{"title":"In response to \"On E-value for tandem MS scoring schemes\"","authors":"Jainab Khatun, Morgan C. Giddings","doi":"10.1093/bioinformatics/btn252","DOIUrl":null,"url":null,"abstract":"We thank Mark Segal for raising the issue of interpreting MS/MS scores. As he noted, we used a method proposed by Fenyo and Beavis (FB) (2003) to asses the significance of identification using HMM_Score. In his letter, Segal makes two basic assertions about this use: (1) that the extreme value distribution does not apply for the MS/MS database scoring systems used by FB and our HMM and (2) the linear tail fitting of the log survival function is not robust. He proposes a method that he authored as an alternative for estimating evd parameters that he says may be more robust, and also points to a method by Shen et al. that is specific to assessing significance of proteins/peptides identifications using MS/MS data. While it is valuable to examine whether there exist better ways of statistically interpreting the results of MS/MS search, in his letter, Segal did not provide any clear supporting evidence for his claim that the MS/MS scorers cannot use E-values. In our case, we calculate a score distribution for all random matches on-the-fly, then deriving the survival function, s, (the cumulative probability distribution) and finally, fitting a line to log of this function for the high-scoring portion of s. We verified the methodology for a series of randomly chosen HMM_Score search results, observing that in all cases, the fit had very high correlation values (R2 > 0.9). All subsequent validation of HMM_Score was performed using the E-values produced, and as reported the system performs well.","PeriodicalId":90576,"journal":{"name":"Journal of bioinformatics","volume":"1 1","pages":"1654"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btn252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We thank Mark Segal for raising the issue of interpreting MS/MS scores. As he noted, we used a method proposed by Fenyo and Beavis (FB) (2003) to asses the significance of identification using HMM_Score. In his letter, Segal makes two basic assertions about this use: (1) that the extreme value distribution does not apply for the MS/MS database scoring systems used by FB and our HMM and (2) the linear tail fitting of the log survival function is not robust. He proposes a method that he authored as an alternative for estimating evd parameters that he says may be more robust, and also points to a method by Shen et al. that is specific to assessing significance of proteins/peptides identifications using MS/MS data. While it is valuable to examine whether there exist better ways of statistically interpreting the results of MS/MS search, in his letter, Segal did not provide any clear supporting evidence for his claim that the MS/MS scorers cannot use E-values. In our case, we calculate a score distribution for all random matches on-the-fly, then deriving the survival function, s, (the cumulative probability distribution) and finally, fitting a line to log of this function for the high-scoring portion of s. We verified the methodology for a series of randomly chosen HMM_Score search results, observing that in all cases, the fit had very high correlation values (R2 > 0.9). All subsequent validation of HMM_Score was performed using the E-values produced, and as reported the system performs well.