Gentle masking of low-complexity sequences improves homology search.
Detection of sequences that are homologous, i.e. descended from a common ancestor, is a fundamental task in computational biology. This task is confounded by low-complexity tracts (such as atatatatatat), which arise frequently and independently, causing strong similarities that are not homologies. There has been much research on identifying low-complexity tracts, but little research on how to treat them during homology search. We propose to find homologies by aligning sequences with "gentle" masking of low-complexity tracts. Gentle masking means that the match score involving a masked letter is min(0,S), where S is the unmasked score. Gentle masking slightly but noticeably improves the sensitivity of homology search (compared to "harsh" masking), without harming specificity. We show examples in three useful homology search problems: detection of NUMTs (nuclear copies of mitochondrial DNA), recruitment of metagenomic DNA reads to reference genomes, and pseudogene detection. Gentle masking is currently the best way to treat low-complexity tracts during homology search.
Computational Biology Research Center, Institute for Advanced Industrial Science and Technology, Koto-ku, Tokyo, Japan. martin@cbrc.jp
Martin C
MC
Frith
D000595:Amino Acid Sequence; D000818:Animals; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000235:genetics; D057225:Data Mining / Q000379:methods*; D006801:Humans; D056186:Metagenomics; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry / Q000235:genetics; D017385:Sequence Homology
D011506:Proteins; D004247:DNA