makes it straightforward to add new datasets as they become available. Orthologous alleles. In addition to variation within an organ- ism, a key component of genome analysis is comparison with other related genomes. Fixed differences between species can be used either alone or in combination with other polymor- phism data such as the HKA test (29) to ﬁnd genomic regions that are under selection. For variant sites within a genome, the direction of the mutation can be determined by inferring the ancestral state and identifying the new (derived) allele. When deep genotyping information exists for a population and the derived allele can be inferred, the derived allele frequency (DAF) can be calculated. The theoretical basis for a shift in DAF between neutral and functional regions is presented in detail elsewhere (30), showing that the DAF spectrum is independent of population history. We have used the blastz/chain/net/liftOver process (2) to identify the chimpanzee and macaque states for each of the biallelic SNPs in dbSNP (1), in HapMap release 21 (http:// www.hapmap.org/genotypes/2006-07/rs strand/nonredunant) and in the Seattle SNP datasets (http://pga.gs.washington. edu, http://egp.gs.washington.edu) (31,32). When one of the two human alleles is the same as the chimpanzee state, that allele is most likely to be ancestral, so the other allele repre- sents a new mutation and is called the derived allele. This simple parsimony approach can lead to errors in up to 2% of the derived allele calls, due to mutation on the chimpanzee lin- eage that may still be polymorphic or could be ﬁxed, so the macaque allele is also provided to be used for conﬁrmation. As more advanced approaches to inferring the ancestral state are developed, we intend to provide these results as well. The orthologous alleles for the variant data are available in the ‘HapMap SNPs’ track and the ﬁxed differences are available in the chimpSimpleDiff table in the Genome Browser Database. Analysis of the derived alleles was used to address the question of whether sequences that have been constrained throughout mammalian evolution are currently under selec- tion in the human population. The DAF spectrum shift for non-coding elements between constrained and non- constrained regions showed that selection on the non-coding constrained elements is currently active in the human popula- tion. Furthermore, it is approximately as strong as the pressure on protein coding regions, indicating that the non- coding constrained regions are likely to be functional (33). Thus, examining the DAF spectrum can identify candidate functional regions for further scrutiny during the follow-up of association studies and help us develop a complete under- standing of locus-speciﬁc biology. Self alignments and repeats. Duplications and repeats play important roles in both genomic disease and gene evolution, as replication slippage leads to copy number differences and retrotransposition-mediated duplications allow the birth of new gene variants. In addition, repetitive complexity can lead to misassignment and misassembly of genome sequence (34), which may confound interpretation within these regions. The Genome Browser provides results from several approaches to look for these types of features that are biologically interesting but can be a source of error for some analyses. Nucleic Acids Research, 2007, Vol. 35, Database issue D719 The ‘Self Chain’ track shows alignments of the human genome with itself, using a scoring system that allows longer gaps than traditional afﬁne scoring systems. These can be used to identify genomic intervals that are not unique in the genome. Similarly, the ‘Segmental Dups’ are experimentally validated blocks of duplicated genomic DNA, typically ranging in size from 1 to 200 kb (35). They often contain sequence features such as high copy repeats and gene sequences with intron–exon structure. Arian Smit’s RepeatMasker (http://www.repeatmasker.org) program (36,37) screens DNA sequences for interspersed repeats, low complexity DNA sequences and other repeat elements. These results are avail- able in the ‘RepeatMasker’ track. Similarly, simple tandem repeats identiﬁed by the Tandem Repeat Finder (38) are avail- able in the ‘Simple Repeats’ track. These repeat regions can lead to genotyping errors as cross-hybridization is more likely. DATA DISPLAY AND AVAILABILITY As described elsewhere, the Genome Browser (28,39–41) and the Table Browser (42) are useful tools for the display, analysis and retrieval of genome scale biological data. All of these data are available for display in the Genome Browser at http://genome.ucsc.edu, for interactive analysis through the Table Browser at http://genome.ucsc.edu/cgi-bin/hgTables, and via direct access to text ﬁles on our download site at http://hgdownload.cse.ucsc.edu/. WEB SITE REFERENCES http://genome.ucsc.edu; UCSC Genome Browser. http://genome.ucsc.edu/cgi-bin/hgTables; UCSC Table Browser. http://hgdownload.cse.ucsc.edu/; UCSC Database Downloads. ACKNOWLEDGEMENTS We acknowledge support from the National Human Genome Research Institute (NHGRI; for D. J. Thomas, B. L. Rhead, R. M. Kuhn, W. J. Kent and H. Trumbower), the Howard Hughes Medical Institute (HHMI; for D. Haussler), the National Cancer Institute (NCI; for H. Trumbower) and A. D. Kern’s NIH Kirschstein-NRSA postdoctoral fellowship. We would like to thank the many collaborators who have contributed annotation data to our project, as well as our users for their feedback and support. We would also like to thank the dedicated system administrators who have provided an excellent computing environment: Jorge Garcia, Patrick Gavin, Chester Manuel, Victoria Lin and Paul Tatarsky. Funding to pay the Open Access publication charges for this article was provided by NHGRI. Conflict of interest statement. D. J. Thomas, H. Trumbower, B. L. Rhead, R. M. Kuhn, D. Haussler, and W. J. Kent receive royalties from the sale of UCSC Genome Browser source code licenses to commercial entities. REFERENCES 1. Sherry,S.T., Ward,M.H., Kholodov,M., Baker,J., Phan,L., Smigielski,E.M. and Sirotkin,K. (2001) dbSNP: the NCBI database of genetic variation. Nucleic Acids Res., 29, 308–311.