Improved label-free LC-MS analysis by wavelet-based noise rejection

Research output: Contribution to journalArticle


Label-free LC-MS analysis allows determining the differential expression level of proteins in multiple samples, without the use of stable isotopes. This technique is based on the direct comparison of multiple runs, obtained by continuous detection in MS mode. Only differentially expressed peptides are selected for further fragmentation, thus avoiding the bias toward abundant peptides typical of data-dependent tandem MS. The computational framework includes detection, alignment, normalization and matching of peaks across multiple sets, and several software packages are available to address these processing steps. Yet, more care should be taken to improve the quality of the LC-MS maps entering the pipeline, as this parameter severely affects the results of all downstream analyses. In this paper we show how the inclusion of a preprocessing step of background subtraction in a common laboratory pipeline can lead to an enhanced inclusion list of peptides selected for fragmentation and consequently to better protein identification.


  • Salvatore Cappadona
  • Paolo Nanni
  • Marco Benevento
  • Fredrik Levander
  • Pierra Versura
  • Aldo Roda
  • Sergio Cerutti
  • Linda Pattini
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Immunology in the medical area
Original languageEnglish
JournalJournal of Biomedicine and Biotechnology
Publication statusPublished - 2010
Publication categoryResearch