RASCAL: rapid scanning and correction of multiple sequence alignments. MOTIVATION: Most multiple sequence alignment programs use heuristics that sometimes introduce errors into the alignment. The most commonly used methods to correct these errors use iterative techniques to maximize an objective function. We present here an alternative, knowledge-based approach that combines a number of recently developed methods into a two-step refinement process. The alignment is divided horizontally and vertically to form a ’lattice’ in which well aligned regions can be differentiated. Alignment correction is then restricted to the less reliable regions, leading to a more reliable and efficient refinement strategy. RESULTS: The accuracy and reliability of RASCAL is demonstrated using: (i) alignments from the BAliBASE benchmark database, where significant improvements were often observed, with no deterioration of the existing high-quality regions, (ii) a large scale study involving 946 alignments from the ProDom protein domain database, where alignment quality was increased in 68% of the cases; and (iii) an automatic pipeline to obtain a high-quality alignment of 695 full-length nuclear receptor proteins, which took 11 min on a DEC Alpha 6100 computer. AVAILABILITY: RASCAL is available at ftp://ftp-igbmc.u-strasbg.fr/pub/RASCAL.
Keywords for this software
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- DeBlasio, Dan; Kececioglu, John: Parameter advising for multiple sequence alignment (2017)
- Wen, Zhining; Wang, Kelong; Li, Menglong; Nie, Fusheng; Yang, Yi: Analyzing functional similarity of protein sequences with discrete wavelet transform (2005)
- Wang, Yi; Li, Kuo-Bin: An adaptive and iterative algorithm for refining multiple sequence alignment (2004)