Load and Preprocess
RAW data

Just load and go. For best results, and convenience, PEAKS provides algorithms for loading, refining and preprocessing RAW data. This first step in any analysis is critical; a poorly generated peaklist is a serious detriment to any further analysis. So it's best to start with RAW data and use PEAKS algorithms to prepare the data.

PEAKS' preprocessing algorithms are some of the best on the market. They have to be! Database search tools may be able to find a hit after removing 80% of the data, but a tool with a rich history in de novo sequencing requires a more fine grained level of detail.

Load in RAW data from most instruments directly into PEAKS, or use a standard data format [supported formats]. Then choose to:

• Merge Scans of the same peptide. The instrument can MS/MS the same peptide several times. Merging these scans means higher quality data. We use the retention time and precursor m/z value to avoid merging the wrong scans.
• Recalculate correct precursor charge. RAW data often contains incomplete or inaccurate charge information. But we can recalculate it carefully by examination of the survey scan (or in the case of ion-trap data, the MS/MS itself). It is an incorrect, but commonly used, approach to allow the search results to determine what the precursor charge was. This increases the search time and risk of false positive hits. Besides which, proper scientific method requires that the data determine the results, not vise-verse.
• Remove MS/MS scans that are of poor quality. A large percentage of MS/MS scans contain only noise. Removing these will speed up processing time, and reduce the risk of random false positive assignments.
• Preprocess within MS/MS scans
  • Baseline deduction noise filtering
  • Centroiding
  • Deconvolution