Improvements to the Percolator Algorithm for Peptide Identification from Shotgun Proteomics Data Sets

Spivak, Marina; Weston, Jason; Bottou, Léon; Käll, Lukas; Noble, William Stafford

doi:10.1021/pr801109k

Cited by 251 publications

(247 citation statements)

References 27 publications

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“…This approach contrasts with previous applications of machine learning to this task (5,26,27,37,38), which optimize at the level of PSMs or peptides. In general, focusing on one optimization target or the other will depend on the goal of the proteomics experiment.…”

Section: Resultsmentioning

confidence: 93%

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Direct Maximization of Protein Identifications from Tandem Mass Spectra

Spivak¹,

Weston

Tomazela³

et al. 2012

Molecular & Cellular Proteomics

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The goal of many shotgun proteomics experiments is to determine the protein complement of a complex biological mixture. For many mixtures, most methodological approaches fall significantly short of this goal. Existing solutions to this problem typically subdivide the task into two stages: first identifying a collection of peptides with a low false discovery rate and then inferring from the peptides a corresponding set of proteins. In contrast, we formulate the protein identification problem as a single optimization problem, which we solve using machine learning methods. This approach is motivated by the observation that the peptide and protein level tasks are cooperative, and the solution to each can be improved by using information about the solution to the other. The resulting algorithm directly controls the relevant error rate, can incorporate a wide variety of evidence and, for complex samples, provides 18 -34% more protein identifications than the current state of the art approaches.

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Section: Resultsmentioning

confidence: 93%

“…The number of HU is a hyperparameter that can be chosen by cross-validation. This nonlinear function is the improved model used in Q-ranker (27). Throughout this work, we use a fixed value of three hidden units.…”

Section: Table I Features Used To Represent Psmsmentioning

confidence: 99%

Direct Maximization of Protein Identifications from Tandem Mass Spectra

Spivak¹,

Weston

Tomazela³

et al. 2012

Molecular & Cellular Proteomics

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“…The relative abundance of phosphopeptides was quantitated based on the area under the MS peaks using the quantitation node in Proteome Discoverer. The Percolator algorithm (29) in Proteome Discoverer was used to filter peptide spectrum matches at a false discovery rate Ͻ1% using q-values. The probability of phosphorylation for each Ser/Thr/Tyr site on each peptide was calculated by the phosphoRS algorithm.…”

Section: Methodsmentioning

confidence: 99%

Phosphoproteomic Analysis Identifies Focal Adhesion Kinase 2 (FAK2) as a Potential Therapeutic Target for Tamoxifen Resistance in Breast Cancer

Zahari

Renuse

et al. 2015

Molecular & Cellular Proteomics

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Tamoxifen, an estrogen receptor-␣ (ER) antagonist, is an important agent for the treatment of breast cancer. However, this therapy is complicated by the fact that a substantial number of patients exhibit either de novo or acquired resistance. To characterize the signaling mechanisms underlying this resistance, we treated the MCF7 breast cancer cell line with tamoxifen for over six months and showed that this cell line acquired resistance to tamoxifen in vitro and in vivo. We performed SILAC-based quantitative phosphoproteomic profiling on the tamoxifen resistant and vehicle-treated sensitive cell lines to quantify the phosphorylation alterations associated with tamoxifen resistance. From >5600 unique phosphopeptides identified, 1529 peptides exhibited hyperphosphorylation and 409 peptides showed hypophosphorylation in the tamoxifen resistant cells. Gene set enrichment analysis revealed that focal adhesion pathway was one of the most enriched signaling pathways activated in tamoxifen resistant cells. Significantly, we showed that the focal adhesion kinase FAK2 was not only hyperphosphorylated but also transcriptionally upregulated in tamoxifen resistant cells. FAK2 suppression by specific siRNA knockdown or a small molecule inhibitor repressed cellular proliferation in vitro and tumor formation in vivo. More importantly, our survival analysis revealed that high expression of FAK2 is significantly associated with shorter metastasis-free survival in estrogen receptor-positive breast cancer patients treated with tamoxifen. Our studies suggest that FAK2 is a potential therapeutic target for the management of hormone-refractory breast cancers. Molecular & Cellular

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“…Note: The search function is completed automatically by the software using various search engine specific algorithms. The percolator algorithm (MASCOT), SEQUEST, or other combinations of algorithms are employed to identify proteins from peptides and to score the validity of the hits; more information on the tools available are covered in a review from Gonzalez-Galarza et al 28,29 . Depending on the software, additional search parameters may need to be selected according to the discretion of the user.…”

Section: Proteomics and Deamidation Analysismentioning

confidence: 99%

A Quantitative Glycomics and Proteomics Combined Purification Strategy

Hecht

McCord

Muddiman

2016

JoVE

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There is a growing desire in the biological and clinical sciences to integrate and correlate multiple classes of biomolecules to unravel biology, define pathways, improve treatment, understand disease, and aid biomarker discovery. N-linked glycosylation is one of the most important and robust post-translational modifications on proteins and regulates critical cell functions such as signaling, adhesion, and enzymatic function.Analytical techniques to purify and analyze N-glycans have remained relatively static over the last decade. While accurate and effective, they commonly require significant expertise and resources. Though some high-throughput purification schemes have been developed, they have yet to find widespread adoption and often rely on the enrichment of glycopeptides. One promising method, developed by Thomas-Oates et al., filter aided N-glycan separation (FANGS), was qualitatively demonstrated on tissues. Herein, we adapted FANGS to plasma and coupled it to the individuality normalization when labeling with glycan hydrazide tags strategy in order to achieve accurate relative quantification by liquid chromatography mass spectrometry and enhanced electrospray ionization. Furthermore, we designed new functionality to the protocol by achieving tandem, shotgun proteomics and glycosylation site analysis on hen plasma. We showed that N-glycans purified on filter and derivatized by hydrophobic hydrazide tags were comparable in terms of abundance and class to those by solid phase extraction (SPE); the latter is considered a gold standard in the field. Importantly, the variability in the two protocols was not statistically different. Proteomic data that was collected in-line with glycomic data had the same depth compared to a standard trypsin digest. Peptide deamidation is minimized in the protocol, limiting non-specific deamidation detected at glycosylation motifs. This allowed for direct glycosylation site analysis, though the protocol can accommodate 18 O site labeling as well. Overall, we demonstrated a new in-line high-throughput, unbiased, filter based protocol for quantitative glycomics and proteomics analysis.

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Improvements to the Percolator Algorithm for Peptide Identification from Shotgun Proteomics Data Sets

Cited by 251 publications

References 27 publications

Direct Maximization of Protein Identifications from Tandem Mass Spectra

Direct Maximization of Protein Identifications from Tandem Mass Spectra

Phosphoproteomic Analysis Identifies Focal Adhesion Kinase 2 (FAK2) as a Potential Therapeutic Target for Tamoxifen Resistance in Breast Cancer

A Quantitative Glycomics and Proteomics Combined Purification Strategy

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