BACKGROUND: We developed a new version of the open source software package Peptrix that can yet compare large numbers of Orbitrap™ LC-MS data. The peptide profiling results for Peptrix on MS1 spectra were compared with those obtained from a small selection of open source and commercial software packages: msInspect, Sieve™ and Progenesis™. The properties compared in these packages were speed, total number of detected masses, redundancy of masses, reproducibility in numbers and CV of intensity, overlap of masses, and differences in peptide peak intensities. Reproducibility measurements were taken for the different MS1 software applications by measuring in triplicate a complex peptide mixture of immunoglobulin on the Orbitrap™ mass spectrometer. Values of peptide masses detected from the high intensity peaks of the MS1 spectra by peptide profiling were verified with values of the MS2 fragmented and sequenced masses that resulted in protein identifications with a significant score. FINDINGS: Peptrix finds about the same number of peptide features as the other packages, but peptide masses are in some cases approximately 5 to 10 times less redundant present in the peptide profile matrix. The Peptrix profile matrix displays the largest overlap when comparing the number of masses in a pair between two software applications. The overlap of peptide masses between software packages of low intensity peaks in the spectra is remarkably low with about 50% of the detected masses in the individual packages. Peptrix does not differ from the other packages in detecting 96% of the masses that relate to highly abundant sequenced proteins. MS1 peak intensities vary between the applications in a non linear way as they are not processed using the same method. CONCLUSIONS: Peptrix is capable of peptide profiling using Orbitrap™ files and finding differential expressed peptides in body fluid and tissue samples. The number of peptide masses detected in Orbitrap™ files can be increased by using more MS1 peptide profiling applications, including Peptrix, since it appears from the comparison of Peptrix with the other applications that all software packages have likely a high false negative rate of low intensity peptide peaks (missing peptides).
BACKGROUND: We developed a new version of the open source software package Peptrix that can yet compare large numbers of Orbitrap™ LC-MS data. The peptide profiling results for Peptrix on MS1 spectra were compared with those obtained from a small selection of open source and commercial software packages: msInspect, Sieve™ and Progenesis™. The properties compared in these packages were speed, total number of detected masses, redundancy of masses, reproducibility in numbers and CV of intensity, overlap of masses, and differences in peptide peak intensities. Reproducibility measurements were taken for the different MS1 software applications by measuring in triplicate a complex peptide mixture of immunoglobulin on the Orbitrap™ mass spectrometer. Values of peptide masses detected from the high intensity peaks of the MS1 spectra by peptide profiling were verified with values of the MS2 fragmented and sequenced masses that resulted in protein identifications with a significant score. FINDINGS: Peptrix finds about the same number of peptide features as the other packages, but peptide masses are in some cases approximately 5 to 10 times less redundant present in the peptide profile matrix. The Peptrix profile matrix displays the largest overlap when comparing the number of masses in a pair between two software applications. The overlap of peptide masses between software packages of low intensity peaks in the spectra is remarkably low with about 50% of the detected masses in the individual packages. Peptrix does not differ from the other packages in detecting 96% of the masses that relate to highly abundant sequenced proteins. MS1 peak intensities vary between the applications in a non linear way as they are not processed using the same method. CONCLUSIONS: Peptrix is capable of peptide profiling using Orbitrap™ files and finding differential expressed peptides in body fluid and tissue samples. The number of peptide masses detected in Orbitrap™ files can be increased by using more MS1peptide profiling applications, including Peptrix, since it appears from the comparison of Peptrix with the other applications that all software packages have likely a high false negative rate of low intensity peptide peaks (missing peptides).
Authors: Rodrigo D A M Alves; Marco Eijken; Sigrid Swagemakers; H Chiba; Mark K Titulaer; Peter C Burgers; Theo M Luider; Johannes P T M van Leeuwen Journal: J Proteome Res Date: 2010-09-03 Impact factor: 4.466
Authors: Lukas N Mueller; Oliver Rinner; Alexander Schmidt; Simon Letarte; Bernd Bodenmiller; Mi-Youn Brusniak; Olga Vitek; Ruedi Aebersold; Markus Müller Journal: Proteomics Date: 2007-10 Impact factor: 3.984
Authors: Lennard J M Dekker; Peter C Burgers; Halima Charif; Angelique L C T van Rijswijk; Mark K Titulaer; Guido Jenster; Rainer Bischoff; Chris H Bangma; Theo M Luider Journal: Proteomics Date: 2010-06 Impact factor: 3.984
Authors: Mark K Titulaer; Ivar Siccama; Lennard J Dekker; Angelique L C T van Rijswijk; Ron M A Heeren; Peter A Sillevis Smitt; Theo M Luider Journal: BMC Bioinformatics Date: 2006-09-05 Impact factor: 3.169
Authors: Marcel P Stoop; Vaibhav Singh; Lennard J Dekker; Mark K Titulaer; Christoph Stingl; Peter C Burgers; Peter A E Sillevis Smitt; Rogier Q Hintzen; Theo M Luider Journal: PLoS One Date: 2010-08-27 Impact factor: 3.240
Authors: Isabel M Carvalho-Oliveira; Nuno Charro; Jamil Aarbiou; Ruvalic M Buijs-Offerman; Martina Wilke; Thomas Schettgen; Thomas Kraus; Mark K Titulaer; Peter Burgers; Theo M Luider; Deborah Penque; Bob J Scholte Journal: J Proteome Res Date: 2009-07 Impact factor: 4.466
Authors: Dana A N Mustafa; Peter C Burgers; Lennard J Dekker; Halima Charif; Mark K Titulaer; Peter A E Sillevis Smitt; Theo M Luider; Johan M Kros Journal: Mol Cell Proteomics Date: 2007-03-14 Impact factor: 5.911
Authors: Mark K Titulaer; Dana A N Mustafa; Ivar Siccama; Marco Konijnenburg; Peter C Burgers; Arno C Andeweg; Peter A E Sillevis Smitt; Johan M Kros; Theo M Luider Journal: BMC Bioinformatics Date: 2008-03-01 Impact factor: 3.169
Authors: Tyler Greer; Ling Hao; Anatoliy Nechyporenko; Sanghee Lee; Chad M Vezina; Will A Ricke; Paul C Marker; Dale E Bjorling; Wade Bushman; Lingjun Li Journal: PLoS One Date: 2015-08-12 Impact factor: 3.240