Principal Co-ordinates Analysis

Principal Co-ordinates Analysis Online Inquiry

Introduction of Principal Co-ordinates Analysis

Principal Co-ordinates Analysis. PCoA (principal co-ordinates analysis) is a visualization method to study the similarity or difference of data. Similar to the PCA (Principal component analysis) analysis method, the main difference is that PCA is based on Euclidean distance, and PCoA is based on distances other than Euclidean distance, and finds the potential principal components of the overall difference through dimensionality reduction. In short, PCoA analysis is a non-binding data dimensionality reduction analysis method that can be used to study the similarity or difference of sample composition and observe the differences between individuals or groups.

Principal Co-ordinates Analysis Method

Commonly used principal co-ordinates analysis software includes PCoA diagram and PCoA analysis package in R language. The PCoA mapping is mainly divided into three steps. Firstly, select a specific similarity distance (such as Bray-curits, Unifrac) and calculate the distance matrix. Secondly, PCoA analysis (can be done with pcoa command), and finally PCoA graphics (can be displayed with ordiplot command or ggplot).

Principal coordinates analysis (PCoA) of bacterial community structure.Fig 1. Principal coordinates analysis (PCoA) of bacterial community structure. (Morrissey EM, et al. 2017)

Different shapes or colors in the PCoA diagram represent sample groups under different environments or conditions. The scales of the horizontal and vertical axes are relative distances and have no practical meaning. Among them, PCoA Axis 1 represents the principal coordinate that explains the largest data change, and PCoA Axis 2 represents the principal coordinate that accounts for the largest proportion of the remaining data changes. The spatial distance of sample points represents the distance between samples.

Application Field

Microbial diversity analysis.

Specific OTU (Optical Transform Unit) analysis.

In the research process of microbial community structure, such as 16S and metagenomic sequencing analysis, PCoA sequencing methods are often used to understand the similarities and differences in microbial evolution. If you have data analysis needs in this area, but you don’t have enough time to complete it. CD Genomics, as a biological information service provider, can provide you with PCoA analysis services. We can set different distance algorithms according to your needs, and make beautiful result pictures. If you have any questions or other analysis needs, please feel free to contact us.


  1. Morrissey EM, et al. Bacterial carbon use plasticity, phylogenetic diversity and the priming of soil organic matter. ISME J. 2017;11(8):1890-1899.
* For Research Use Only. Not for use in diagnostic procedures.
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