Article

PeakPerformance - a tool for Bayesian inference-based fitting of LC-MS/MS peaks

2024-02-21

Abstract excerpt

A major bottleneck of chromatography-based analytics has been the elusive fully automated identification and integration of peak data without the need of extensive human supervision. The presented Python package PeakPerformance applies Bayesian inference to chromatographic peak fitting, and provides an automated approach featuring model selection and uncertainty quantification. Currently, its application is focus...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 04854144-0622-5ef5-bfd5-8cd973ba912a
DOI: 10.1101/2024.02.17.580815

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

PeakPerformance - a tool for Bayesian inference-based fitting of LC-MS/MS peaksDOI 10.1101/2024.02.17.580815Read

Dynamic binning peak detection and assessment of various lipidomics liquid chromatography-mass spectrometry pre-processing platformsSemantic proximity Read

Pipelines and Systems for Threshold Avoiding Quantification of LC-MS/MS dataSemantic proximity Read

A benchmarking workflow for assessing the reliability of batch correction methodsSemantic proximity Read

DIAproteomics: A multi-functional data analysis pipeline for data-independent-acquisition proteomics and peptidomicsSemantic proximity Read

A sensitivity analysis to determine the robustness of STRmix™ with respect to laboratory calibration.Semantic proximity Read

Integrated workflow for univariate and multivariate evaluation of batch correction reliabilitySemantic proximity Read

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics.Semantic proximity Read

A Bayesian approach to accurate and robust signature detection on LINCS L1000 dataSemantic proximity Read

Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipelineSemantic proximity Read

Retention Time Standardization and Registration (RTStaR): An algorithm that matches corresponding and identifies unique species in nanoliquid chromatography-nanoelectrospray ionization-mass spectrometry lipidomic datasetsSemantic proximity Read

rtmsEcho: An Open-Source R Package for Automated Analysis of Acoustic Ejection Mass Spectrometry DataSemantic proximity Read

Comprehensive peptide quantification for data independent acquisition mass spectrometry using chromatogram librariesSemantic proximity Read