% Generated by Paperpile. Check out http://paperpile.com for more information.
% BibTeX export options can be customized via Settings -> BibTeX.

@UNPUBLISHED{Kelleher2018-fu,
  title    = "Efficient pedigree recording for fast population genetics
              simulation",
  author   = "Kelleher, Jerome and Thornton, Kevin and Ashander, Jaime and
              Ralph, Peter",
  abstract = "In this paper we describe how to efficiently record the entire
              genetic history of a population during a forwards-time,
              individual-based population genetics simulation. This
              dramatically reduces the computational burden of tracking
              individual genomes by simulating only those loci that may affect
              reproduction (those having non-neutral variants), and recording
              history as a succinct tree sequence as introduced in the software
              package msprime, on which neutral mutations can be quickly placed
              afterwards. We implement the method in two popular forwards-time
              simulation frameworks, which speeds up large, whole-genome
              simulations by one to two orders of magnitude. In addition to
              speed, the method has several advantages: (1) All marginal
              genealogies of the simulated individuals are recorded, rather
              than just genotypes. (2) A population of N individuals with M
              polymorphic sites can be stored in O(N log N + M) space, making
              it feasible to store a simulation9s entire final generation (and
              its9 history) rather than only a subset. (3) A simulation can
              easily be initialized with a more efficient coalescent simulation
              of deep history. To make these possible, we introduce the msprime
              Tables API, which allows for the efficient interchange of tree
              sequences between modular program components, and provide an
              algorithm to quickly simplify a tree sequence by removing history
              irrelevant to a given set of genomes.",
  journal  = "bioRxiv",
  pages    = "248500",
  month    =  jan,
  year     =  2018,
  keywords = "MIRA2018;pylibseq\_manual;fwdpp\_manual",
  language = "en"
}

@ARTICLE{Kelleher2016-cb,
  title    = "Efficient Coalescent Simulation and Genealogical Analysis for
              Large Sample Sizes",
  author   = "Kelleher, Jerome and Etheridge, Alison M and McVean, Gilean",
  abstract = "A central challenge in the analysis of genetic variation is to
              provide realistic genome simulation across millions of samples.
              Present day coalescent simulations do not scale well, or use
              approximations that fail to capture important long-range linkage
              properties. Analysing the results of simulations also presents a
              substantial challenge, as current methods to store genealogies
              consume a great deal of space, are slow to parse and do not take
              advantage of shared structure in correlated trees. We solve these
              problems by introducing sparse trees and coalescence records as
              the key units of genealogical analysis. Using these tools, exact
              simulation of the coalescent with recombination for
              chromosome-sized regions over hundreds of thousands of samples is
              possible, and substantially faster than present-day approximate
              methods. We can also analyse the results orders of magnitude more
              quickly than with existing methods.",
  journal  = "PLoS Comput. Biol.",
  volume   =  12,
  number   =  5,
  pages    = "e1004842",
  month    =  may,
  year     =  2016,
  keywords = "MIRA2018;Optimum shift paper;pylibseq\_manual;fwdpp\_manual",
  language = "en"
}

@ARTICLE{Thornton2014-hx,
  title    = "A C++ template library for efficient forward-time population
              genetic simulation of large populations",
  author   = "Thornton, Kevin R",
  abstract = "fwdpp is a C++ library of routines intended to facilitate the
              development of forward-time simulations under arbitrary mutation
              and fitness models. The library design provides a combination of
              speed, low memory overhead, and modeling flexibility not
              currently available from other forward simulation tools. The
              library is particularly useful when the simulation of large
              populations is required, as programs implemented using the
              library are much more efficient than other available forward
              simulation programs.",
  journal  = "Genetics",
  volume   =  198,
  number   =  1,
  pages    = "157--166",
  month    =  sep,
  year     =  2014,
  keywords = "population genetics; quantitative genetics;
              simulation;MyPapers;fwdpy\_paper;Optimum shift
              paper;MIRA2018;fwdpp\_manual",
  language = "en"
}
