Published on February 17, 2014
Biology Chemistry Informatics Evaluation of metabolomic sample processing methods using hierarchical cluster analysis Cluster Analysis Goal: Use hierarchical cluster analysis (HCA) to evaluate data variance structure Topics: 1. Evaluate sample and variable similarities 2. Identify the effect of data transformation, distance and linkage methods on data similarities
Clustering data Biology Chemistry Informatics Cluster Analysis Goal: Use HCA to cluster samples (Use DATA: Pumpkin data 1.csv) Visualize: 1. Sample (row) raw similarities as a heat map 2. Annotate heatmap with extraction and treatment type 3. Select cluster distance and linkage method to cluster the samples 4. Determine the effect of data transformations on the cluster structure (view as a dendrogram) Exercises: 1. What factor, extraction or treatment, has the greatest contribution to the data variance structure? 2. Describe the effect of clustering raw data or sample correlations
Biology Chemistry Raw data matrix visualized as a heatmap samples variables Cluster Analysis Informatics
Raw data matrix organized by HCA Biology Chemistry Informatics Cluster Analysis •ACN:/IPA/water|fresh and MeOH/CH3Cl/water|dried display distinct patterns in metabolites which are most similar to each other •Sample similarities are linked to metabolite magnitudes
Biology Chemistry Clustering based on sample correlations (spearman) Informatics Cluster Analysis •100% MeOH/fresh is the most dissimilar protocol from all others •ACN:/IPA/water and MeOH/CH3Cl/water are most similar to each other •Sample similarities are decoupled from metabolite magnitudes
Clustering metabolites Biology Chemistry Informatics Goal 2: Use HCA to evaluate metabolite similarities Cluster Analysis Visualize: 1.Z-scaled and correlation based variable clustering 2.Use a dendrogram to extract variable clusters 3.Select two variables from the same cluster and visualize their correlation Exercise: 1.Do the clustered variables share biological functions? 2.Which type of correlation is most robust to outliers? 3.Are the correlations for the visualized variable independent of extraction/treatment?
Z-scaled variable clusters Biology Chemistry Cluster Analysis Informatics
Correlation based variable clusters Biology Chemistry Cluster Analysis Informatics
Biology Chemistry Extraction of clusters of correlated variables Informatics less similar most similar cluster Cluster Analysis lowest common branch height more similar
Biology Chemistry Cluster Analysis Informatics Correlation among cluster members (4)
Die so gefundenen Gruppen von „ähnlichen“ Objekten werden als Cluster ... Statistical Analysis ... , 3 Edition, Kapitel 8.2.2, Gabler ...
Business Analytics Business Analytics 2. Cluster Analysis Lars Schmidt-Thieme Information Systems and Machine Learning Lab (ISMLL) University of Hildesheim ...
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar ...
Cluster analysis is a method for separating data into clusters or groups in a situation where no prior information about a grouping structure is available ...
cluster analysis, k-means cluster, and two-step cluster. ... Figure 16-2.) The largest distance, 0.25, occurs between the Japanese and Canadian judges.
This is a two-step cluster analysis using SPSS. I do this to demonstrate how to explore profiles of responses. These profiles can then be used ...
The Product. 2/CLU is our tool for quick, easy and stable segmentation of a large number of objects into homogeneous clusters. Features in brief
The Cluster Analysis is an explorative analysis that tries to identify structures within the data. Cluster analysis is also called segmentation analysis.
490 Chapter 8 Cluster Analysis: Basic Concepts and Algorithms broad categories of algorithms and illustrate a variety of concepts: K-means, agglomerative ...
The term cluster analysis (first used by Tryon, ... If r and p are equal to 2, then this distance is equal to the Euclidean distance. Percent disagreement.