Gene Shaving for clustering similar genes (Paper Explained) скачать в хорошем качестве

Gene Shaving for clustering similar genes (Paper Explained)

*Overview*: Identifying clusters of similar genes is an essential task in medicine. The standard approach of hierarchical clustering has many limitations, such as assigning a gene to only one cluster. Gene shaving proposes an unsupervised iterative procedure of finding clusters of genes with similar expression patterns and high variance across samples. The method can also incorporate supervision to find gene clusters relevant for specific applications. https://www.ncbi.nlm.nih.gov/pmc/arti... *Authors*: Trevor Hastie, Robert Tibshirani, Michael B Eisen, Ash Alizadeh, Ronald Levy, Louis Staudt, Wing C Chan, David Botstein, and Patrick Brown *Abstract*: Large gene expression studies, such as those conducted using DNA arrays, often provide millions of different pieces of data. To address the problem of analyzing such data, we describe a statistical method, which we have called 'gene shaving.' The method identifies subsets of genes with coherent expression patterns and large variation across conditions. Gene shaving differs from hierarchical clustering and other widely used methods for analyzing gene expression studies in that genes may belong to more than one cluster, and the clustering may be supervised by an outcome measure. The technique can be 'unsupervised', that is, the genes and samples are treated as unlabeled, or partially or fully supervised by using known properties of the genes or samples to assist in finding meaningful groupings. We illustrate the use of the gene shaving method to analyze gene expression measurements made on samples from patients with diffuse large B-cell lymphoma. The method identifies a small cluster of genes whose expression is highly predictive of survival. The gene shaving method is a potentially useful tool for exploration of gene expression data and identification of interesting clusters of genes worth further investigation. 00:00 - Introduction 00:35 - Overview & Gene clusters results 08:13 - Method 24:14 - Supervised Gene Shaving 27:50 - Conclusion Connect with me:   / andreimargeloiu