False Discovery Rate for Homology Searches
While many different aspects of retrieval algorithms (e.g., BLAST) have been studied in depth, the method for determining the retrieval threshold has not enjoyed the same attention. Furthermore, with genetic databases growing rapidly, the challenges of multiple testing are escalating. In order to improve search sensitivity, we propose the use of the false discovery rate (FDR) as the method to control the number of irrelevant (“false positive”) sequences. In this paper, we introduce BLASTFDR, an extended version of BLAST that uses a FDR method for the threshold criterion. We evaluated five different multiple testing methods on a large training database and chose the best performing one, Benjamini-Hochberg, as the default for BLASTFDR. BLASTFDR achieves 14.1% better retrieval performance than BLAST on a large (5,161 queries) test database and 26.8% better retrieval score for queries belonging to small superfamilies. Furthermore, BLASTFDR retrieved only 0.27 irrelevant sequences per query compared to 7.44 for BLAST.
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- 4.Bonferroni, C.E.: Il calcolo delle assicurazioni su gruppi di teste. Tipografia del Senato (1935)Google Scholar
- 6.Chandonia, J., Hon, G., Walker, N., Lo Conte, L., Koehl, P., Levitt, M., Brenner, S.: The ASTRAL Compendium in 2004. Nucleic Acids Research 32(Database Issue), D189–D192 (2004)Google Scholar
- 10.Holm, S.: A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 65–70 (1979)Google Scholar
- 13.Wheeler, T.J., Clements, J., Eddy, S.R., Hubley, R., Jones, T.A., Jurka, J., Smit, A.F., Finn, R.D.: Dfam: a database of repetitive DNA based on profile hidden Markov models. Nucleic Acids Research 41(D1), D70–D82 (2013)Google Scholar