Mothur is a comprehensive suite of tools for microbial ecology community. It is initiated by Dr. Patrick Schloss and his software development team in the Department of Microbiology and Immunology at The University of Michigan. For more information, see Mothur-Wiki.
The chimera.pintail command identifies putative chimeras using the pintail approach. It looks at the variation between the expected differences and the observed differences in the query sequence over several windows.
This method was written using the algorithms described in the paper "At Least 1 in 20 16S rRNA Sequence Records Currently Held in the Public Repositories is Estimated To Contain Substantial Anomalies" by Kevin E. Ashelford 1, Nadia A. Chuzhanova 3, John C. Fry 1, Antonia J. Jones 2 and Andrew J. Weightman 1.
The Pintail algorithm is a technique for determining whether a 16S rDNA sequence is anomalous. It is based on the idea that the extent of local base differences between two aligned 16S rDNA sequences should be roughly the same along the length of the alignment (having allowed for the underlying pattern of hypervariable and conserved regions known to exist within the 16S rRNA gene). In other words, evolutionary distance between two reliable sequences should be constant along the length of the gene.
In contrast, if an error-free sequence is compared with an anomalous sequence, evolutionary distance along the alignment is unlikely to be constant, especially if the anomaly in question is a chimera and formed from phylogenetically different parental sequences.
The Pintail algorithm is designed to detect and quantify such local variations and in doing so generates the Deviation from Expectation (DE) statistic. The higher the DE value, the greater the likelihood that the query is anomalous.
The algorithm works as follows
The sequence to be checked (the query) is first globally aligned with a phylogenetically similar sequence known to be error-free (the subject). At regular intervals along the resulting alignment, the local evolutionary distance between query and subject is estimated by recording percentage base mismatches within a sampling window of fixed length. The resulting array of percentages (observed percentage differences) reflects variations in evolutionary distance between the query and subject along the length of the 16S rRNA gene. Subtracting observed percentage differences from an equivalent array of expected percentage differences (predicted values for error-free sequences), we obtain a set of deviations, the standard deviation of which (Deviation from Expectation, DE) summarises the variation between observed and expected datasets. The greater the DE value, the greater the disparity there is between observed and expected percentage differences, and the more likely it is that the query sequence is anomalous.