@article {Stephens2005,
	title = {{Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation.}},
	journal = {American journal of human genetics},
	volume = {76},
	number = {3},
	year = {2005},
	pages = {449{\textendash}62},
	abstract = {Although many algorithms exist for estimating haplotypes from genotype data, none of them take full account of both the decay of linkage disequilibrium (LD) with distance and the order and spacing of genotyped markers. Here, we describe an algorithm that does take these factors into account, using a flexible model for the decay of LD with distance that can handle both "blocklike" and "nonblocklike" patterns of LD. We compare the accuracy of this approach with a range of other available algorithms in three ways: for reconstruction of randomly paired, molecularly determined male X chromosome haplotypes; for reconstruction of haplotypes obtained from trios in an autosomal region; and for estimation of missing genotypes in 50 autosomal genes that have been completely resequenced in 24 African Americans and 23 individuals of European descent. For the autosomal data sets, our new approach clearly outperforms the best available methods, whereas its accuracy in inferring the X chromosome haplotypes is only slightly superior. For estimation of missing genotypes, our method performed slightly better when the two subsamples were combined than when they were analyzed separately, which illustrates its robustness to population stratification. Our method is implemented in the software package PHASE (v2.1.1), available from the Stephens Lab Web site.},
	keywords = {Algorithms, Alleles, Biometry, Chromosomes, Data Interpretation, Genetic, Genomics, Genomics: statistics \& numerical data, Genotype, Haplotypes, Haplotypes: genetics, Human, Humans, Linkage Disequilibrium, Male, Models, Software, Statistical, X, X: genetics},
	issn = {0002-9297},
	doi = {10.1086/428594},
	url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1196397\&tool=pmcentrez\&rendertype=abstract},
	author = {Stephens, Matthew and Scheet, Paul}
}
@article {Tamura2011,
	title = {{MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods.}},
	journal = {Molecular biology and evolution},
	volume = {28},
	number = {10},
	year = {2011},
	month = {oct},
	pages = {2731{\textendash}9},
	abstract = {Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.},
	keywords = {Algorithms, Amino Acid Substitution, Bayes Theorem, Computational Biology, Computational Biology: methods, Computer Simulation, Data Mining, Data Mining: methods, Databases, DNA, Evolution, Genetic, Internet, Likelihood Functions, Models, Molecular, Molecular Biology, Molecular Biology: methods, Mutation, Phylogeny, Sequence Alignment, Sequence Analysis, User-Computer Interface},
	issn = {1537-1719},
	doi = {10.1093/molbev/msr121},
	url = {http://mbe.oxfordjournals.org/content/28/10/2731.abstract},
	author = {Tamura, Koichiro and Peterson, Daniel and Peterson, Nicholas and Stecher, Glen and Nei, Masatoshi and Kumar, Sudhir}
}
