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Association Analysis for Large-Scale Gene Set Data 293.6. Tissue Expression and Chromosomal Distribution of the Gene SetAssociations are not quantified in these two analyses. The tissue-expressionpattern for the whole gene set is visualized based on the CGAP project publiclyavailable data. The chromosomal distribution function is visualized based onthe UCSC annotation.1. Press the “Tissue Expression Bar Chart” or “Chromosomal distribution Chart”button (this will open a new window).2. Click the tissue/chromosome bar representing the tissue/chromosome of interestto retrieve genes associated with the tissue/chromosome (this also opens a newwindow).3. For the tissue expression analysis, the significance of enrichment for each gene inthe gene list is provided (see Note 9 for the evaluation of the significance ofenrichment). One could also click on each member of the list to see its tissuedistribution.4. Click “SAVE” button to create a new gene set.3.7. Advanced Batch Mode Data Mining With GeneKeyDBOften it is important to find associations for which there is no tool available.In such case installing and querying one of the genome annotation databasesis necessary. As a rule, most annotation databases are bulky. Two systems,GeneKeyDB and BioMART, provide a lighter solution to this problem. Designingcustom-associative analysis based on either GeneKeyDB or BioMART requireshigher level of computer proficiency and will not be discussed herein. Aguide on installing GeneKeyDB locally is available at http://bioinfo.vanderbilt.edu/genekeydb/mirroring.4. Notes1. Mailing lists and forums: mailing lists and forums can be used to request help,new features, and to submit bugs. Forums and mailing lists can be accessedthrough sourceforge:Sourceforge projects:GenekeyDB: http://sourceforge.net/projects/genekeydb/.Mailing lists:GeneKeyDB: genekeydb-faqs@lists.sourceforge.net.WebGestalt: geneset-wg-faq@lists.sourceforge.net.GOTM: geneset-gotm-faq @lists.sourceforge.net.2. ID conversion: the difficulties in ID conversion arise from the fact that the relationshipsamong different IDs are not always one-to-one. For example, one unigeneidentifier can map to more than one Entrez gene ID. Therefore, mapping to Entrezgene ID through unigene might be unreliable and would produce unreliable finalresults unless the many-to-one relationships are taken into account. The same istrue for other IDs as well, such as oligo microarray IDs.