Clustering Outline microarray data analysis Gene expression Microarrays

  • Slides: 39
Download presentation
Clustering

Clustering

Outline: microarray data analysis Gene expression Microarrays Preprocessing normalization scatter plots Inferential statistics t-test

Outline: microarray data analysis Gene expression Microarrays Preprocessing normalization scatter plots Inferential statistics t-test ANOVA Exploratory (descriptive) statistics distances clustering principal components analysis (PCA)

Descriptive statistics Microarray data are highly dimensional: there are many thousands of measurements made

Descriptive statistics Microarray data are highly dimensional: there are many thousands of measurements made from a small number of samples. Descriptive (exploratory) statistics help you to find meaningful patterns in the data. A first step is to arrange the data in a matrix. Next, use a distance metric to define the relatedness of the different data points. Two commonly used distance metrics are: -- Euclidean distance -- Pearson coefficient of correlation Page 203

What is a cluster? A cluster is a group that has homogeneity (internal cohesion)

What is a cluster? A cluster is a group that has homogeneity (internal cohesion) and separation (external isolation). The relationships between objects being studied are assessed by similarity or dissimilarity measures.

Background § Clustering is one of the most important unsupervised learning processes that organizing

Background § Clustering is one of the most important unsupervised learning processes that organizing objects into groups whose members are similar in some way. § Clustering finds structures in a collection of unlabeled data. § A cluster is a collection of objects which are similar between them and are dissimilar to the objects belonging to other clusters.

Motivation I • Microarray data quality checking – Does replicates cluster together? – Does

Motivation I • Microarray data quality checking – Does replicates cluster together? – Does similar conditions, time points, tissue types cluster together?

Motivation II • Cluster genes Prediction of functions of unknown genes by known ones

Motivation II • Cluster genes Prediction of functions of unknown genes by known ones

Functional significant gene clusters Two-way clustering Sample clusters Gene clusters

Functional significant gene clusters Two-way clustering Sample clusters Gene clusters

Motivation II • Cluster genes Prediction of functions of unknown genes by known ones

Motivation II • Cluster genes Prediction of functions of unknown genes by known ones • Cluster samples Discover clinical characteristics (e. g. survival, marker status) shared by samples.

Bhattacharjee et al. (2001) Human lung carcinomas m. RNA expression profiling reveals distinct adenocarcinoma

Bhattacharjee et al. (2001) Human lung carcinomas m. RNA expression profiling reveals distinct adenocarcinoma subclasses. Proc. Natl. Acad. Sci. USA, Vol. 98, 1379013795.

Hierarchical Clustering Calculate the similarity between all possible combinations of two profiles Two most

Hierarchical Clustering Calculate the similarity between all possible combinations of two profiles Two most similar clusters are grouped together to form a new cluster Calculate the similarity between the new cluster and all remaining clusters. Keys • Similarity • Clustering

Microarray Clustering 1 Outline Microarrays Hierarchical Clustering KMeansMicroarray Clustering 1 Outline Microarrays Hierarchical Clustering KMeans
Microarrays Technology behind microarrays Data analysis approaches ClusteringMicroarrays Technology behind microarrays Data analysis approaches Clustering
Microarrays Technology behind microarrays Data analysis approaches ClusteringMicroarrays Technology behind microarrays Data analysis approaches Clustering
Clustering analysis of microarray gene expression data PingClustering analysis of microarray gene expression data Ping
Clustering Gene Expression Data EMBnet DNA Microarrays WorkshopClustering Gene Expression Data EMBnet DNA Microarrays Workshop
Clustering Gene Expression Data DNA Microarrays Workshop FebClustering Gene Expression Data DNA Microarrays Workshop Feb
Clustering Gene Expression Data EMBnet DNA Microarrays WorkshopClustering Gene Expression Data EMBnet DNA Microarrays Workshop
Clustering Gene Expression Data DNA Microarrays Workshop FebClustering Gene Expression Data DNA Microarrays Workshop Feb
Table 4 Microarray gene expression data Gene GroupsTable 4 Microarray gene expression data Gene Groups
Gene Expression Dr Kevin Ahern Gene Expression GeneGene Expression Dr Kevin Ahern Gene Expression Gene
Gene Expression CHAPTER 19 Gene expression Gene regulationGene Expression CHAPTER 19 Gene expression Gene regulation
Overview of Microarray Gene Expression 2 n GeneOverview of Microarray Gene Expression 2 n Gene
Overview of Microarray Gene Expression 2 n GeneOverview of Microarray Gene Expression 2 n Gene
Microarray analysis Quantitation of Gene Expression Data toMicroarray analysis Quantitation of Gene Expression Data to
Gene expression Microarray data analysis July 22 2009Gene expression Microarray data analysis July 22 2009
Microarray Data Analysis March 2004 Differential Gene ExpressionMicroarray Data Analysis March 2004 Differential Gene Expression
Knowledgebased Analysis of Microarray Gene Expression Data usingKnowledgebased Analysis of Microarray Gene Expression Data using
Knowledgebased analysis of microarray gene expression data byKnowledgebased analysis of microarray gene expression data by
Microarray Gene Expression Data Analysis Functional Genomics ChapterMicroarray Gene Expression Data Analysis Functional Genomics Chapter
Tutorial 7 Gene expression analysis 1 Gene expressionTutorial 7 Gene expression analysis 1 Gene expression
Tutorial 7 Gene expression analysis 1 Gene expressionTutorial 7 Gene expression analysis 1 Gene expression
Analysis of microarray data Introduction Microarrays are chipsAnalysis of microarray data Introduction Microarrays are chips
Microarray data analysis Yves Moreau Microarrays n 2Microarray data analysis Yves Moreau Microarrays n 2
Analysis of microarray data Introduction Microarrays are chipsAnalysis of microarray data Introduction Microarrays are chips