Issue 6, 2020

Guide for protein fold change and p-value calculation for non-experts in proteomics

Abstract

Proteomics studies generate tables with thousands of entries. A significant component of being a proteomics scientist is the ability to process these tables to identify regulated proteins. Many bioinformatics tools are freely available for the community, some of which within reach for scientists with limited or no background in programming and statistics. However, proteomics has become popular in most other biological and biomedical disciplines, resulting in more and more studies where data processing is delegated to specialists that are not lead authors of the scientific project. This creates a risk or at least a limiting factor, as the biological interpretation of a dataset is contingent of a third-party specialist transforming data without the input of the project leader. We acknowledge in advance that dedicated scripts and software have a higher level of sophistication; but we hereby claim that the approach we describe makes proteomics data processing immediately accessible to every scientist. In this paper, we describe key steps of the typical data transformation, normalization and statistics in proteomics data analysis using a simple spreadsheet. This manuscript aims to demonstrate to those who are not familiar with the math and statistics behind these workflows that a proteomics dataset can be processed, simplified and interpreted in software like Microsoft Excel. With this, we aim to reach the community of non-specialists in proteomics to find a common language and illustrate the basic steps of –omics data processing.

Graphical abstract: Guide for protein fold change and p-value calculation for non-experts in proteomics

Supplementary files

Article information

Article type
Research Article
Submitted
10 juil. 2020
Accepted
18 sept. 2020
First published
18 sept. 2020

Mol. Omics, 2020,16, 573-582

Guide for protein fold change and p-value calculation for non-experts in proteomics

J. T. Aguilan, K. Kulej and S. Sidoli, Mol. Omics, 2020, 16, 573 DOI: 10.1039/D0MO00087F

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements