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RASCAL: rapid scanning and correction of multiple sequence alignments
J D Thompson1, J C Thierry, O Poch
1Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire (CNRS/INSERM/ULP), B.P. 10142, 67404 Illkirch Cedex, France.
Bioinformatics (Oxford, England)
|June 13, 2003
Summary
This study introduces RASCAL, a novel knowledge-based method for refining multiple sequence alignments. RASCAL improves alignment accuracy and reliability by focusing corrections on less reliable regions, outperforming traditional iterative techniques.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Multiple sequence alignment (MSA) programs often introduce errors due to heuristic methods.
- Iterative techniques are common for correcting alignment errors but can be inefficient.
- A new knowledge-based approach offers an alternative refinement strategy.
Purpose of the Study:
- To present RASCAL, a two-step refinement process for multiple sequence alignments.
- To improve the reliability and efficiency of sequence alignment correction.
- To offer an alternative to iterative error correction methods.
Main Methods:
- A knowledge-based, two-step refinement strategy.
- Dividing alignments into a 'lattice' to differentiate well-aligned regions.
- Restricting alignment correction to less reliable regions.
Main Results:
- RASCAL demonstrated significant improvements on BAliBASE alignments.
- Alignment quality increased in 68% of 946 ProDom protein domain database alignments.
- A high-quality alignment of 695 nuclear receptor proteins was generated in 11 minutes.
Conclusions:
- RASCAL provides a more reliable and efficient alignment refinement strategy.
- The method successfully improves alignment quality without degrading existing high-quality regions.
- RASCAL offers a valuable tool for bioinformatics research and large-scale sequence analysis.