ALL-P is a statistical framework based on a hierarchical modeling that takes into account shared peptide information for estimating protein abundances. ALL-P performs a simultaneous analysis of all the quantified peptides, handling the biological and technical errors as well as the peptide effect.
Compared to a method based on the analysis of one protein at a time that does not include shared peptides (ONE-P method), ALL-P proved to be far more reliable for estimating protein abundances and testing abundance changes.

ALL-P is described in: Blein-Nicolas M., Xu H., de Vienne D., Giraud C., Huet S., Zivy, M. (2012) Including shared peptides for estimating protein abundances: a significant improvement for quantitative proteomics. Proteomics.12 2797–2801 .

The source codes of ALL-P and ONE-P can be downloaded from the source code page. They can be easily reproduced and adapted to other experimental designs.

Try the ALL-P procedure! Go to the demo page