Bioinformatics · 2025 · 15 citations · 14 references
Life SciencesBioinformaticsBiostatisticsComputational BiologyProteomicsProteomics InformaticsBottom-up ProteomicsMass Spectrometry Data AnalysisMass Spectrometry-based ProteomicsBioinformatics In ProteomicsData Analysis AlgorithmsData Stream MiningData Stream ModelProteomic Data AnalysisRelative Protein QuantificationRelative QuantificationTop-down Proteomics Workflows
SUMMARY: Proteome studies frequently encounter challenges in down-stream data analysis due to limited bioinformatics resources, rapid data generation, and variations in analytical methods. To address these issues, we developed SpectroPipeR, an R package designed to streamline data analysis tasks and provide a comprehensive, standardized pipeline for Spectronaut® DIA-MS data. This novel package automates various analytical processes, including XIC plots, ID rate summary, normalization, batch and covariate adjustment, relative protein quantification, multivariate analysis, and statistical analysis, while generating interactive HTML reports for e.g. ELN systems. AVAILABILITY AND IMPLEMENTATION: The SpectroPipeR package (manual: https://stemicha.github.io/SpectroPipeR/) was written in R and is freely available on GitHub (https://github.com/stemicha/SpectroPipeR).
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Global quantification of mammalian gene expression control
Björn Schwanhäußer, Dorothea Busse, Na Li et al. · Nature · 2011 · 6.9K citations
Roland Bruderer, Oliver M. Bernhardt, Tejas Gandhi et al. · Molecular & Cellular Proteomics · 2015 · 1.3K citations · Full text