Making Sense of LC-MS/MS Spectra – Part I

' Armel Nicolas

From lots of gibberish to useful data…

This post is destined to become the introduction of a new series of glorious blog entries on the subject of LC-MS/MS data analysis.

Still of Darth Vader


In this series we would like to talk about proteomics data analysis and the different steps it involves. The series will focus on the data type most non-specialist users are likely to have, namely Bottom-Up proteomics data acquired in Data Dependent Acquisition mode. The data may correspond to unlabelled samples, or to samples labelled with SILAC or isobaric labels (TMT or iTRAQ). As this series progresses, we may also touch on other types of proteomics data. We will focus on the theoretical steps of the analysis, but if we get around to it we may also add a tutorial for performing some analysis steps yourself.


Imagine you have recently sent samples to us or another proteomics service or facility, and have just received the results.  These may include a report on the analysis with results, tables of proteins and peptides as well as files containing all of the raw acquired spectra.

But… hey, you are a true scientist and you don’t like blackboxes : you must know how it works!


The aim of this series is to help you understand the different steps of the process that we need to get through to convert proteomics spectra into useful expression data. As this series progresses, we will go through:

  • A brief introduction to proteomics file formats and their contents.
  • The concept of features.
  • Strategies for identification of spectra. Control of the false discovery rate.
  • Quantitation. This will cover absolute and relative quantitation, and both labelled and label-free strategies.
  • Assembly of peptides into protein groups.
  • Data normalisation strategies available in different contexts.
  • … anything else we can think of adding to this list as the series progresses.
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