Dataset Information

D-score - D-score: a search engine independent MD-score

ABSTRACT: Processing of the dataset of synthetic phosphopeptides by Savitzki et al. (MCP, 2011) using multiple search engines. Establishment of the D-score: a search engine independent MD-score.

INSTRUMENT(S): LTQ Orbitrap, instrument model

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Marc Vaudel

PROVIDER: PXD000021 | Pride | 2013-01-23

REPOSITORIES: Pride

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Publications

D-score: a search engine independent MD-score.

Vaudel Marc M Breiter Daniela D Beck Florian F Rahnenführer Jörg J Martens Lennart L Zahedi René P RP

Proteomics 20130215 6

While peptides carrying PTMs are routinely identified in gel-free MS, the localization of the PTMs onto the peptide sequences remains challenging. Search engine scores of secondary peptide matches have been used in different approaches in order to infer the quality of site inference, by penalizing the localization whenever the search engine similarly scored two candidate peptides with different site assignments. In the present work, we show how the estimation of posterior error probabilities for ...[more]

PMID: 23307401

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Project description:The standard platform for proteomics experiments today is mass spectrometry, particularly for samples derived from complex matrices. Recent increases in mass spectrometry sequencing speed, sensitivity and resolution now permit comprehensive coverage of even the most precious and limited samples, particularly when coupled with improvements in protein extraction techniques and chromatographic separation. However, the results obtained from laborious sample extraction and expensive instrumentation are often hindered by a sub optimal data processing pipelines. One critical data processing piece is peptide sequencing which is most commonly done through database search engines. In almost all MS/MS search engines users must limit their search space due to time constraints and q-value considerations. In nearly all experiments, the search is limited to a canonical database that typically does not reflect the individual genetic variations of the organism being studied. Searching for posttranslational modifications can exponentially increase the search space thus careful consideration must be used during the selection process. In addition, engines will nearly always assume the presence of only fully tryptic peptides. Despite these stringent parameters, proteomic data searches may take hours or even days to complete and opening even one of these criteria to more realistic biological settings will lead to detrimental increases in search time on expensive and custom data processing towers. Even on high performance servers, these search engines are computationally expensive, and most users decide to dial back their search parameters. We present Bolt, a new search engine that can search more than nine hundred thousand protein sequences (canonical, isoform, mutations, and contaminants) with 31 post translation modifications and N-terminal and C-terminal partial tryptic search in a matter of minutes on a standard configuration laptop. Along with increases in speed, Bolt provides an additional benefit of improvement in high confidence identifications, as demonstrated by manual validation of unique peptides identified by Bolt that were missed with parallel searching using standard engines. When in disagreement, 67% of peptides identified by Bolt may be manually validated by strong fragmentation patterns, compared to 14% of peptides uniquely identified by SEQUEST. Bolt represents, to the best of our knowledge, the first fully scalable, cloud based quantitative proteomic solution that can be operated within a user-friendly GUI interface.

Dataset Information

D-score - D-score: a search engine independent MD-score

Publications

D-score: a search engine independent MD-score.

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