Data analysis of assorted serum peptidome profiles
- 29 March 2007
- journal article
- Published by Springer Nature in Nature Protocols
- Vol. 2 (3) , 588-602
- https://doi.org/10.1038/nprot.2007.57
Abstract
Discovery of biomarker patterns using proteomic techniques requires examination of large numbers of patient and control samples, followed by data mining of the molecular read-outs (e.g., mass spectra). Adequate signal processing and statistical analysis are critical for successful extraction of markers from these data sets. The protocol, specifically designed for use in conjunction with MALDI-TOF-MS-based serum peptide profiling, is a data analysis pipeline, starting with transfer of raw spectra that are interpreted using signal processing algorithms to define suitable features (i.e., peptides). We describe an algorithm for minimal entropy-based peak alignment across samples. Peak lists obtained in this way, and containing all samples, all peptide features and their normalized MS-ion intensities, can be evaluated, and results validated, using common statistical methods. We recommend visual inspection of the spectra to confirm all results, and have written freely available software for viewing and color-coding of spectral overlays.Keywords
This publication has 23 references indexed in Scilit:
- Robust Algorithm for Alignment of Liquid Chromatography−Mass Spectrometry Analyses in an Accurate Mass and Time Tag Data Analysis PipelineAnalytical Chemistry, 2006
- Advances and Challenges in Liquid Chromatography-Mass Spectrometry-based Proteomics Profiling for Clinical ApplicationsMolecular & Cellular Proteomics, 2006
- Automated serum peptide profilingNature Protocols, 2006
- Direct Tandem Mass Spectrometry Reveals Limitations in Protein Profiling Experiments for Plasma Biomarker DiscoveryJournal of Proteome Research, 2005
- Quantitative Proteomic Analysis by Accurate Mass Retention Time PairsAnalytical Chemistry, 2005
- In Vitro Biomarker Discovery for Atherosclerosis by ProteomicsMolecular & Cellular Proteomics, 2004
- Sample classification from protein mass spectrometry, by ‘peak probability contrasts’Bioinformatics, 2004
- A Tool To Visualize and Evaluate Data Obtained by Liquid Chromatography-Electrospray Ionization-Mass SpectrometryAnalytical Chemistry, 2004
- SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancerCurrent Opinion in Biotechnology, 2004
- Peer Reviewed: SELDI-TOF MS for Diagnostic ProteomicsAnalytical Chemistry, 2003