Department of Chemistry , University of British Columbia , Vancouver , British Columbia V6T 1Z1 , Canada.
Canada's Michael Smith Genome Sciences Centre , British Columbia Cancer Agency , Vancouver , British Columbia V5Z 1G1 , Canada.
J Proteome Res. 2018 Jun 1;17(6):2237-2247. doi: 10.1021/acs.jproteome.8b00072. Epub 2018 Apr 26.
Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the "raw" MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable parsing of raw MS files derived from Thermo Orbitrap instruments to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS, MS, and MS metadata as well as matrices of quantification values based on isobaric tagging approaches. In this study, the utility of RawQuant is demonstrated in several scenarios: (1) reanalysis of shotgun proteomics data for the identification of the human proteome, (2) reanalysis of experiments utilizing isobaric tagging for whole-proteome quantification, and (3) analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw Thermo Orbitrap MS files acquired in a range of common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets and suggests targetable areas to improve depth of coverage in identification-focused studies and quantification accuracy when using isobaric tags.
通过质谱（MS）对蛋白质样品进行有效分析需要仔细选择和优化一系列实验参数。作为主要检测设备的输出，“原始”MS 数据文件可用于评估给定样品分析的成功程度。然而，标准原始 MS 文件的闭源性质可能会使有效解析其中包含的数据变得复杂。为了简化并增加可能的分析范围，开发了 RawQuant 工具，以实现从 Thermo Orbitrap 仪器中解析原始 MS 文件，从而以可公开读取的文本格式生成元数据和扫描数据。可以命令 RawQuant 导出包含 MS、MS 和 MS 元数据的用户友好文件，以及基于等压标记方法的定量值矩阵。在这项研究中，展示了 RawQuant 在几种情况下的实用性：（1）重新分析用于鉴定人类蛋白质组的 shotgun 蛋白质组学数据，（2）重新分析利用等压标记进行全蛋白质组定量的实验，以及（3）分析新型细菌蛋白质组和合成肽混合物，以评估使用等压标签时的定量准确性。这些分析共同成功地证明了 RawQuant 可有效地解析和定量从各种常见蛋白质组学实验中获得的原始 Thermo Orbitrap MS 文件的数据。此外，使用 RawQuant 进行的个别分析突出了不同实验设置中的参数考虑因素，并提出了可改进以鉴定为重点的研究中覆盖深度和使用等压标签时定量准确性的靶向领域。
