GATA: A graphic alignment tool for comparative sequenceanalysis
Several problems exist with current methods used to align DNA sequences for comparative sequence analysis. Most dynamic programming algorithms assume that conserved sequence elements are collinear. This assumption appears valid when comparing orthologous protein coding sequences. Functional constraints on proteins provide strong selective pressure against sequence inversions, and minimize sequence duplications and feature shuffling. For non-coding sequences this collinearity assumption is often invalid. For example, enhancers contain clusters of transcription factor binding sites that change in number, orientation, and spacing during evolution yet the enhancer retains its activity. Dotplot analysis is often used to estimate non-coding sequence relatedness. Yet dot plots do not actually align sequences and thus cannot account well for base insertions or deletions. Moreover, they lack an adequate statistical framework for comparing sequence relatedness and are limited to pairwise comparisons. Lastly, dot plots and dynamic programming text outputs fail to provide an intuitive means for visualizing DNA alignments.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Director. Office of Science; American CancerSociety
- DOE Contract Number:
- DE-AC02-05CH11231
- OSTI ID:
- 861245
- Report Number(s):
- LBNL-56803; R&D Project: GHEIS3; BnR: 600305000; TRN: US200601%%738
- Journal Information:
- BMC Bioinformatics, Vol. 6, Issue 9; Related Information: Journal Publication Date: 2005
- Country of Publication:
- United States
- Language:
- English
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