BSI Research Conducted Using PEAKS
Featured Papers
ABRF 2013
HUPO 2012
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In Depth Analysis of Protein Amino Acid Sequence and PTMs with High-Resolution Mass Spectrometry.
Yang L, Shan B, Ma B. HUPO 2012: Oral Session. |
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We propose the software workflow for in-depth protein sequence analysis. The BSA experiment showcased that the workflow found many things in a pure sample, including contaminants, unsuspected PTMs, and mutations. It increased the protein coverage, and explained more high-quality MS/MS spectra. |
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Zhang J, Xin L, Shan B, Chen W, Xie M, Yuen D, Zhang W, Zhang Z, Lajoie G, Ma B. PEAKS DB: De Novo sequencing assisted database search for sensitive and accurate peptide identification. Mol Cell Proteomics 11: 10.1074/mcp.M111.010587, 1–8, 2012. |
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Many software tools have been developed for the automated identification of peptides from tandem mass spectra. The accuracy and sensitivity of the identification software via database search are critical for successful proteomics experiments. A new database search tool, PEAKS DB, has been developed by incorporating the de novo sequencing results into the database search. PEAKS DB achieves significantly improved accuracy and sensitivity over two other commonly used software packages. Additionally, a new result validation method, decoy fusion, has been introduced to solve the issue of over-confidence that exists in the conventional target-decoy method for certain types of peptide identification software. |
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Han X, He L, Xin L, Shan B, and Ma B.PeaksPTM: Mass Spectrometry-Based Identification of Peptides with Unspecified Modifications. Journal of Proteomics Research 10(7): 2930-2936 (2011). |
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Tandem mass spectrometry (MS/MS) has been routinely used to identify peptides from a protein sequence database. To identify post-translationally modified peptides, most existing software requires the specification of a few possible modifications. However, such knowledge of possible modifications is not always available. In this paper, we describe a new algorithm for identifying modified peptides without requiring the user to specify the possible modifications; instead, all modifications from the Unimod database are considered. Meanwhile, several new techniques are employed to avoid the exponential growth of the search space, as well as to control the false discoveries due to this unrestricted search approach. Finally, a software tool, PeaksPTM, has been developed and already achieved a stronger performance than competitive tools for unrestricted identification of post-translational modifications. |
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Han Y, Ma B, Zhang K. SPIDER: Software for Protein Identification from Sequence Tags Containing De Novo Sequencing Error. J Bioinform Comput Biol. 2005 Jun;3(3):697-716. |
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For the identification of novel proteins using MS/MS, de novo sequencing software computes one or several possible amino acid sequences (called sequence tags) for each MS/MS spectrum. Those tags are then used to match, accounting amino acid mutations, the sequences in a protein database. If the de novo sequencing gives correct tags, the homologs of the proteins can be identified by this approach and software such as MS-BLAST is available for the matching. However, de novo sequencing very often gives only partially correct tags. The most common error is that a segment of amino acids is replaced by another segment with approximately the same masses. We developed a new efficient algorithm to match sequence tags with errors to database sequences for the purpose of protein and peptide identification. A software package, SPIDER, was developed and made available on Internet for free public use. This paper describes the algorithms and features of the SPIDER software. |
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Ma B, Zhang K, Hendrie C, Liang C, Li M, Doherty-Kirby A, Lajoie G. PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun Mass Spectrom. 2003;17(20):2337-42. |
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A number of different approaches have been described to identify proteins from tandem mass spectrometry (MS/MS) data. The most common approaches rely on the available databases to match experimental MS/MS data. These methods suffer from several drawbacks and cannot be used for the identification of proteins from unknown genomes. In this communication, we describe a new de novo sequencing software package, PEAKS, to extract amino acid sequence information without the use of databases. PEAKS uses a new model and a new algorithm to efficiently compute the best peptide sequences whose fragment ions can best interpret the peaks in the MS/MS spectrum. The output of the software gives amino acid sequences with confidence scores for the entire sequences, as well as an additional novel positional scoring scheme for portions of the sequences. The performance of PEAKS is compared with Lutefisk, a well-known de novo sequencing software, using quadrupole-time-of-flight (Q-TOF) data obtained for several tryptic peptides from standard proteins. |
ASMS 2012
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GlycoMaster: Glycopeptide High-Throughput Identification and Characterization Software.
He L, Shan B, Xin L, Lajoie G, Ma B. ASMS 2012: MP 131. |
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Optimized Database Search Software for Peptide Identification with AB SCIEX TripleTOF 5600.
Yang L, Shan B. ASMS 2012: MP 363. |
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In Depth Analysis of the Spectra Unassigned by Database Search.
Yang L, Shan B, Zhang Z, Chen W, Ma B. ASMS 2012: MP 375. |
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How Useful Is the Product Ion Mass Accuracy for Peptide Identification?.
Shan B, Dankiw B, Ma B. ASMS 2012: MP 382. |
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Analysis of post translational modifications with AB SCIEX TripleTOF 5600 System.
Zhang C, Shan B. ASMS 2012: TP 478. |
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Cross-Species Search for Accurate and Sensitive Peptide Identification.
Chen W, Yuen D, Maloney D, Ma B. ASMS 2012: WP 418. |
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Combine Multiple Database Search Engines with Uniform FDR.
Xin L, Munro B, Ma B. ASMS 2012: ThP 297. |
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Peptide Identification with High Mass Accuracy using Lock Mass Calibration.
