Principal Component Analysis

Principal component analysis (PCA) is a technique to simplify the analysis data, and also is a visualization method for studying the similarity or difference of data. This method can effectively find out the most important elements and structures in the data and remove noise and redundancy. It also can reduce the dimension of the original complex data and reveal the simple structure hidden behind the complex data.

By analyzing the composition of OTU (97% similarity) of different samples, the differences and distances between samples can be reflected. PCA uses variance decomposition to reflect the differences of multiple sets of data on the two-dimensional coordinate graph. The coordinate axis takes two eigenvalues that can reflect the variance value to the maximum. For example, the more similar the sample composition, the closer the distance reflected in the PCA plot. Samples in different environments may show dispersion and aggregation. The two or three components with the highest interpretation degree of sample difference in PCA results can be used to verify hypothesis factors.

Principal component analysis (PCA) for functional diversity of microbial communities in soil collected from different areasFig.1 Principal component analysis (PCA) for functional diversity of microbial communities in soil collected from different areas. (Xie Y, et al. 2016)

Service Offering

Our services in terms of principal component analysis include,

  • Data processing
  • Principal component analysis of the microbial community
  • The drawing of the PCA plot
  • Other customized services you require

Tool Used

Analytical tools used in our principal component analysis service include PC-ORD, CANOCO software, and other related tools. Under the OUT of 97% similarity, PC-ORA and CANOCO are used to make the PCA plot.

Turnaround Time

In general, our turnaround time is 2-4 weeks depending on the size of your project.

Advantages of Our Services 

  • Principal component analysis is simple and has no parameter limitation.
  • We have a professional team of experts who can conduct personalized bioinformatics analysis.
  • Our comprehensive and detailed service content allows you to enjoy a one-stop experience.
  • We can combine your demands and negotiate to determine the content of services.

Creative Biogene focuses on the field of the principal component analysis. We use advanced analysis platforms to provide you with results of good reproducibility. Combining rich project experience, strict data quality control and professional analysis process, we will ensure that the project is carried out accurately and quickly. And we will uphold the pursuit of high quality faith and the professional spirit of dedicated service to provide you with our optimal service.

If you are interested in our services, please contact us for more details.


  1. Xie Y, et al. (2016). "Effect of heavy metals pollution on soil microbial diversity and bermudagrass genetic variation." Frontiers in plant science. 7: 755.
For Research Use Only.
Have a question? Get a Free Consultation