Composition-based statistics and translated nucleotide searches: improving the TBLASTN module of BLAST.
BACKGROUND
TBLASTN is a mode of operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames. We present the first description of the modern implementation of TBLASTN, focusing on new techniques that were used to implement composition-based statistics for translated nucleotide searches. Composition-based statistics use the composition of the sequences being aligned to generate more accurate E-values, which allows for a more accurate distinction between true and false matches. Until recently, composition-based statistics were available only for protein-protein searches. They are now available as a command line option for recent versions of TBLASTN and as an option for TBLASTN on the NCBI BLAST web server.


RESULTS
We evaluate the statistical and retrieval accuracy of the E-values reported by a baseline version of TBLASTN and by two variants that use different types of composition-based statistics. To test the statistical accuracy of TBLASTN, we ran 1000 searches using scrambled proteins from the mouse genome and a database of human chromosomes. To test retrieval accuracy, we modernize and adapt to translated searches a test set previously used to evaluate the retrieval accuracy of protein-protein searches. We show that composition-based statistics greatly improve the statistical accuracy of TBLASTN, at a small cost to the retrieval accuracy.


CONCLUSIONS
TBLASTN is widely used, as it is common to wish to compare proteins to chromosomes or to libraries of mRNAs. Composition-based statistics improve the statistical accuracy, and therefore the reliability, of TBLASTN results. The algorithms used by TBLASTN are not widely known, and some of the most important are reported here. The data used to test TBLASTN are available for download and may be useful in other studies of translated search algorithms.
Gertz
E Michael
EM
National Center for Biotechnology Information, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA. gertz@ncbi.nlm.nih.gov
Yu
Yi-Kuo
YK
Agarwala
Richa
R
Schäffer
Alejandro A
AA
Altschul
Stephen F
SF
D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000706:statistics & numerical data*; D030561:Databases, Nucleic Acid / Q000706:statistics & numerical data*; D030562:Databases, Protein / Q000706:statistics & numerical data*; D006801:Humans; D014176:Protein Biosynthesis; D016415:Sequence Alignment; D012984:Software