Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20926
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dc.contributor.authorVAN MOERBEKE, Marijke-
dc.date.accessioned2016-04-04T06:35:36Z-
dc.date.available2016-04-04T06:35:36Z-
dc.date.issued2016-
dc.identifier.urihttp://hdl.handle.net/1942/20926-
dc.description.abstractSeveral integrative data methods in which information of objects from different data sources can be combined are included in the IntClust package. As a single data source is limited in its point of view, this provides more insight and the opportunity to investigate how the variables are interconnected. Clustering techniques are to be applied to the combined information. For now, only agglomerative hierarchical clustering is implemented. Further, differential gene expression and pathway analysis can be conducted on the clusters. Plotting functions are available to visualize and compare results of the different methods.-
dc.language.isoen-
dc.rightsGPL-3-
dc.subject.otherclustering-
dc.titleIntClust: a software package for an integrated data analysis via clustering-
dc.typeOther-
local.bibliographicCitation.jcatO-
dc.relation.referencesFODEH, J. S., BRANDT, C., LUONG, B. T., HADDAD, A., SCHULTZ, M., MURPHY, T., KRAUTHAMMER, M. (2013). Complementary Ensemble Clustering of Biomedical Data. J Biomed Inform. 46(3) pp.436-443.PERUALILA-TAN, N., SHKEDY, Z., TALLOEN, W., GOEHLMANN, H. W. H., QSTAR Consortium, VAN MOERBEKE, M., KASIM, A., (in press). Weighted-Similarity Based Clustering of Chemical Structure and Bioactivity Data in Early Drug Discovery. Journal of Bioinformatics and Computational Biology.SMYTH, G. K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology. 3(1).LI, Y., TU, K., ZHENG, S., WANG, J., LI, Y., LI, X. (2011). Association of Feature Gene Expression with Structural Fingerprints of Chemical Compounds. Journal of Bioinformatics and Computational biology. 9(4). pp. 503-519. MAECHLER, M., ROUSSEEUW, P., STRUYF, A., HUBERT, M. (2014). cluster: Cluster Analysis Basics and Extensions. R package version 1.15.3. TALLOEN, W., VERBEKE, T. (2011). a4: Automated Affymetrix Array Analysis Umbrella Package. R package version 1.14.0. WANG, B., MEZLINI, M. A., DEMIR, F., FIUME, M., TU, Z., BRUDNO, M., HAIBE-KAINS, B., GOLDENBERG, A. (2014). Similarity Network Fusion for aggregating data types on a genomic scale. Nature. 11(3) pp. 333-337.RAVINDRANATH, A. C.,PERUALILA-TAN, N., KASIM, A.,DRAKAKIS, G., LIGGI, S., BREWERTON, S. C.,MASON, D., BODKIN, M. J., EVANS, D. A., BHAGWAT, A. TALLOEN, W., GOHLMANN, H. W. H., QSTAR Consortium, SHKEDY, Z., BENDER, A. (2015). Connecting gene expression data from connectivity map and in silico target predictions for small molecule mechanism-of-action analysis. Mol. BioSyst. Available at: <http://pubs.rsc.org/En/content/ articlelanding/2015/mb/c4mb00328d#!divAbstract>-
local.type.specifiedSoftware Package-
dc.identifier.urlhttps://cran.r-project.org/web/packages/IntClust/index.html-
item.fulltextWith Fulltext-
item.fullcitationVAN MOERBEKE, Marijke (2016) IntClust: a software package for an integrated data analysis via clustering.-
item.accessRightsOpen Access-
item.contributorVAN MOERBEKE, Marijke-
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