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Multiple Comparison Tests

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...

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Related Experiment Video

Updated: May 13, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

Jun Ji¹, Jeffrey Ling, Helen Jiang

¹Departments of Surgery, Stanford University, Stanford, CA 94305, USA.

BMC Research Notes

|March 26, 2013

Summary

This summary is machine-generated.

This study introduces a cloud-based web application for analyzing mass spectrometry (MS) data, simplifying proteomics biomarker discovery. The tool efficiently processes large datasets, identifying statistically significant protein peaks for validation.

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A Strategy for Sensitive, Large Scale Quantitative Metabolomics

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

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Last Updated: May 13, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

Area of Science:

Proteomics
Biomarker Discovery
Bioinformatics

Background:

Mass spectrometry (MS) is a key tool for high-throughput proteomics biomarker discovery.
Challenges include managing large datasets, peak identification, and high-dimensional differential analysis with false discovery rate (FDR) control.
There is a need for "turnkey" solutions to rapidly process MS data for biomarker investigations.

Purpose of the Study:

To present an efficient and effective cloud-based solution for analyzing mass spectrometry data.
To provide experimental biologists with accessible "cloud" computing capabilities for MS data analysis.
To facilitate the discovery of potential protein biomarkers using MS.

Main Methods:

Development of a web application for online MS data uploading and analysis.
Implementation of cloud computing capabilities for large-scale data processing.
User-friendly interface designed for experimental biologists.

Main Results:

An efficient and effective solution for MS data analysis is presented.
The web portal offers easy access to cloud computing for experimental biologists.
The application supports large-scale MS data uploading and analysis.

Conclusions:

The presented web application simplifies large-scale MS data analysis.
This bioinformatic tool facilitates the discovery of potential protein biomarkers.
The user interface is designed for ease of use by biologists.