Work

Normalization methods in mass spectrometry-based analytical proteomics: A case study based on renal cell carcinoma datasets

Year: 2023

Type: article

Abstract: Normalization is a crucial step in proteomics data analysis as it enables data adjustment and enhances comparability between datasets by minimizing multiple sources of variability, such as sampling, sample handling, storage, treatment, and mass spectrometry measurements. In this study, we investigated different normalization methods, including Z-score normalization, median divide normalization, and quantile normalization, to evaluate their performance using a case study based on renal cell carcinoma datasets. Our results demonstrate that when comparing datasets by pairs, both the Z-score and quantile normalization methods consistently provide better results in terms of the number of proteins identified and quantified as well as in identifying statistically significant up or down-regulated proteins. However, when three or more datasets are compared at the same time the differences are found to be negligible.

Source: Talanta

DOI: 10.1016/j.talanta.2023.124953

Authors: Luis B. Carvalho, Pedro A.D. Teigas-Campos, Susana Jorge, Michele Protti, Laura Mercolini, Rajiv Dhir, Jacek R. Wiśniewski, Carlos Lodeiro, Hugo M. Santos, José L. Capelo

Institutions: LAQV Requimte, Associação Científica Proteomass, Laboratório de Análises LAQV-REQUIMTE, Universidade Nova de Lisboa, University of Bologna, University of Pittsburgh Medical Center, Max Planck Institute of Biochemistry, University of Pittsburgh

Language: English

Topic: Advanced Proteomics Techniques and Applications

Subfield: Spectroscopy

Field: Chemistry

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,940

Funders: University of Pittsburgh, Ministerio de Economía y Competitividad, Ministério da Ciência, Tecnologia e Ensino Superior, Proteomass Scientific Society, Laboratório Associado para a Química Verde, Fundação para a Ciência e a Tecnologia

Awards: Empowering personal health in bladder cancer patients by disclosing medical information hidden on complex urinary proteomes: diagnostic, prognostic and response to therapy, G1240268737, Laboratório Associado para a Química Verde - Tecnologias e Processos Limpos, Laboratório Associado para a Química Verde - Tecnologias e Processos Limpos, G2756637201, G2814222956, G4378797157, G5868090805, G6119126181, Deciphering the interplay of molecular alterations underpinning renal cell carcinoma by label-free mass spectrometry and clinical proteomics: A systems medicine approach for precision diagnosis, G6966134840, G8213652065, Laboratório Associado para a Química Verde - Tecnologias e Processos Limpos

OpenAlex ID: W4384564289

FWCI: 1.575

Cites: 34

Cited by: 18

Related to: 10