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PubMed Protein Genome Structure PopSet Taxonomy OMIM

	UniGene Links  DDD  FAQ  Query Tips  Other Links  Locus Link  HomoloGene  dbEST  Trace Archive  BLAST  CGAP	SearchPubMed Protein Nucleotide Structure Genome PopSet OMIM Taxonomy Books ProbeSet 3D Domains UniSTS Domains SNP HomoloGene Journals UniGene   Limits Index History Details UniGene Build Procedure - Transcriptome Based Clustering is the process of finding subsets of sequences that belong together within a larger set. This is done by converting discrete similarity scores to Boolean links between sequences. That is, two sequences are considered linked if their similarity exceeds a threshold. UniGene clustering proceeds in several stages, with each stage adding less reliable data to the results of the preceding stage. This staged clustering affords greater control than a more egalitarian treatment of all links between sequences. The Stages Screening for contaminants, repeats, and low-complexity sequence is performed. Low-complexity screening is performed using NCBI's Dust program. Mitochondrial and ribosomal sequences are screened for, as are vector contaminants and repetitive elements. After screening, a sequence must contain at least 100 informative bp to be a candidate for entry into UniGene. Builds are either genome based or transcript based, as described here. Gene links are found. The set of mRNA sequences is compared with itself. Sequence pairs that are sufficiently similar are linked together to form initial clusters. Links between ESTs and mRNA are added to these clusters. The set of ESTs is compared with sequences from the set of initial clusters using megaBLAST, and sufficiently similar sequence pairs are added to the clusters. Links that would join the initial mRNA-based clusters are discarded. EST to EST links are also generated and used to extend the initial clusters and to generate clusters composed solely of ESTs. Clone-based edges are added; these allow non-overlapping 5' and 3' ESTs to be assigned to the same cluster. Because of imperfect clone labeling, a single clone-ID based edge is insufficient to merge two clusters. Clone IDs that link at least two 5' ends from one cluster with at least two 3' ends from another cluster are found, and the two clusters are merged. Any resulting cluster that does not contain a sequence with a polyadenylation signal or tail is discarded. Clusters that meet these criteria are called anchored clusters, because their 3' ends are presumed to be known. ESTs that do not belong to an anchored cluster are rechecked at a lower level of stringency than in the preceding passes. An EST that passes this less stringent test is then added to the cluster that contains the sequence that is the best match to the EST; it is a guest member. Clusters of size 1 (that is, clusters that seem to identify infrequently expressed genes) are compared against the rest of the sequences in UniGene at a lower level of stringency and merged with the cluster containing the most similar sequence. The resulting clusters are compared with the preceding week's build and renumbered in an attempt to maintain continuity. Because the sequences that make up a cluster may change from week to week and because the cluster identifier may disappear (typically when two clusters merge), using the cluster identifier as a reference is ill advised. Using the GB accession numbers of the sequences that make up the cluster is a safe alternative.

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