Searching DNA databases for similarities to DNA sequences: when is a match significant?
BACKGROUND
Searching DNA sequences against a DNA database is an essential element of sequence analysis. However, few systematic studies have been carried out to determine when a match between two DNA sequences has biological significance and this is limiting the use that can be made of DNA searching algorithms.


RESULTS
A test set of DNA sequences has been constructed consisting of artificially evolved and real sequences. This set has been used to test various database searching algorithms (BLAST, BLAST2, FASTA and Smith-Waterman) on a subset of the EMBL database. The results of this analysis have been used to determine the sensitivity and coverage of all of the algorithms. Guidelines have been produced which can be used to assess the significance of DNA database search results. The Smith-Waterman algorithm was shown to have the best coverage, but the worst sensitivity, whereas the default BLASTN algorithm (word length set to 11) was shown to have good sensitivity, but poor coverage. A sensible compromise between speed, sensitivity and coverage can be obtained using either the FASTA or BLAST (word length set to 6) algorithms. However, analysis of the results also showed that no algorithm works well when the length of the probe sequence is <200 bases. In general, matches can accurately be identified between coding regions of DNA sequences when there is >35% sequence identity between the corresponding proteins. Searching a DNA sequence against a DNA sequence database can, therefore, be a useful tool in sequence analysis.


BACKGROUND
The test sets used are available via anonymous ftp from mbisg2.sbc.man.ac.uk in the directory /pub/cabios/testdata/


BACKGROUND
I.Anderson@stud.man.ac.uk; abrass@man.ac.uk
Anderson
I
I
School of Biological Sciences, University of Manchester, 2.205 Stopford Building, Oxford Road, Manchester M13 9PT, UK. I.Anderson@stud.man.ac.uk
Brass
A
A
D000465:Algorithms; D001483:Base Sequence; D016208:Databases, Factual; D016247:Information Storage and Retrieval; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012984:Software