title: A sequence sub-sampling algorithm increases the power to detect distant homologues.
abstract: Searching databases for distant homologues using alignments instead of individual sequences increases the power of detection. However, most methods assume that protein evolution proceeds in a regular fashion, with the inferred tree of sequences providing a good estimation of the evolutionary process. We investigated the combined HMMER search results from random alignment subsets (with three sequences each) drawn from the parent alignment (Rand-shuffle algorithm), using the SCOP structural classification to determine true similarities. At false-positive rates of 5%, the Rand-shuffle algorithm improved HMMER's sensitivity, with a 37.5% greater sensitivity compared with HMMER alone, when easily identified similarities (identifiable by BLAST) were excluded from consideration. An extension of the Rand-shuffle algorithm (Ali-shuffle) weighted towards more informative sequence subsets. This approach improved the performance over HMMER alone and PSI-BLAST, particularly at higher false-positive rates. The improvements in performance of these sequence sub-sampling methods may reflect lower sensitivity to alignment error and irregular evolutionary patterns. The Ali-shuffle and Rand-shuffle sequence homology search programs are available by request from the authors.
authors: Department of Clinical Pharmacology, Bioinformatics Group, Royal College of Surgeons in Ireland, 123 St Stephens Green, Dublin 2, Ireland. kjohnston@rcsi.ie
authors: Catrióna R
authors: CR
authors: Johnston
authors: Denis C
authors: DC
authors: Shields
mesh_terms: D000465:Algorithms; D016207:Cytokines / Q000737:chemistry / Q000235:genetics; D019143:Evolution, Molecular; D006801:Humans; D011506:Proteins / Q000737:chemistry / Q000145:classification; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid
chemical_list: D016207:Cytokines; D011506:Proteins