Evaluating False Transfer Rates from the Match-between-Runs Algorithm with a Two-Proteome Model
Evaluating False Transfer Rates from the Match-between-Runs Algorithm with a Two-Proteome Model
复制标题
DOI：
10.1021/acs.jproteome.9b00492
复制
发表时间：
2019-11-01
影响因子：
4.4
通讯作者：
Gygi, Steven P.
中科院分区：
文献类型：
--
作者：
Lim, Matthew Y.;Paulo, Joao A.;Gygi, Steven P.
独立LC-MS/MS运行之间的随机性在蛋白质组学领域中是一个具有挑战性的问题，导致显著的缺失值（即，丰度测量）。为了解决这个问题，已经开发了几种方法，包括计算方法，如MaxQuant的运行间匹配（MBR）算法。MBR通常会同时考虑几十次运行，将标识从任何一次运行转移到任何其他运行。为了评估与这些转移事件相关的错误，我们创建了一个双样本/双蛋白质组方法。以这种方式，评估不含酵母裂解物的样品（n = 20）是否从含酵母的样品（n = 20）转移了错误鉴定。虽然MBR将光谱鉴定的总数增加了约40%，但我们还发现，所有鉴定的酵母蛋白中有44%的鉴定转移到至少一个没有酵母的样品中。然而，在应用MaxQuant LFQ算法后，其中只有2.7%保留在最终数据集中。我们得出结论，MBR的错误传输是丰富的，但很少保留在最终的数据集。
Stochasticity between independent LC-MS/MS runs is a challenging problem in the field of proteomics, resulting in significant missing values (i.e., abundance measurements) among observed peptides. To address this issue, several approaches have been developed including computational methods such as MaxQuant's match-between-runs (MBR) algorithm. Often dozens of runs are all considered at once by MBR, transferring identifications from any one run to any of the others. To evaluate the error associated with these transfer events, we created a two-sample/two-proteome approach. In this way, samples containing no yeast lysate (n = 20) were assessed for false identification transfers from samples containing yeast (n = 20). While MBR increased the total number of spectral identifications by similar to 40%, we also found that 44% of all identified yeast proteins had identifications transferred to at least one sample without yeast. However, of these only 2.7% remained in the final data set after applying the MaxQuant LFQ algorithm. We conclude that false transfers by MBR are plentiful, but few are retained in the final data set.