Evaluation of methods for detecting recombination from DNA sequences: Computer simulations

By David Posada, Keith A. Crandall. Proceedings of the National Academy of Sciences of the United States of America, 2001

1,529 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/494c52af3033c767ea70339b7b566450d8befa50

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. David Posada
2. Sergei L. Kosakovsky Pond
3. Hervé Philippe
4. Darren P. Martin
5. Maciej F. Boni
6. T. C. Bruen
7. David Bryant
8. Michal Feldman

In Molecular Biology

1. Sergei L. Kosakovsky Pond
2. Simon D. W. Frost
3. David Posada
4. Hervé Philippe
5. T. C. Bruen
6. David Bryant
7. Ben Murrell
8. Darren P. Martin

Citations in the corpus

• Evaluation of methods for detecting recombination from DNA sequences: empirical data. (2002, methodology): “Recombination among sequences has been simulated using the co-alescent with recombination (Brown et al. 2001; Posada and Crandall 2001; Wiuf, Christensen, and Hein 2001) or using a more classical forward approach (Maynard Smith 1999 .”
• Paraphyly of Tarasa (Malvaceae) and Diverse Origins of the Polyploid Species (2003, methodology): “The program GeneConv (Sawyer 1999) was used to test for potential recombination of ITS sequences between taxa (Posada and Crandall 2001).”
• An Exact Nonparametric Method for Inferring Mosaic Structure in Sequence Triplets (2007, methodology): “Power and false positives: We compared the power and false-positive rates of our D-method to the 14 methods evaluated in Posada and Crandall (2001).”
• A Simple and Robust Statistical Test for Detecting the Presence of Recombination (2006, methodology): “Without population growth, the power to detect recombination of all six methods generally increases as a function of both sequence diversity and the rate of recombination, similar to earlier observations (Posada and Crandall 2001; Wiuf et al. 2001).”
• Automated phylogenetic detection of recombination using a genetic algorithm. (2006, methodology): “Panel C shows the number of datasets (out of 100) which were classified as recombinant by: the best performing method of the 14 Posada and Crandall (2001); the composite likelihood permutation test (McVean, Awadalla and Fearnhead, 2002), using benchmark results from Carvajal-Rodriguez, Crandall and…”
• RDP4: Detection and analysis of recombination patterns in virus genomes (2015, methodology): “Besides the original RDP method (Martin and Rybicki 2000), these methods include BOOTSCAN (Salminen et al. 1995), MAXCHI (Maynard Smith 1992), CHIMAERA (Posada and Crandall 2001), 3 SEQ (Boni, Posada, and Feldman 2007), GENECONV (Padidam, Sawyer, and Fauquet 1999), LARD (Holmes, Worobey, and Rambaut”
• RDP2: recombination detection and analysis from sequence alignments (2005, methodology): “Among the new inclusions are many methods that have performed well in comparative tests (Drouin et al., 1999; Posada and Crandall, 2001; Posada, 2000).”