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- W2143119188 abstract "Abstract Motivation: To devise a method that, unlike available methods, directly measures variations in phylogenetic signals in gene sequences that result from recombination, tests the significance of the signal variations and distinguishes misleading signals. Results: We have developed a method, that we call ‘sister-scanning’, for assessing phylogenetic and compositional signals in the various patterns of identity that occur between four nucleotide sequences. A Monte Carlo randomization is done for all columns (positions) within a window and batchmode documentclass[fleqn,10pt,legalpaper]{article} usepackage{amssymb} usepackage{amsfonts} usepackage{amsmath} pagestyle{empty} begin{document} (Z) end{document}-scores are obtained for four real sequences or three real sequences with an outlier that is also randomized. The usefulness of the approach is demonstrated using tobamovirus and luteovirus sequences. Contradictory phylogenetic signals were distinguished in both datasets, as were regions of sequence that contained no clear signal or potentially misleading signals related to compositional similarities. In the tobamovirus dataset, contradictory phylogenetic signals were separated by coding sequences up to a kilobase long that contained no clear signal. Our re-analysis of this dataset using sister-scanning also yielded the first evidence known to us of an inter-species recombination site within a viral RNA-dependent RNA polymerase gene together with evidence of an unusual pattern of conservation in the three codon positions. Availability: A program package, SiScan, for use under MS-DOS can be downloaded from http://life.anu.edu.au/with test data and instructions. Contact: mgibbs@rsbs.anu.edu.au; johna@rsbs.anu.edu.au; gibbs@rsbs.anu.edu.au * To whom correspondence should be addressed." @default.
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- W2143119188 date "2000-07-01" @default.
- W2143119188 modified "2023-10-14" @default.
- W2143119188 title "Sister-Scanning: a Monte Carlo procedure for assessing signals in recombinant sequences" @default.
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- W2143119188 doi "https://doi.org/10.1093/bioinformatics/16.7.573" @default.
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