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Related Concept Videos

What is an Experiment?01:12

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An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
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Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
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IsoProt: A Complete and Reproducible Workflow To Analyze iTRAQ/TMT Experiments.

Johannes Griss1,2, Goran Vinterhalter3, Veit Schwämmle4

  • 1EMBL-European Bioinformatics Institute , Wellcome Trust Genome Campus , CB10 1SD Hinxton, Cambridge , United Kingdom.

Journal of Proteome Research
|March 12, 2019
PubMed
Summary

Reproducibility in proteomics is enhanced with IsoProt, a containerized workflow. This open-source tool ensures identical results across platforms for quantitative proteomics data analysis.

Keywords:
DockerJupyterProtProtocolsTMTbioinformaticsiTRAQisobaric labelingprotocolreproducibilityworkflow

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Area of Science:

  • Biomedical Research
  • Bioinformatics
  • Proteomics

Background:

  • Reproducibility is a significant challenge in biomedical research.
  • Complex bioinformatic workflows in proteomics often involve numerous software tools and parameters, making methods sections insufficient for complete reproduction.
  • Ensuring tool interoperability requires extensive parameter definition and data manipulation.

Purpose of the Study:

  • To present IsoProt, a comprehensive and reproducible bioinformatic workflow for quantitative proteomics.
  • To address the limitations of current methods sections in fully describing and enabling the reproduction of proteomics data analysis.
  • To provide a user-friendly solution for analyzing isobarically labeled proteomics data.

Main Methods:

  • IsoProt is deployed on a portable container environment for consistent execution.
  • The workflow exclusively utilizes open-source tools.
  • It features an interactive browser interface for easy configuration and execution of analysis steps.

Main Results:

  • IsoProt provides a complete record of performed analyses, including R code for statistical analysis, downloadable as an HTML document.
  • The workflow ensures identical results regardless of the computer platform.
  • It facilitates the reproducible analysis of quantitative proteomics data.

Conclusions:

  • IsoProt significantly improves the reproducibility of quantitative proteomics data analysis.
  • The containerized, open-source approach ensures consistent and reliable results.
  • This workflow enhances the transparency and reliability of biomedical research findings.