ESTmapper: Efficiently Aligning DNA Sequences to Genomes
Xue Wu, Woei-Jyh Lee, Chau‐Wen Tseng
Abstract
Xue Wu, Woei-Jyh Lee, Chau‐Wen Tseng
Abstract
With improvements in technology, scientists are able to sequence the full DNA (genome) of an increasing number of organisms. One way biologists can take advantage of this genomic sequence data is to use it in conjunction with expressed sequence tag (EST) information to find genes and their splice sites. We describe how ESTmapper uses an eager write-only top-down (WOTD) suffix tree to efficiently align DNA sequences against genomes, and compare its precision and performance against popular techniques for DNA alignment (BLAT, sim4, Spidey, BLAST, megaBLAST) and EST clustering (TGICL and PaCE). Experimental results show that ESTmapper is 3 to 1000 times faster than current techniques for aligning and clustering DNA sequences, and produces alignments of comparable or better quality.
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With improvements in technology, scientists are able to sequence the full DNA (genome) of an increasing number of organisms. One way biologists can take advantage of this genomic sequence data is to use it in conjunction with expressed sequence tag (EST) information to find genes and their splice sites. We describe how ESTmapper uses an eager write-only top-down (WOTD) suffix tree to efficiently align DNA sequences against genomes, and compare its precision and performance against popular techniques for DNA alignment (BLAT, sim4, Spidey, BLAST, megaBLAST) and EST clustering (TGICL and PaCE). Experimental results show that ESTmapper is 3 to 1000 times faster than current techniques for aligning and clustering DNA sequences, and produces alignments of comparable or better quality.
Key concepts: Genome, Suffix tree, Cluster analysis, Computer science, Sequence (biology), Computational biology, DNA sequencing, DNA