Weighted clustering of called array CGH data.

@article{citeulike:2169775, abstract = {Array comparative genomic hybridization (aCGH) is a laboratory technique to measure chromosomal copy number changes. A clear biological interpretation of the measurements is obtained by mapping these onto an ordinal scale with categories loss/normal/gain of a copy. The pattern of gains and losses harbors a level of tumor specificity. Here, we present WECCA (weighted clustering of called aCGH data), a method for weighted clustering of samples on the basis of the ordinal aCGH data. Two similarities to be used in the clustering and particularly suited for ordinal data are proposed, which are generalized to deal with weighted observations. In addition, a new form of linkage, especially suited for ordinal data, is introduced. In a simulation study, we show that the proposed cluster method is competitive to clustering using the continuous data. We illustrate WECCA using an application to a breast cancer data set, where WECCA finds a clustering that relates better with survival than the original one.}, address = {Department of Mathematics, Vrije Universiteit, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands. wvanwie@few.vu.nl.}, author = {Van Wieringen, Wessel N N. and Van De Wiel, Mark A A. and Ylstra, Bauke }, citeulike-article-id = {2169775}, issn = {1465-4644}, journal = {Biostatistics}, month = {December}, posted-at = {2007-12-26 10:54:49}, priority = {2}, title = {Weighted clustering of called array CGH data.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/18156651}, year = {2007} }

TY - JOUR ID - citeulike:2169775 L3 - citeulike-article-id:2169775 TI - Weighted clustering of called array CGH data. JF - Biostatistics AD - Department of Mathematics, Vrije Universiteit, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands. wvanwie@few.vu.nl. SN - 1465-4644 N2 - Array comparative genomic hybridization (aCGH) is a laboratory technique to measure chromosomal copy number changes. A clear biological interpretation of the measurements is obtained by mapping these onto an ordinal scale with categories loss/normal/gain of a copy. The pattern of gains and losses harbors a level of tumor specificity. Here, we present WECCA (weighted clustering of called aCGH data), a method for weighted clustering of samples on the basis of the ordinal aCGH data. Two similarities to be used in the clustering and particularly suited for ordinal data are proposed, which are generalized to deal with weighted observations. In addition, a new form of linkage, especially suited for ordinal data, is introduced. In a simulation study, we show that the proposed cluster method is competitive to clustering using the continuous data. We illustrate WECCA using an application to a breast cancer data set, where WECCA finds a clustering that relates better with survival than the original one. AU - Van Wieringen, Wessel N AU - Van De Wiel, Mark A AU - Ylstra, Bauke PY - 2007/12/22/ UR - http://view.ncbi.nlm.nih.gov/pubmed/18156651 ER -