The CRAPome: A contaminant repository for affinity purification-mass spectrometry data

Dattatreya Mellacheruvu, Zachary Wright, Amber L. Couzens, Jean Philippe Lambert, Nicole A. St-Denis, Tuo Li, Yana V. Miteva, Simon Hauri, Mihaela E. Sardiu, Teck Yew Low, Vincentius A. Halim, Richard D. Bagshaw, Nina C. Hubner, Abdallah Al-Hakim, Annie Bouchard, Denis Faubert, Damian Fermin, Wade H. Dunham, Marilyn Goudreault, Zhen Yuan LinBeatriz Gonzalez Badillo, Tony Pawson, Daniel Durocher, Benoit Coulombe, Ruedi Aebersold, Giulio Superti-Furga, Jacques Colinge, Albert J.R. Heck, Hyungwon Choi, Matthias Gstaiger, Shabaz Mohammed, Ileana M. Cristea, Keiryn L. Bennett, Mike P. Washburn, Brian Raught, Rob M. Ewing, Anne Claude Gingras, Alexey I. Nesvizhskii

Research output: Contribution to journalArticlepeer-review

1077 Scopus citations


Affinity purification coupled with mass spectrometry (AP-MS) is a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (for example, proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. The standard approach is to identify nonspecific interactions using one or more negative-control purifications, but many small-scale AP-MS studies do not capture a complete, accurate background protein set when available controls are limited. Fortunately, negative controls are largely bait independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the contaminant repository for affinity purification (the CRAPome) and describe its use for scoring protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely accessible at

Original languageEnglish (US)
Pages (from-to)730-736
Number of pages7
JournalNature Methods
Issue number8
StatePublished - Aug 2013

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Biochemistry
  • Biotechnology
  • Cell Biology


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