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Old 06-13-2013, 08:31 AM   #3
priya
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Location: sweden

Join Date: Apr 2013
Posts: 57
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Hi, Hierachical clustering is a nice way of representing the samples difference and to look at the relationship between the samples in the initial stages of how raw data look like. Although the way the clusters are formed in tree corresponds to how we calculate the distance measure(Single/Wards/Complete/Average) and the type of method (Euclidean/Pearson)used to calculate the distances between two data points . I have 16 RNA-seq samples, tried to perform hierarchical clustering on dataset, by using Euclidean distance measure and Wards methods, the tree genertated was different if i use Single-linkage method. Although by Single linkage method the tree is making sense in terms of biology, but I am not completely clear of the point which will be the optimal method to consider when we look at the RNA-seq data having count values??

Any suggestions please??
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