Rahman M, Xie M, Yuen D, Ma B. ASMS 2012: ThP 591. |
ABRF 2012
HUPO 2011
ASMS 2011
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Yuen, D. SPIDER: Reconstructive Protein Homology Search with De Novo Sequencing Tag. University of Waterloo, April 24, 2011. |
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Peptide identification is a central task in mass spectrometry based proteomics. Existing approaches include: (1) protein sequence database search with uninterpreted spectra, (2) de novo sequencing, (3) database search of de novo sequence tags, and (4) spectral library search. These approaches are usually performed separately according to the circumstances. In this abstract, we present the PEAKS-DB software that combines the first three approaches to significantly improve the sensitivity and reduce the FDR of peptide identification. |
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Xin L. Probability Scoring System for De Novo And Protein Identification with Tandem Mass Spectrometry. University of Western Ontario, 2010. |
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Based on the PEAKS raw ion score, we propose some new features to distinguish correct matches from false matches. Then we build statistical models on these features and a probability scoring system is established. Not only does the new scoring function provide the automated result validation, but also it improves the accuracy of the PEAKS algorithm. In addition we propose a novel local search method for improving the de novo} sequencing algorithm of PEAKS. The thesis is divided into two parts according to two different approaches. In the first part, we calculate a probability score for each amino acid from \textit{de novo} sequencing results. In the second part, probability scoring systems are established for both peptide matches and protein hits. Experimental results show that new probability scoring system outperforms PEASK4.5 scoring system in both probability accuracy and the ability to distinguish correct matches from false matches. |
ASMS 2010
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Liu X, Shan B, Xin L, Ma B. Better score function for peptide identification with ETD MS/MS spectra. BMC Bioinformatics. 2010 Jan 18;11 Suppl 1:S4. |
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Background: Tandem mass spectrometry (MS/MS) has become the primary way for protein identification in proteomics. A good score function for measuring the match quality between a peptide and an MS/MS spectrum is instrumental for the protein identification. Traditionally the tobe-measured peptides are fragmented with the collision induced dissociation (CID) method. More recently, the electron transfer dissociation (ETD) method was introduced and has proven to produce better fragment ion ladders for larger and more basic peptides. However, the existing software programs that analyze ETD MS/MS data are not as advanced as they are for CID.
Results: To take full advantage of ETD data, in this paper we develop a new score function to evaluate the match between a peptide and an ETD MS/MS spectrum. Experiments on real data demonstrated that this newly developed score function significantly improved the de novo sequencing accuracy of the PEAKS software on ETD data.
Conclusion: A new and better score function for ETD MS/MS peptide identification was developed. The method used to develop our ETD score function can be easily reused to train new score functions for other types of MS/MS data. |
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Liu X, Han Y, Yuen D, Ma B. Automated protein (re)sequencing with MS/MS and a homologous database yields almost full coverage and accuracy. Bioinformatics. 2009 Sep 1;25(17):2174-80. Epub 2009 Jun 17. |
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Motivation: The bottom-up tandem mass spectrometry (MS/MS) is regularly used in proteomics nowadays for identifying proteins from a sequence database. De novo sequencing software is also available for sequencing novel peptides with relatively short sequence lengths. However, automated sequencing of novel proteins from MS/MS remains a challenging problem. Results: Very often, although the target protein is novel, it has a homologous protein included in a known database. When this happens, we propose a novel algorithm and automated software tool, named Champs, for sequencing the complete protein from MS/MS data of a few enzymatic digestions of the purified protein. Validation with two standard proteins showed that our automated method yields greater than 99% sequence coverage and 100% sequence accuracy on these two proteins. Our method is useful to sequence novel proteins or "re-sequence" a protein that has mutations comparing with the database protein sequence. |
ASMS 2009
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Ma, B. and Lajoie, G. De Novo Interpretation of Tandem Mass Spectra. Current Protocols in Bioinformatics. 25:13.10.1–13.10.8.
March 1, 2009. |
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De novo sequencing is an effective method for identifying unknown peptide sequences from their tandem mass spectra. This unit briefly introduces how this can be done manually. A protocol for using the PEAKS online software for automated de novo sequencing is described. Finally, we show how to use the PEAKS scores to validate the de novo sequencing results. |
ASMS 2008
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Xin L, Lajoie G, Ma B. New Method for the Validation of de novo Sequencing Results. ASMS 2008: WP 645. |
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Since de novo sequencing does not depend on protein databases, the validation and confidence methods developed in the database search approach such as the reverse-database query cannot be applied. Here we present a general validation algorithm which uses any de novo sequencing scores to calculate the correctness probabilities of each amino acid in the de novo sequencing results. In addition to result validation, these probabilities can also be used in other protein identification software such as SPIDER. |
ASMS 2007
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Xu C, Ma B. Software for computational peptide identification from MS-MS data. Drug Discov Today. 2006 Jul;11(13-14):595-600. |
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Protein identification in biological samples is an important task in drug discovery research. Protein identification is nowadays regularly performed by tandem mass spectrometry (MS-MS). Because of the difficulty of measuring intact proteins using MS-MS, typically a protein is enzymically digested into peptides and the MS-MS spectrum of each peptide is measured. Computational methods are then invoked to identify the peptides, which are later combined together to identify the protein. The most recognized peptide identification software packages can be classified into four categories: database searching, de novo sequencing, sequence tagging and consensus of multiple engines. |
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Ma B, Rogers I. Application Note: PEAKS de novo performance on LTQ Orbitrap data. June 2006. |
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High resolution, high mass accuracy instruments like Thermo’s LTQ Orbitrap, promise to significantly enhance proteomics analysis. De novo sequencing is one of the applications of peptide mass spectrometry that will be most affected by the increase in data quality. Here the authors present the improvement in results obtainable by PEAKS peptide de novo sequencing when using an LTQ Orbitrap mass spectrometer. During this demonstration of the accuracy of PEAKS de novo sequencing on a Thermo LTQ Orbitrap mass spectrometer, 97% accuracy is achieved. |
ASMS 2006
ASMS 2005
ASMS 2004
ASMS 2003
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