SAINT: probabilistic scoring of affinity purification–mass spectrometry data
Open accessAbstract
We present 'significance analysis of interactome' (SAINT), a computational tool that assigns confidence scores to protein-protein interaction data generated using affinity purification-mass spectrometry (AP-MS). The method uses label-free quantitative data and constructs separate distributions for true and false interactions to derive the probability of a bona fide protein-protein interaction. We show that SAINT is applicable to data of different scales and protein connectivity and allows transparent analysis of AP-MS data.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The SAINT scoring algorithm models protein spectral counts between experimental and control affinity purifications.
“we have used the Significance Analysis of INTeractome (SAINT) scoring algorithm (90), which models protein spectral counts between experimental and control affinity purifications (Figure 2)”
From The Impact of Mass Spectrometry–Based Proteomics on Fundamental Discoveries in Virology (2014) · cites this paper as [90]
Control selection is essential for judging the specificity of viral-host protein interactions identified.
“The selection of controls is critical for assessing the specificity of the identified viral–host protein interactions.”
From Proteomic approaches to uncovering virus–host protein interactions during the progression of viral infection (2016) · cites this paper as [28]
The comparison of the proteins identified in the bait and control isolations can be performed using label-free approaches, such as comparing spectral counts or precursor ion intensities obtained from LC-MS analyses.
“The comparison of the proteins identified in the bait and control isolations can be performed using label-free approaches, such as comparing spectral counts or precursor ion intensities obtained from LC–MS analyses [28].”
From Proteomic approaches to uncovering virus–host protein interactions during the progression of viral infection (2016) · cites this paper as [28]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Eng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484 · see citing works
Antimicrobial Autophagy: A Conserved Innate Immune Response in Drosophila
Moy, R. H., & Cherry, S. R. (2013) · Journal of Innate Immunity · doi:10.1159/000350326 · Cited by 3,549 · see citing works
Global landscape of protein complexes in the yeast Saccharomyces cerevisiae
Krogan, N. J., Cagney, G., Yu, H., Zhong, G., Guo, X., Ignatchenko, A., Li, J., Pu, S., Datta, N., Tikuisis, A., et al. (2006) · Nature · doi:10.1038/nature04670 · Cited by 2,915 · see citing works
Proteome survey reveals modularity of the yeast cell machinery
Gavin, A., Aloy, P., Grandi, P., Krause, R., Böesche, M., Marzioch, M., Rau, C., Jensen, L. J., Bastuck, S., Dümpelfeld, B., et al. (2006) · Nature · doi:10.1038/nature04532 · Cited by 2,544 · see citing works
Network organization of the human autophagy system
Behrends, C., Sowa, M. E., Gygi, S. P., & Harper, J. W. (2010) · Nature · doi:10.1038/nature09204 · Cited by 1,554 · see citing works
Gibbs Sampling Methods for Stick-Breaking Priors
Ishwaran, H., & James, L. F. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501750332758 · Cited by 1,553 · see citing works
Defining the Human Deubiquitinating Enzyme Interaction Landscape
Sowa, M. E., Bennett, E. J., Gygi, S. P., & Harper, J. W. (2009) · Cell · doi:10.1016/j.cell.2009.04.042 · Cited by 1,512 · see citing works
Large‐scale mapping of human protein–protein interactions by mass spectrometry
Ewing, R. M., Chu, P. C., Elisma, F., Li, H., Taylor, P. P., Climie, S. C., McBroom, L. D. B., Robinson, M. D., O'Connor, L., Li, M. M., et al. (2007) · Molecular Systems Biology · doi:10.1038/msb4100134 · Cited by 985 · see citing works
The BioGRID Interaction Database: 2008 update
Breitkreutz, B., Stark, C., Reguly, T., Boucher, L., Breitkreutz, A., Livstone, M. S., Oughtred, R., Lackner, D. H., Bähler, J., Wood, V., et al. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm1001 · Cited by 698 · see citing works
Self-citationA Global Protein Kinase and Phosphatase Interaction Network in Yeast
Breitkreutz, A., Choi, H., Sharom, J. R., Boucher, L., Neduva, V., Larsen, B. G., Lin, Z., Breitkreutz, B., Stark, C., Liu, G., et al. (2010) · Science · doi:10.1126/science.1176495 · Cited by 686 · see citing works
Self-citationAnalysis and validation of proteomic data generated by tandem mass spectrometry
Nesvizhskii, A. I., Vitek, O., & Aebersold, R. H. (2007) · Nature Methods · doi:10.1038/nmeth1088 · Cited by 629 · see citing works
Self-citationJerónimo, C., Forget, D., Bouchard, A., Li, Q., Chua, G., Poitras, C., Thérien, C., Bergeron, D., Bourassa, S., Greenblatt, J., et al. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.06.027 · Cited by 444 · see citing works
Quantitative proteomics combined with BAC TransgeneOmics reveals in vivo protein interactions
Hubner, N. C., Bird, A. W., Cox, J., Splettstoesser, B., Bandilla, P., Poser, I., Hyman, A., & Mann, M. (2010) · Journal of Cell Biology · doi:10.1083/jcb.200911091 · Cited by 440 · see citing works
Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis
Griffin, N. M., Yu, J., Long, F., Oh, P., Shore, S., Li, Y., Koziol, J., & Schnitzer, J. E. (2009) · Nature Biotechnology · doi:10.1038/nbt.1592 · Cited by 400 · see citing works
Probabilistic assembly of human protein interaction networks from label-free quantitative proteomics
Sardiu, M. E., Cai, Y., Jin, J., Swanson, S. K., Conaway, R. C., Conaway, J. W., Florens, L., & Washburn, M. P. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0706983105 · Cited by 226 · see citing works
iRefWeb: interactive analysis of consolidated protein interaction data and their supporting evidence
Turner, B., Razick, S., Turinsky, A. L., Vlasblom, J., Crowdy, E., Cho, E., Morrison, K., Donaldson, I. M., & Wodak, S. J. (2010) · Database · doi:10.1093/database/baq023 · Cited by 207 · see citing works
Rinner, O., Mueller, L. N., Hubálek, M., Müller, M., Gstaiger, M., & Aebersold, R. H. (2007) · Nature Biotechnology · doi:10.1038/nbt1289 · Cited by 162 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- [9]Muller P Parmigiani G Rice K Bernardo JM Bayesian Statistics 8 Oxford Univ. Press 2007
- [12]Turner B Database (Oxford) 2010 baq023 2010
Cited by
Sorted by citations
The CRAPome: a contaminant repository for affinity purification–mass spectrometry data
Mellacheruvu, D., Wright, Z., Couzens, A. L., Lambert, J.-P., St-Denis, N. A., Li, T., Miteva, Y. V., Hauri, S., Sardiu, M. E., Low, T. Y., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2557 · Cited by 1,686 · see citing works
Self-citationGlobal landscape of HIV–human protein complexes
Jäger, S., Cimermancic, P., Gulbahce, N., Johnson, J. R., McGovern, K. E., Clarke, S. C., Shales, M., Mercenne, G., Pache, L., Li, K., et al. (2012) · Nature · doi:10.1038/nature10719 · Cited by 731 · see citing works
SLC38A9 is a component of the lysosomal amino acid sensing machinery that controls mTORC1
Rebsamen, M., Pochini, L., Stasyk, T., de Araújo, M. E. G., Galluccio, M., Kandasamy, R. K., Snijder, B., Fauster, A., Rudashevskaya, E. L., Bruckner, M., et al. (2015) · Nature · doi:10.1038/nature14107 · Cited by 673 · see citing works
A Dynamic Protein Interaction Landscape of the Human Centrosome-Cilium Interface
Gupta, G. D., Coyaud, É., Gonçalves, J., Mojarad, B. A., Liu, Y., Wu, Q., Gheiratmand, L., Comartin, D., Tkach, J. M., Cheung, S. W. T., et al. (2015) · Cell · doi:10.1016/j.cell.2015.10.065 · Cited by 538 · see citing works
Self-citationSirtuin 4 is a lipoamidase regulating pyruvate dehydrogenase complex activity
Mathias, R. A., Greco, T. M., Oberstein, A., Budayeva, H. G., Chakrabarti, R., Rowland, E. A., Kang, Y., Shenk, T., & Cristea, I. M. (2014) · Cell · doi:10.1016/j.cell.2014.11.046 · Cited by 430 · see citing works
Affinity-purification coupled to mass spectrometry: basic principles and strategies
Dunham, W. H., Mullin, M., & Gingras, A. (2012) · PROTEOMICS · doi:10.1002/pmic.201100523 · Cited by 368 · see citing works
Franjic, D., Skarica, M., Ma, S., Arellano, J. I., Tebbenkamp, A. T. N., Choi, J., Xu, C., Li, Q., Morozov, Y. M., Andrijevic, D., et al. (2022) · Neuron · doi:10.1016/j.neuron.2021.10.036 · Cited by 308 · see citing works
The functional interactome landscape of the human histone deacetylase family
Joshi, P., Greco, T. M., Guise, A. J., Luo, Y., Yu, F., Nesvizhskii, A. I., & Cristea, I. M. (2013) · Molecular Systems Biology · doi:10.1038/msb.2013.26 · Cited by 289 · see citing works
Self-citationThe Functional Proximal Proteome of Oncogenic Ras Includes mTORC2
Kovalski, J. R., Bhaduri, A., Zehnder, A. M., Neela, P. H., Che, Y., Wozniak, G. G., & Khavari, P. A. (2019) · Molecular Cell · doi:10.1016/j.molcel.2018.12.001 · Cited by 154 · see citing works
Heme drives hemolysis-induced susceptibility to infection via disruption of phagocyte functions
Martins, R., Maier, J., Gorki, A.-D., Huber, K. V. M., Sharif, O., Starkl, P., Saluzzo, S., Quattrone, F., Gawish, R., Lakovits, K., et al. (2016) · Nature Immunology · doi:10.1038/ni.3590 · Cited by 142 · see citing works
Boxer, L. D., Barajas, B., Tao, S., Zhang, J., & Khavari, P. A. (2014) · Genes & Development · doi:10.1101/gad.246579.114 · Cited by 147 · see citing works
Identification of Protein Interactions Involved in Cellular Signaling
Westermarck, J., Ivaska, J., & Corthals, G. L. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r113.027771 · Cited by 143 · see citing works
BioID identifies novel c-MYC interacting partners in cultured cells and xenograft tumors
Dingar, D., Kalkat, M., Chan, P.-K., Srikumar, T., Bailey, S. D., Tu, W. B., Coyaud, E., Ponzielli, R., Kolyar, M., Jurisica, I., et al. (2015) · Journal of Proteomics · doi:10.1016/j.jprot.2014.09.029 · Cited by 131 · see citing works
TBL1XR1 mutations drive extranodal lymphoma by inducing a pro-tumorigenic memory fate
Venturutti, L., Teater, M., Zhai, A., Chadburn, A., Babiker, L., Kim, D., Béguelin, W., Lee, T. C., Kim, Y., Chin, C. R., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.049 · Cited by 127 · see citing works
Lum, K. K., & Cristea, I. M. (2016) · Expert Review of Proteomics · doi:10.1586/14789450.2016.1147353 · Cited by 113 · see citing works
Miteva, Y. V., Budayeva, H. G., & Cristea, I. M. (2013) · Analytical Chemistry · doi:10.1021/ac3033257 · Cited by 105 · see citing works
A Key Role for the Ubiquitin Ligase UBR4 in Myofiber Hypertrophy in Drosophila and Mice
Hunt, L. C., Stover, J., Haugen, B., Shaw, T. I., Li, Y., Pagala, V. R., Finkelstein, D., Barton, E. R., Fan, Y., Labelle, M., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.06.094 · Cited by 90 · see citing works
Dual action antifungal small molecule modulates multidrug efflux and TOR signaling
Shekhar-Guturja, T., Gunaherath, G. M. K. B., Wijeratne, E. M. K., Lambert, J.-P., Averette, A. F., Lee, S. C., Kim, T., Bahn, Y.-S., Tripodi, F., Ammar, R., et al. (2016) · Nature Chemical Biology · doi:10.1038/nchembio.2165 · Cited by 101 · see citing works
Self-citationDiner, B. A., Lum, K. K., Javitt, A., & Cristea, I. M. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.047068 · Cited by 93 · see citing works
Mathias, R. A., Guise, A. J., & Cristea, I. M. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o114.046565 · Cited by 93 · see citing works
PIKES Analysis Reveals Response to Degraders and Key Regulatory Mechanisms of the CRL4 Network
Reichermeier, K. M., Straube, R., Reitsma, J. M., Sweredoski, M. J., Rose, C. M., Moradian, A., den Besten, W., Hinkle, T., Verschueren, E., Petzold, G., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2019.12.013 · Cited by 78 · see citing works
The Impact of Mass Spectrometry–Based Proteomics on Fundamental Discoveries in Virology
Greco, T. M., Diner, B. A., & Cristea, I. M. (2014) · Annual Review of Virology · doi:10.1146/annurev-virology-031413-085527 · Cited by 67 · see citing works
Zhang, C., Robinson, B. S., Xu, W., Yang, L., Yao, B., Zhao, H., Byun, P. K., Jin, P., Veraksa, A., & Moberg, K. H. (2015) · Developmental Cell · doi:10.1016/j.devcel.2015.05.010 · Cited by 70 · see citing works
Choi, H., Glatter, T., Gstaiger, M., & Nesvizhskii, A. I. (2012) · Journal of Proteome Research · doi:10.1021/pr201185r · Cited by 68 · see citing works
Self-citationXie, J. L., Qin, L., Miao, Z., Grys, B. T., Diaz, J. D. L. C., Ting, K., Krieger, J. R., Tong, J., Tan, K., Leach, M. D., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00547-y · Cited by 60 · see citing works
Network Analysis Identifies Mitochondrial Regulation of Epidermal Differentiation by MPZL3 and FDXR
Bhaduri, A., Ungewickell, A., Boxer, L. D., Lopez-Pajares, V., Zarnegar, B. J., & Khavari, P. A. (2015) · Developmental Cell · doi:10.1016/j.devcel.2015.10.023 · Cited by 60 · see citing works
O’Meara, T. R., O’Meara, M. J., Polvi, E. J., Pourhaghighi, M. R., Liston, S. D., Lin, Z.-Y., Veri, A. O., Emili, A., Gingras, A.-C., & Cowen, L. E. (2019) · PLoS Biology · doi:10.1371/journal.pbio.3000358 · Cited by 49 · see citing works
Self-citationHistone Deacetylases in Herpesvirus Replication and Virus-Stimulated Host Defense
Guise, A., Budayeva, H., Diner, B., & Cristea, I. (2013) · Viruses · doi:10.3390/v5071607 · Cited by 43 · see citing works
Lin, A. E., Greco, T. M., Döhner, K., Sodeik, B., & Cristea, I. M. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.030866 · Cited by 38 · see citing works
Nishimura, T., Fakim, H., Brandmann, T., Youn, J.-Y., Gingras, A.-C., Jinek, M., & Fabian, M. R. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1011 · Cited by 31 · see citing works
Self-citationGingras, A.-C., & Raught, B. (2012) · FEBS Letters · doi:10.1016/j.febslet.2012.03.065 · Cited by 34 · see citing works
Self-citationDiscovery of Host–Viral Protein Complexes During Infection
Rowles, D. L., Terhune, S. S., & Cristea, I. M. (2013) · Methods in Molecular Biology · doi:10.1007/978-1-62703-601-6_4 · Cited by 15 · see citing works
- Authors
- Choi, H., Larsen, B., Lin, Z.-Y., Breitkreutz, A., Mellacheruvu, D., Fermin, D., Qin, Z. S., Tyers, M., Gingras, A.-C., & Nesvizhskii, A. I.
- Affiliations
- University of Michigan (US)
- Lunenfeld-Tanenbaum Research Institute (CA)
- University of Toronto (CA)
- Corresponding author
- Gingras, Anne-Claude
- Nesvizhskii, Alexey I
- ORCID
- Venue
- Nature Methods
- Published
- 2010-12-05
- Volume
- 8
- Issue
- 1
- Pages
- 70-73
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC3064265
- OpenAlex
- W2047077861
- Cited by
- 800
- References
- 17
- Citations by year
- 2026: 37 · 2025: 54 · 2024: 56 · 2023: 59 · 2022: 62 · 2021: 68 · 2020: 66 · 2019: 64 · 2018: 50 · 2017: 59 · 2016: 47 · 2015: 57 · 2014: 43 · 2013: 34 · 2012: 29
- FWCI
- 11.46
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Canadian Institutes of Health Research (MOP 84314, MOP-12246)
- National Cancer Institute (R01CA126239)
- National Institute of General Medical Sciences (R01GM094231)
- National Center for Research Resources (R01RR024031)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Biotin and Related Studies
- Keywords
- saints, protein-protein interaction, affinity purification mass spectrometry, confidence scores, significance assessment, interactome analysis, probabilistic scoring
- MeSH terms
- Chromatography, Affinity, Computer Simulation, Probability, Protein Binding, Proteins, Mass Spectrometry, Computational Biology, Protein Interaction Mapping
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
