GeneLists is a repository of C. elegans gene lists that collects gene lists from microarray publications, the GO project, gene classes and RNAi phenotypes from WormBase, KEGG pathways, and user submissions. Web-based programs for list comparison and a link to expression data are provided. The software and gene lists are freely available.
You can view and compare the public gene lists, or you can compare your list of genes to the lists in the database.
If you want to store a gene list for repeated analyses or share it, you can load your gene list into the database. Gene lists you load can be private, shared with users you select, or publicly accessible.
To load gene lists first register and login, then load the gene list. Gene lists can be copied into the web form or uploaded as a tab-delimited text file. If you have your gene and associated annotation in a spreadsheet, save it as tab-delimited text before uploading it. Private gene lists will remain private and confidential.
The GeneLists database is open to the public and free of charge.
Gene lists are derived from user entries and genomic annotation sources. These include Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), several functional categories from WormBase, and the gene expression topomap. Gene lists from these sources are typically updated quarterly.
The GeneLists site can be used to quickly annotate a gene list. Upload a list of genes and gene aliases and descriptions are automatically associated with the gene list.
Gene lists can be compared to sets of gene lists in the database. Select 'Compare your genes to these gene lists.' or click on the Compare icon. Then select the gene list set to which your genes will be compared.
The results provide 1) the content of your gene list in genes from the comparison lists, 2) a statistical measure of the concentration of your genes in each comparison list corrected for multiple testing.
These results can be downloaded as table in tab-delimited text format.
The 'View Microarray data for these genes.' icon links to a separate site that shows clustergrams of the genes in selected published gene expression datasets.
Please contact Jim Lund if you encounter problems, have questions, or require additional information. Comments and suggestions are welcome.