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Impact of the Identification Strategy on the Reproducibility of the DDA and DIA Results.


ABSTRACT: Data-independent acquisition (DIA) is a promising technique for the proteomic analysis of complex protein samples. A number of studies have claimed that DIA experiments are more reproducible than data-dependent acquisition (DDA), but these claims are unsubstantiated since different data analysis methods are used in the two methods. Data analysis in most DIA workflows depends on spectral library searches, whereas DDA typically employs sequence database searches. In this study, we examined the reproducibility of the DIA and DDA results using both sequence database and spectral library search. The comparison was first performed using a cell lysate and then extended to an interactome study. Protein overlap among the technical replicates in both DDA and DIA experiments was 30% higher with library-based identifications than with sequence database identifications. The reproducibility of quantification was also improved with library search compared to database search, with the mean of the coefficient of variation decreasing more than 30% and a reduction in the number of missing values of more than 35%. Our results show that regardless of the acquisition method, higher identification and quantification reproducibility is observed when library search was used.

SUBMITTER: Fernandez-Costa C 

PROVIDER: S-EPMC7898222 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Impact of the Identification Strategy on the Reproducibility of the DDA and DIA Results.

Fernández-Costa Carolina C   Martínez-Bartolomé Salvador S   McClatchy Daniel B DB   Saviola Anthony J AJ   Yu Nam-Kyung NK   Yates John R JR  

Journal of proteome research 20200619 8


Data-independent acquisition (DIA) is a promising technique for the proteomic analysis of complex protein samples. A number of studies have claimed that DIA experiments are more reproducible than data-dependent acquisition (DDA), but these claims are unsubstantiated since different data analysis methods are used in the two methods. Data analysis in most DIA workflows depends on spectral library searches, whereas DDA typically employs sequence database searches. In this study, we examined the rep  ...[more]

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