NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses.

ABSTRACT: Mass spectrometry (MS)-based quantitative proteomics experiments frequently generate data with missing values, which may profoundly affect downstream analyses. A wide variety of imputation methods have been established to deal with the missing-value issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics community. Herein, we developed a user-friendly and powerful stand-alone software, NAguideR, to enable implementation and evaluation of different missing value methods offered by 23 widely used missing-value imputation algorithms. NAguideR further evaluates data imputation results through classic computational criteria and, unprecedentedly, proteomic empirical criteria, such as quantitative consistency between differe

SUBMITTER: Wang S 

PROVIDER: S-EPMC7641313 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature