Please use this identifier to cite or link to this item: https://doi.org/10.1002/0471250953.bi0815s39
Title: Analyzing protein-protein interactions from affinity purification-mass spectrometry data with SAINT
Authors: Choi, H. 
Liu, G.
Mellacheruvu, D.
Tyers, M.
Gingras, A.-C.
Nesvizhskii, A.I.
Keywords: Affinity purification-mass spectrometry (AP-MS)
Label-free quantitative proteomics
Protein-protein interactions
statistical model
Issue Date: Sep-2012
Source: Choi, H.,Liu, G.,Mellacheruvu, D.,Tyers, M.,Gingras, A.-C.,Nesvizhskii, A.I. (2012-09). Analyzing protein-protein interactions from affinity purification-mass spectrometry data with SAINT. Current Protocols in Bioinformatics (SUPPL.39) : -. ScholarBank@NUS Repository. https://doi.org/10.1002/0471250953.bi0815s39
Abstract: Significance Analysis of INTeractome (SAINT) is a software package for scoring proteinprotein interactions based on label-free quantitative proteomics data (e.g., spectral count or intensity) in affinity purification-mass spectrometry (AP-MS) experiments. SAINT allows bench scientists to select bona fide interactions and remove nonspecific interactions in an unbiased manner. However, there is no 'one-size-fits-all' statistical model for every dataset, since the experimental design varies across studies. Key variables include the number of baits, the number of biological replicates per bait, and control purifications. Here we give a detailed account of input data format, control data, selection of highconfidence interactions, and visualization of filtered data. We explain additional options for customizing the statistical model for optimal filtering in specific datasets. We also discuss a graphical user interface of SAINT in connection to the LIMS system ProHits, which can be installed as a virtual machine on Mac OS X or Windows computers. © 2012 John Wiley & Sons, Inc.
Source Title: Current Protocols in Bioinformatics
URI: http://scholarbank.nus.edu.sg/handle/10635/108868
ISSN: 19343396
DOI: 10.1002/0471250953.bi0815s39
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