Exploratory and inferential analysis of gene cluster neighborhood graphs Export

@article{citeulike:5781741, abstract = {BACKGROUND:Many different cluster methods are frequently used in gene expression data analysis to find groups of co-expressed genes. However, cluster algorithms with the ability to visualize the resulting clusters are usually preferred. The visualization of gene clusters gives practitioners an understanding of the cluster structure of their data and makes it easier to interpret the cluster results.RESULTS:In this paper recent extensions of R package gcExplorer are presented. gcExplorer is an interactive visualization toolbox for the investigation of both the overall cluster structure and single clusters. The different visualization options including arbitrary node and panel functions are described in detail. Finally the toolbox can be used to investigate the quality of a given clustering graphically as well as theoretically by testing the association between a partition and a functional group under study.DISCUSSION:It is shown that gcExplorer is a very helpful tool for a general exploration of microarray experiments. The identification of potentially interesting gene candidates or functional groups is substantially accelerated and eased. Inferential analysis on a cluster solution is used to judge its ability to provide insight into the underlying mechanistic biology of the experiment.}, author = {Scharl, Theresa and Voglhuber, Ingo and Leisch, Friedrich}, citeulike-article-id = {5781741}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/1471-2105-10-288}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19751523}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19751523}, doi = {10.1186/1471-2105-10-288}, issn = {1471-2105}, journal = {BMC Bioinformatics}, number = {1}, pages = {288+}, posted-at = {2009-09-15 07:23:41}, priority = {2}, title = {Exploratory and inferential analysis of gene cluster neighborhood graphs}, url = {http://dx.doi.org/10.1186/1471-2105-10-288}, volume = {10}, year = {2009} }

TY - JOUR ID - citeulike:5781741 L3 - citeulike-article-id:5781741 N2 - BACKGROUND:Many different cluster methods are frequently used in gene expression data analysis to find groups of co-expressed genes. However, cluster algorithms with the ability to visualize the resulting clusters are usually preferred. The visualization of gene clusters gives practitioners an understanding of the cluster structure of their data and makes it easier to interpret the cluster results.RESULTS:In this paper recent extensions of R package gcExplorer are presented. gcExplorer is an interactive visualization toolbox for the investigation of both the overall cluster structure and single clusters. The different visualization options including arbitrary node and panel functions are described in detail. Finally the toolbox can be used to investigate the quality of a given clustering graphically as well as theoretically by testing the association between a partition and a functional group under study.DISCUSSION:It is shown that gcExplorer is a very helpful tool for a general exploration of microarray experiments. The identification of potentially interesting gene candidates or functional groups is substantially accelerated and eased. Inferential analysis on a cluster solution is used to judge its ability to provide insight into the underlying mechanistic biology of the experiment. IS - 1 JF - BMC Bioinformatics SN - 1471-2105 TI - Exploratory and inferential analysis of gene cluster neighborhood graphs VL - 10 SP - 288 AU - Scharl, Theresa AU - Voglhuber, Ingo AU - Leisch, Friedrich PY - 2009/// UR - http://dx.doi.org/10.1186/1471-2105-10-288 ER -