Dataset Information

PhosphoScore: an open-source phosphorylation site assignment tool for MSn data.

ABSTRACT: Correct phosphorylation site assignment is a critical aspect of phosphoproteomic analysis. Large-scale phosphopeptide data sets that are generated through liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) analysis often contain hundreds or thousands of phosphorylation sites that require validation. To this end, we have created PhosphoScore, an open-source assignment program that is compatible with phosphopeptide data from multiple MS levels (MS(n)). The algorithm takes into account both the match quality and normalized intensity of observed spectral peaks compared to a theoretical spectrum. PhosphoScore produced >95% correct MS(2) assignments from known synthetic data, > 98% agreement with an established MS(2) assignment algorithm (Ascore), and >92% agreement with visual inspection of MS(3) and MS(4) spectra.

SUBMITTER: Ruttenberg BE

PROVIDER: S-EPMC2562657 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

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PhosphoScore: an open-source phosphorylation site assignment tool for MSn data.

Ruttenberg Brian E BE Pisitkun Trairak T Knepper Mark A MA Hoffert Jason D JD

Journal of proteome research 20080611 7

Correct phosphorylation site assignment is a critical aspect of phosphoproteomic analysis. Large-scale phosphopeptide data sets that are generated through liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) analysis often contain hundreds or thousands of phosphorylation sites that require validation. To this end, we have created PhosphoScore, an open-source assignment program that is compatible with phosphopeptide data from multiple MS levels (MS(n)). The algorithm takes into accou ...[more]

PMID: 18543960

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Project description:IntroductionIn smoking cessation clinical trials, timeline followback (TLFB) interviews are widely used to track daily cigarette consumption. However, there are no standard tools for calculating abstinence based on TLFB data. Individual research groups have to develop their own calculation tools, which is not only time- and resource-consuming but might also lead to variability in the data processing and calculation procedures.Aims and methodsTo address these issues, we developed a novel open-source Python package named abstcal to calculate abstinence using TLFB data. This package provides data verification, duplicate and outlier detection, missing-data imputation, integration of biochemical verification data, and calculation of a variety of definitions of abstinence, including continuous, point-prevalence, and prolonged abstinence.ResultsWe verified the accuracy of the calculator using data derived from a clinical smoking cessation study. To improve the package's accessibility, we have made it available as a free web app.ConclusionsThe abstcal package is a reliable abstinence calculator with open-source access, providing a shared validated online tool to the addiction research field. We expect that this open-source abstinence calculation tool will improve the rigor and reproducibility of smoking and addiction research by standardizing TLFB-based abstinence calculation.ImplicationsAbstinence calculation is an essential task in any smoking intervention study. However, there have not been standard open-source tools available to the researchers. This commentary describes a Python-based package called abstcal that can calculate abstinence from TLFB data, a common methodology to collect smoking consumption data in research settings. The package supports the calculation of point-prevalence, prolonged, and continuous abstinence. Importantly, the package has a web app interface that allows researchers to use the tool without any coding experience. This tool will facilitate smoking research by providing a standardized and easy-to-use abstinence calculation tool.

Dataset Information

PhosphoScore: an open-source phosphorylation site assignment tool for MSn data.

Publications

PhosphoScore: an open-source phosphorylation site assignment tool for MSn data.

Similar Datasets

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