Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Proteomics01:33

Proteomics

10.1K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
10.1K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.8K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

PSAQ<sup>+1</sup>: Absolute Protein Quantification Using a <sup>13</sup>C<sub>1</sub>-Labeled Protein Standard, Coisolation of Peptide Pairs and LC-PRM.

Analytical chemistry·2026
Same author

Arf1 is involved in Neisseria meningitidis-induced cortical branched F-actin network reorganization.

EMBO reports·2026
Same author

Deciphering photosynthetic protein networks: a crosslinking-MS strategy for studying functional thylakoid membranes.

The Plant journal : for cell and molecular biology·2026
Same author

Direct carbapenemase typing from disc diffusion antibiograms with MALCA (MAchine Learning CArbapenemase).

Nature communications·2026
Same author

Performance Is Not All You Need! Comment on "Unsupervised Machine Learning for Differential Analysis in Proteomics".

Analytical chemistry·2026
Same author

Association of nasopharyngeal <i>Dolosigranulum pigrum</i> and <i>Corynebacterium</i> species with post-acute sequelae of SARS-CoV-2 in a longitudinal cohort.

Microbiology spectrum·2026

Related Experiment Video

Updated: Mar 15, 2026

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions
05:37

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions

Published on: October 20, 2020

7.5K

DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics.

Samuel Wieczorek1,2,3, Florence Combes1,2,3, Cosmin Lazar1,2,3

  • 1Université Grenoble Alpes, BIG-BGE, Grenoble, 38000, France.

Bioinformatics (Oxford, England)
|September 9, 2016
PubMed
Summary
This summary is machine-generated.

DAPAR and ProStaR are R-based software tools for label-free quantitative proteomics statistical analysis. They offer data processing, imputation, and differential protein abundance identification with false discovery rate control.

More Related Videos

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization
12:11

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Published on: February 27, 2020

7.4K
Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

1.2K

Related Experiment Videos

Last Updated: Mar 15, 2026

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions
05:37

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions

Published on: October 20, 2020

7.5K
Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization
12:11

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Published on: February 27, 2020

7.4K
Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
07:01

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

1.2K

Area of Science:

  • Proteomics
  • Bioinformatics
  • Statistical Analysis

Background:

  • Label-free quantitative proteomics experiments generate complex datasets requiring robust statistical analysis.
  • Accurate identification and quantification of differentially abundant proteins are crucial for biological discovery.

Purpose of the Study:

  • To introduce DAPAR and ProStaR, two software tools designed for the statistical analysis of label-free XIC-based quantitative proteomics data.
  • To provide a user-friendly interface for complex proteomics data analysis.

Main Methods:

  • DAPAR offers comprehensive procedures for data filtering, normalization, missing value imputation, peptide intensity aggregation, and statistical testing.
  • ProStaR provides a graphical user interface for accessible utilization of DAPAR functionalities via a web browser.
  • Both tools are implemented in the R language.

Main Results:

  • DAPAR enables the selection of differentially abundant proteins with associated false discovery rates.
  • ProStaR simplifies the application of DAPAR's advanced statistical methods through an intuitive web interface.

Conclusions:

  • DAPAR and ProStaR offer a powerful and accessible solution for statistical analysis in quantitative proteomics.
  • These tools facilitate the reliable identification of protein abundance changes in biological samples.