Assessing Multiple Evidence Streams to Decide on Confidence for Identification of Post-Translational Modifications, within and Across Data Sets
Assessing Multiple Evidence Streams to Decide on Confidence for Identification of Post-Translational Modifications, within and Across Data Sets
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DOI：
10.1101/2022.12.15.520504
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发表时间：
2022-12
影响因子：
4.4
通讯作者：
O. Camacho;Kerry A Ramsbottom;Andrew Collins;A. Jones
中科院分区：
文献类型：
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作者：
O. Camacho;Kerry A Ramsbottom;Andrew Collins;A. Jones
磷酸化是一种翻译后修饰，由于其在许多生物过程中的相关性，引起了研究人员的极大兴趣。LC-MS/MS技术已经实现了高通量数据采集，研究声称鉴定和定位了数千个磷酸盐位点。磷酸盐的识别和定位来自不同的分析管道和评分算法，整个管道中嵌入了不确定性。对于许多管道和算法，使用任意阈值，但在这些研究中，对实际的全局错误定位率知之甚少。最近，有人建议使用诱饵氨基酸来估计磷酸化位点的全局错误定位率，其中报道的肽谱匹配。我们在这里描述了一个简单的管道，旨在最大限度地提高从这些研究中提取的信息，客观地从肽谱匹配到肽型位点水平，以及结合多项研究的结果，同时保持跟踪错误定位率。我们表明，该方法是更有效的比目前的过程中，使用一个更简单的机制来处理磷酸盐识别冗余内和跨研究。在我们使用8个水稻磷酸蛋白组学数据集的案例研究中，使用我们的诱饵方法自信地识别了6，368个独特位点，而使用传统阈值处理（其中错误定位率未知）识别了4，687个独特位点。
Phosphorylation is a post-translational modification of great interest to researchers due to its relevance in many biological processes. LC-MS/MS techniques have enabled high-throughput data acquisition with studies claiming identification and localisation of thousands of phosphosites. The identification and localisation of phosphosites emerge from different analytical pipelines and scoring algorithms, with uncertainty embedded throughout the pipeline. For many pipelines and algorithms, arbitrary thresholding is used, but little is known about the actual global false localisation rate in these studies. Recently, it has been suggested using decoy amino acids to estimate global false localisation rates of phosphosites, amongst the peptide-spectrum matches reported. We here describe a simple pipeline aiming to maximize the information extracted from these studies by objectively collapsing from peptide-spectrum match to peptidoform-site level, as well as combining findings from multiple studies while maintaining track of false localisation rates. We show that the approach is more effective than current processes that use a simpler mechanism for handling phosphosite identification redundancy within and across studies. In our case study using 8 rice phophoproteomics data sets, 6,368 unique sites were identified confidently identified using our decoy approach compared to 4,687 using traditional thresholding in which false localisation rates are unknown.