Due to the limited precision of mass spectrometers the locations of the extracted peaks may vary from spectrum to spectrum. This, in turn, means that different spectra cannot be directly comparable. To circumvent the problem appropriate inter-sample alignment of the detected peaks is needed (a procedure often called peak alignment or peak clustering).

In this Tutorial we show how to use Binning analysis (available in the MALDI module) for grouping peaks into bins (peak clusters). It is assumed that peaks have been already extracted from raw MS data (see Step 2 of this Tutorial). The main idea of the Binning analysis is to group peaks of similar molecular weight across all spectra into bins while allowing for slight variations in mass.

After performing  Binning, all samples will have the exact same number of features (bins) at the exact same m/z areas. Hence, the Binning algorithm is a mandatory step if you want to prepare MS data for statistical analysis. In the Step 4 (the last step) of the Tutorial we will shown an example of the statistical analysis (i.e. PCA) performed on binned data.