refs.bib

@article{bycroft2017genome,
  title={The UK Biobank resource with deep phenotyping and genomic data},
  author={Bycroft, Clare and Freeman, Colin and Petkova, Desislava and Band, Gavin and Elliott, Lloyd T and Sharp, Kevin and Motyer, Allan and Vukcevic, Damjan and Delaneau, Olivier and O'Connell, Jared and others},
  journal={Nature},
  volume={562},
  number={7726},
  pages={203},
  year={2018},
  publisher={Nature Publishing Group}
}

@article{Kane2013,
abstract = {This paper presents two complementary statistical computing frameworks that address challenges in parallel processing and the analysis of massive data. First, the foreach package allows users of the R programming environment to define parallel loops that may be run sequentially on a single machine, in parallel on a symmetric multiprocessing (SMP) machine, or in cluster environments without platformspecific code. Second, the bigmemory package implements memoryand filemapped data structures that provide (a) access to arbitrarily large data while retaining a look and feel that is familiar to R users and (b) data structures that are shared across processor cores in order to support efficient parallel computing techniques. Although these packages may be used independently, this paper shows how they can be used in combination to address challenges that have effectively been beyond the reach of researchers who lack specialized software development skills or expensive hardware.},
author = {Kane, Michael J and Emerson, John W and Weston, Stephen},
doi = {10.18637/jss.v055.i14},
file = {:home/privef/Bureau/thesis-celiac/articles/Kane, Emerson, Weston - 2013 - Scalable Strategies for Computing with Massive Data.pdf:pdf},
issn = {15487660},
journal = {Journal of Statistical Software},
number = {14},
pages = {1--19},
title = {{Scalable Strategies for Computing with Massive Data}},
url = {http://www.jstatsoft.org/v55/i14/},
volume = {55},
year = {2013}
}

@article{prive2017efficient,
author = {Privé, Florian and Aschard, Hugues and Ziyatdinov, Andrey and Blum, Michael G B},
title = {Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr},
journal = {Bioinformatics},
volume = {34},
number = {16},
pages = {2781-2787},
year = {2018},
doi = {10.1093/bioinformatics/bty185},
URL = {http://dx.doi.org/10.1093/bioinformatics/bty185},
eprint = {/oup/backfile/content_public/journal/bioinformatics/34/16/10.1093_bioinformatics_bty185/1/bty185.pdf}
}

@article{barrett2012ncbi,
  title={NCBI GEO: archive for functional genomics data sets—update},
  author={Barrett, Tanya and Wilhite, Stephen E and Ledoux, Pierre and Evangelista, Carlos and Kim, Irene F and Tomashevsky, Maxim and Marshall, Kimberly A and Phillippy, Katherine H and Sherman, Patti M and Holko, Michelle and others},
  journal={Nucleic acids research},
  volume={41},
  number={D1},
  pages={D991--D995},
  year={2012},
  publisher={Oxford University Press}
}

@article{anderson2010data,
  title={Data quality control in genetic case-control association studies},
  author={Anderson, Carl A and Pettersson, Fredrik H and Clarke, Geraldine M and Cardon, Lon R and Morris, Andrew P and Zondervan, Krina T},
  journal={Nature protocols},
  volume={5},
  number={9},
  pages={1564},
  year={2010},
  publisher={Europe PMC Funders}
}

@article{purcell2007plink,
  title={PLINK: a tool set for whole-genome association and population-based linkage analyses},
  author={Purcell, Shaun and Neale, Benjamin and Todd-Brown, Kathe and Thomas, Lori and Ferreira, Manuel AR and Bender, David and Maller, Julian and Sklar, Pamela and De Bakker, Paul IW and Daly, Mark J and others},
  journal={The American Journal of Human Genetics},
  volume={81},
  number={3},
  pages={559--575},
  year={2007},
  publisher={Elsevier}
}

@article{chang2015second,
  title={Second-generation PLINK: rising to the challenge of larger and richer datasets},
  author={Chang, Christopher C and Chow, Carson C and Tellier, Laurent CAM and Vattikuti, Shashaank and Purcell, Shaun M and Lee, James J},
  journal={Gigascience},
  volume={4},
  number={1},
  pages={7},
  year={2015},
  publisher={BioMed Central}
}