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Niagara Falls, Ontario, Canada
May 21, 2007 to May 23, 2007
ISBN: 0-7695-2847-3
pp: 707-712
Jamal Alhiyafi , Wayne State University, USA
Cavitha Sebesan , Wayne State University, USA
Shiyong Lu , Wayne State University, USA
Melphine Harriott , Wayne State University, USA
Deborah Jurczyszyn , Wayne State University, USA
Raquel P. Ritchie , Wayne State University, USA
Felicitas S. Gonzales , Wayne State University, USA
Jeffrey L. Ram , Wayne State University, USA
ABSTRACT
The detection of recombination from DNA sequences is relevant to the understanding of evolutionary and molecular genetics. While programs such as GENECONV have been identified as detecting recombination more reliably than others, previous studies have not analyzed how many recombinations they fail to detect. We develop a method for testing how often such programs fail to identify recombinations and how detectability is affected by pairwise differences among the parental sequences. Recombination of sequences having a range of average pairwise differences (APD) is simulated by a stochastic method, and then the history of recombinations is compared to the recombinations identified by GENECONV. With high APD, GENECONV fails to detect ~50% of recombinations; while at a more typical intraspecies APD of 1% to 2%, \ge70% of recombinations are undetected. Quantitative results suggest corrections for estimating recombination rates more accurately and methods to detect evidence of recombination more consistently.
INDEX TERMS
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CITATION
Jamal Alhiyafi, Cavitha Sebesan, Shiyong Lu, Melphine Harriott, Deborah Jurczyszyn, Raquel P. Ritchie, Felicitas S. Gonzales, Jeffrey L. Ram, "Computational Methods for Analysis of Cryptic Recombination in the Performance of Genomic Recombination Detection Software", AINAW, 2007, Advanced Information Networking and Applications Workshops, International Conference on, Advanced Information Networking and Applications Workshops, International Conference on 2007, pp. 707-712, doi:10.1109/AINAW.2007.124
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