Assessment of label-free quantification and missing value imputation for proteomics in non-human primates.

ABSTRACT:

Background

Reliable and effective label-free quantification (LFQ) analyses are dependent not only on the method of data acquisition in the mass spectrometer, but also on the downstream data processing, including software tools, query database, data normalization and imputation. In non-human primates (NHP), LFQ is challenging because the query databases for NHP are limited since the genomes of these species are not comprehensively annotated. This invariably results in limited discovery of proteins and associated Post Translational Modifications (PTMs) and a higher fraction of missing data points. While identification of fewer proteins and PTMs due to database limitations can negatively impact uncovering important and meaningful biological information, missing data also limits downst

SUBMITTER: Hamid Z 

PROVIDER: S-EPMC9264528 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature