literature.md

Suggested methods to merge data

Different strategies have been suggested for forming representative spectra. Frank et al. (JPR 2008) list five strategies, where one selects the representative spectrum to be:

• The "best spectrum”: the spectrum that maximizes a certain score, e.g., percent of explained intensity or percent of explained b/y ions.
• The “consensus spectrum”: a virtual spectrum constructed by averaging all spectra in the cluster. (Tabb et al. JASMS 2005)
• The “most similar spectrum”: the spectrum that has the highest average similarity to the other cluster members (Tabb et al. Anal Chem 2003).
• The “de novo spectrum”: the spectrum that has the highest score when submitted to de novo sequencing.
• The random spectrum: a spectrum chosen from the cluster at random.

Tools that generate spectra libraries and the corresponding spectrum merge strategy

• Skyline BiblioSpec - Best Spectrum in Cluster .
• spectra-cluster (PRIDE) - Consensus spectrum.
• SpectraST - Consensus cluster.
• NIST - Consensus spectra

Benchmarking datasets

Proteome tool's publication Zolg et al. We have extracted a subset of this set to a google drive.

References

• Frank et al. (JPR 2008)
• Wang et al. (bioRxiv_2018)
• Saeed et al. (Trans Comput Biol Bioinform 2014)
• Griss et al. (Nat Methods 2013), see supplementary material
• Perez‐Riverol et al.(Proteomics 2018)
• Denoising Peptide Tandem Mass Spectra for Spectral Libraries: A Bayesian Approach