Data analysis of assorted serum peptidome profiles

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.

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Figure 1: MSKCC data analysis pipeline for serum peptidomics.
Figure 2: Data folder structure and naming convention used by the MSKCC serum proteomics data analysis.
Figure 3: Parameter file for signal processing.
Figure 4: Qcealignf workflow.
Figure 5: Data import and interpretation for GeneSpring.
Figure 6: Unsupervised statistical analysis.
Figure 7: Supervised statistical analysis.
Figure 8: MSV.
Figure 9: Optimization of the singlet width.
Figure 10: Effects of the singlet-width parameter on ion intensity and resolution.
Figure 11: Effects of mass calibration and 'Entropycal'-based alignment on mass spectral overlays.
Figure 12

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Correspondence to Paul Tempst.

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Supplementary information

Supplementary Method 1

Mass Spectra Analysis (PDF 447 kb)

Supplementary Method 2

Customized macro to convert Bruker files to ascii files (ZIP 2 kb)

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Villanueva, J., Philip, J., DeNoyer, L. et al. Data analysis of assorted serum peptidome profiles. Nat Protoc 2, 588–602 (2007). https://doi.org/10.1038/nprot.2007.57

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