An improved method for detecting and delineating genomic regions with altered gene expression in cancer1Department of Clinical Genetics, Lund University Hospital, SE-221 85 Lund, Sweden 2Department of Transfusion Medicine, Lund University Hospital, SE-221 85 Lund, Sweden 3Imaging Platform, Broad Institute of Harvard University and MIT, Cambridge, MA 02142, USA 4Department of Automatic Control, Royal Institute of Technology, SE-100 44 Stockholm, Sweden 5Department of Applied Mathematics, Malmö University, Malmö, SE-205 06 Malmö, Sweden 6Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA
Genome Biology 2008, 9:R13doi:10.1186/gb-2008-9-1-r13
Subject areas: Bioinformatics, Cancer, Genome studies Additional filesAdditional file 1: Complete set of ROC curves from the simulation study Format: PDF Size: 131KB Download file This file can be viewed with: Adobe Acrobat Reader Additional file 2: Complete set of breakpoint distribution plots from the simulation study Format: PDF Size: 149KB Download file This file can be viewed with: Adobe Acrobat Reader Additional file 3: High-resolution versions of the expression maps for each of the ALL cases in the Ross et al data set, as reconstructed by the proposed algorithm. Gray: Original gene scores from the Ross data set. Blue solid: Segmented gene scores. Each row represents one case, except for the bottom row which displays the average segmentation result and DNA copy number profiles (orange) across each leukemic subtype. Format: RAR Size: 6.4MB Download file Additional file 4: Additional information about the proposed segmentation algorithms, including pseudocode. Format: PDF Size: 40KB Download file This file can be viewed with: Adobe Acrobat Reader Additional file 5: Additional data illustrating that the use of the default method parameters for CGHseg is appropriate. Format: PDF Size: 134KB Download file This file can be viewed with: Adobe Acrobat Reader |


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