frequently used strategy, offering high dynamic range, sensitivity, and the ability to compare a high number of samples without additional labeling effort. Here, we present a bioinformatics approach that significantly improves label-free quantification results. We employ Percolator to assess the quality of quantified peptides. This allows to extract accurate and reliable quantitative results based on false discovery rate. Benchmarking our approach on previously published public data shows that it considerably outperforms currently available algorithms. apQuant is available free of charge as a node for Proteome Discoverer.