pmartR: Quality Control and Statistics for Mass Spectrometry-Based Biological Data.
J Proteome Res
; 18(3): 1418-1425, 2019 03 01.
Article
em En
| MEDLINE
| ID: mdl-30638385
Prior to statistical analysis of mass spectrometry (MS) data, quality control (QC) of the identified biomolecule peak intensities is imperative for reducing process-based sources of variation and extreme biological outliers. Without this step, statistical results can be biased. Additionally, liquid chromatography-MS proteomics data present inherent challenges due to large amounts of missing data that require special consideration during statistical analysis. While a number of R packages exist to address these challenges individually, there is no single R package that addresses all of them. We present pmartR, an open-source R package, for QC (filtering and normalization), exploratory data analysis (EDA), visualization, and statistical analysis robust to missing data. Example analysis using proteomics data from a mouse study comparing smoke exposure to control demonstrates the core functionality of the package and highlights the capabilities for handling missing data. In particular, using a combined quantitative and qualitative statistical test, 19 proteins whose statistical significance would have been missed by a quantitative test alone were identified. The pmartR package provides a single software tool for QC, EDA, and statistical comparisons of MS data that is robust to missing data and includes numerous visualization capabilities.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Espectrometria de Massas
/
Proteínas
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Cromatografia Líquida
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Proteômica
Tipo de estudo:
Qualitative_research
Limite:
Animals
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article