What is principal coordinate analysis?

PCoA, namely principal co-ordinates analysis, is also a non-constrained data dimensionality reduction analysis method that can be used to study the similarity or difference of sample community composition, similar to PCA; the main difference is: PCA is based on the Euclidean distance, and PCoA is based on distances other than the Euclidean distance, and finds the potential principal components that affect the difference in the composition of the sample community through dimensionality reduction. In PCoA, a series of eigenvalues and eigenvectors are sorted first, and then the most important eigenvalues in the top few are selected and displayed in the coordinate system. The result is equivalent to a rotation of the distance matrix, which has not changed The mutual positional relationship between the sample points only changes the coordinate system.

Overall solutions

CD ComputaBio can provide you with the following statistical services but not limited to:

• The distance matrix obtained from the analysis can be used in a variety of analysis methods. CD ComputaBio can use the multivariate statistical method PCoA to visually display the similarities and differences in the evolution of microorganisms in different environmental samples.
•  CD ComputaBio's PCoA service can find the most important coordinates in the distance matrix.
•  CD ComputaBio can observe differences between individuals or groups through PCoA.
•  CD ComputaBio can sort by a series of eigenvalues and eigenvectors, and then select the top eigenvalues.

Our services

CD ComputaBio' PCoA principal coordinate analysis service can significantly reduce the cost and labor of the subsequent experiments. PCoA principal coordinate analysis is a personalized and customized innovative scientific research service. Each project needs to be evaluated before the corresponding analysis plan and price can be determined. If you want to know more about service prices or technical details, please feel free to contact us.