DECIPHER, a Search-Based Approach to Chimera Identification for 16S rRNA Sequences

摘要

DECIPHER is a new method for finding 16S rRNA chimeric sequences by the use of a search-based approach. The method is based upon detecting short fragments that are uncommon in the phylogenetic group where a query sequence is classified but frequently found in another phylogenetic group. The algorithm was calibrated for full sequences (fs_DECIPHER) and short sequences (ss_DECIPHER) and benchmarked against WigeoN (Pintail), ChimeraSlayer, and Uchime using artificially generated chimeras. Overall, ss_DECIPHER and Uchime provided the highest chimera detection for sequences 100 to 600 nucleotides long (79% and 81%, respectively), but Uchime's performance deteriorated for longer sequences, while ss_DECIPHER maintained a high detection rate (89%). Both methods had low false-positive rates (1.3% and 1.6%). The more conservative fs_DECIPHER, benchmarked only for sequences longer than 600 nucleotides, had an overall detection rate lower than that of ss_DECIPHER (75%) but higher than those of the other programs. In addition, fs_DECIPHER had the lowest false-positive rate among all the benchmarked programs (<0.20%). DECIPHER was outperformed only by ChimeraSlayer and Uchime when chimeras were formed from closely related parents (less than 10% divergence). Given the differences in the programs, it was possible to detect over 89% of all chimeras with just the combination of ss_DECIPHER and Uchime. Using fs_DECIPHER, we detected between 1% and 2% additional chimeras in the RDP, SILVA, and Greengenes databases from which chimeras had already been removed with Pintail or Bellerophon. DECIPHER was implemented in the R programming language and is directly accessible through a webpage or by downloading the program as an R package (http://DECIPHER.cee.wisc.edu).