Fold Change Analysis

Fold Change Analysis

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CD Genomics can provide fold change analysis services to help customers screen genomics, transcriptomics, proteomics, and metabolomics data for genes with significant expression differences.

Introduction of Fold Change Analysis

The differential ploidy is the change in expression of the same gene in two samples, i.e., the ploidy change. It also reflects the difference, whether it is up- or down-regulated. If the samples are divided into control and experimental groups and you want to determine whether the gene expression in the two data groups is significant, you can do so by calculating the expression value difference ploidy in the two subgroups.

Fold-change-Specific Enrichment Analysis (FSEA) validation.Figure 1. Fold-change-Specific Enrichment Analysis (FSEA) validation. (Wiebe DS, et al., 2020)


Fold change analysis service can be used for but is not limited to the following research:

  • Used to analyze the expression of key genes during development.
  • For analyzing changes in gene expression after drug treatment during drug development.
  • Used to screen for genes with altered expression profiles in mutant material.


  • Bar graph of fold change analysis results.
  • Heat map of fold change analysis results.
  • Radar plot of fold change analysis results.

Fold Change Analysis Content

  • We are able to calculate the difference in the expression of a metabolite between two groups based on the relative or absolute quantitative results of the metabolite.
  • We are able to detect differentially expressed genes using differential ploidy analysis and determine genes with absolute values greater than a threshold as differential genes.


  • In the case of a large sample size, the determination of whether a gene is different or not is not only judged by the difference multiplicity but also needs to be combined with other statistical parameters.
  • The screening standard for transcriptome difference analysis is that the difference fold is generally adjusted appropriately floating between 1.2 and 2 fold and the false discovery rate is adjusted floating between 0.1 and 0.01.
  • During the calculation of the difference ploidy, a minimal value is generally assigned to genes without expression, which does not significantly affect the results and solves the problem of uncountable expression difference ploidy.

We are able to use fold change analysis to help our customers achieve high throughput data analysis in multi-omics. For questions about analysis content, project cycle, and pricing, please click online inquiry.

How It Works

CD Genomics is a professional bioinformatics service provider with years of experience in NGS and long-read sequencing (PacBio SMRT and Oxford Nanopore platforms) data, proteomics and metabolomics data analysis, integrated analysis services, database construction, and other bioinformatics solutions.

How It Works

CD Genomics has professional bioinformatics experts who have successfully provided fold change analysis to researchers in many different fields. Our professional skills and enthusiasm will provide you with high-quality analysis services. If you are interested in our services, please contact us for more details.


  1. Wiebe DS, et al. Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups. Genes (Basel). 2020 Apr 17; 11(4): 434.
* For Research Use Only. Not for use in diagnostic procedures.
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