Integrated data management and validation platform for phosphorylated tandem mass spectrometry data.
MS/MS is a widely used method for proteome-wide analysis of protein expression and PTMs. The thousands of MS/MS spectra produced from a single experiment pose a major challenge for downstream analysis. Standard programs, such as MASCOT, provide peptide assignments for many of the spectra, including identification of PTM sites, but these results are plagued by false-positive identifications. In phosphoproteomic experiments, only a single peptide assignment is typically available to support identification of each phosphorylation site, and hence minimizing false positives is critical. Thus, tedious manual validation is often required to increase confidence in the spectral assignments. We have developed phoMSVal, an open-source platform for managing MS/MS data and automatically validating identified phosphopeptides. We tested five classification algorithms with 17 extracted features to separate correct peptide assignments from incorrect ones using over 2600 manually curated spectra. The naïve Bayes algorithm was among the best classifiers with an AUC value of 97% and PPV of 97% for phosphotyrosine data. This classifier required only three features to achieve a 76% decrease in false positives as compared with MASCOT while retaining 97% of true positives. This algorithm was able to classify an independent phosphoserine/threonine data set with AUC value of 93% and PPV of 91%, demonstrating the applicability of this method for all types of phospho-MS/MS data. PhoMSVal is available at http://csbi.ltdk.helsinki.fi/phomsval.
Lahesmaa-Korpinen
Anna-Maria
AM
Genome-Scale Biology Program, Institute of Biomedicine, University of Helsinki, Helsinki, Finland.
Carlson
Scott M
SM
White
Forest M
FM
Hautaniemi
Sampsa
S
D000465:Algorithms; D001185:Artificial Intelligence; D030562:Databases, Protein; D010748:Phosphopeptides / Q000032:analysis*; D010766:Phosphorylation; D020543:Proteome / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D053719:Tandem Mass Spectrometry / Q000379:methods*
D010748:Phosphopeptides; D020543:Proteome
J Proteome Res. 2008 Jan;7(1):286-92
18078310
Genome Biol. 2007;8(11):R250
18039369
Anal Chem. 1995 Apr 15;67(8):1426-36
7741214
J Proteome Res. 2008 Sep;7(9):3708-17
18707158
Annu Rev Pharmacol Toxicol. 2009;49:199-221
18834307
Mol Cell Proteomics. 2005 Oct;4(10):1419-40
16009968
Nat Biotechnol. 2006 Oct;24(10):1285-92
16964243
Mol Cell Proteomics. 2005 Sep;4(9):1240-50
15951569
J Proteome Res. 2006 Jan;5(1):98-104
16396499
Mol Cell Proteomics. 2007 Sep;6(9):1638-55
17533153
Electrophoresis. 1999 Dec;20(18):3551-67
10612281
Curr Opin Biotechnol. 2008 Aug;19(4):404-9
18619541
J Proteome Res. 2008 Jul;7(7):3054-9
18543960
Bioinformatics. 2004 Aug 4;20 Suppl 1:i49-54
15262780
Anal Chem. 2007 Feb 15;79(4):1301-10
17297928
Methods Mol Biol. 2009;492:143-60
19241031
Curr Protoc Bioinformatics. 2007 Jun;Chapter 13:Unit 13.5
18428786
Bioinformatics. 2006 Feb 15;22(4):400-6
16352652
BMC Bioinformatics. 2008 Jul 07;9:302
18605993
Physiol Genomics. 2008 Mar 14;33(1):18-25
18212004
Nat Biotechnol. 2002 Mar;20(3):301-5
11875433
Nat Biotechnol. 2005 Jan;23(1):94-101
15592455
Mol Cell Proteomics. 2004 Dec;3(12):1154-69
15385600
Genome Inform. 2006;17(2):226-38
17503395
Genome Res. 2009 Oct;19(10):1786-800
19546170
Mol Cell Proteomics. 2002 May;1(5):376-86
12118079
Cell. 2006 Nov 3;127(3):635-48
17081983
J Proteome Res. 2004 Sep-Oct;3(5):958-64
15473683
Proteomics. 2005 Aug;5(13):3475-90
16047398
Anal Chem. 2005 Jul 15;77(14):4626-39
16013882
Mol Cell Proteomics. 2005 Jul;4(7):873-86
15858219
J Proteome Res. 2003 Jan-Feb;2(1):43-50
12643542
Nat Biotechnol. 2004 Feb;22(2):214-9
14730315
J Proteome Res. 2009 Jun;8(6):3141-7
19368407