IMAGEne I: clustering and ranking of I.M.A.G.E. cDNA clones corresponding to known genes

MOTIVATION: To enhance the usefulness of the I.M.A.G.E. Consortium (Lennon et al., 1996, Genomics, 33, 151-152) cDNA clone collection by directed analysis and organization of their associated Expressed Sequence Tags (ESTs), thus enabling effective mining of the immense amounts of public cDNA information. RESULTS: This paper introduces the IMAGEne suite of tools, which clusters ESTs around known genes, then ranks each clone within a cluster. IMAGEne filters data from known gene sequence databases and the GenBank's EST database (Boguski and Shuler, 1995, Nature Genet., 10, 369-371). It applies biological criteria in connection with judicious use of the BLAST (Altschul et al., 1990, J. Mol. Biol., 215), FASTA (Pearson and Lipman, 1988, Proc. Natl Acad. Sci. USA, 85, 2444-2448; Pearson, 1990, Methods Enzymol., 183, 63-98; Gusfield, 1997, Algorithms on Strings, Trees, and Sequences, Cambridge University Press), and SIM (Huang et al., 1990, Comput. Appl. Biosci., 6, 373-381) tools to form known gene clusters. It then applies criteria derived from experienced biologists to select the best representative I.M.A.G.E. clone for a gene. The tool provides an intuitive Java interface for query and display of the gene and its associated clones, thus directing researchers in selecting a clone that will best enhance their research. An important product is a listing of clones that best represent all known genes. The listing will be used for re-arraying clones into minimally redundant Master Arrays. Both the listings and Master Arrays will be made available to the public, which will be a valuable resource to the genomic community in furthering discovery in the area of gene function.