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@article{antolin_hybrid_2017,
title = {A hybrid method for the imputation of genomic data in livestock populations},
volume = {49},
issn = {1297-9686},
url = {http://gsejournal.biomedcentral.com/articles/10.1186/s12711-017-0300-y},
doi = {10.1186/s12711-017-0300-y},
language = {en},
number = {1},
urldate = {2017-03-13},
journal = {Genetics Selection Evolution},
author = {Antol\'{\i}n, Roberto and Nettelblad, Carl and Gorjanc, Gregor and Money, Daniel and Hickey, John M.},
month = dec,
year = {2017},
note = {bibtex: antolin\_hybrid\_2017},
file = {art%3A10.1186%2Fs12711-017-0300-y.pdf:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\BBA36T6A\\art%3A10.1186%2Fs12711-017-0300-y.pdf:application/pdf}
}
@article{hickey_combined_2011,
title = {A combined long-range phasing and long haplotype imputation method to impute phase for {SNP} genotypes},
volume = {43},
copyright = {2011 Hickey et al; licensee BioMed Central Ltd.},
issn = {1297-9686},
url = {http://www.gsejournal.org/content/43/1/12/abstract},
doi = {10.1186/1297-9686-43-12},
abstract = {PMID: 21388557},
language = {en},
number = {1},
urldate = {2015-07-17},
journal = {Genetics Selection Evolution},
author = {Hickey, John M. and Kinghorn, Brian P. and Tier, Bruce and Wilson, James F. and Dunstan, Neil and Werf, Julius HJ van der},
month = mar,
year = {2011},
pmid = {21388557},
note = {bibtex: hickey\_combined\_2011},
keywords = {Algorithms, Alleles, Animals, Cattle, Computer Simulation, Data Interpretation, Statistical, Genome-Wide Association Study, Genotype, Haplotypes, Humans, Livestock, Polymorphism, Single Nucleotide, Sheep, Software, Swine},
pages = {12},
file = {Full Text PDF:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\ZDCP2VUM\\Hickey et al. - 2011 - A combined long-range phasing and long haplotype i.pdf:application/pdf;Full Text PDF:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\PCCUDT9G\\Hickey et al. - 2011 - A combined long-range phasing and long haplotype i.pdf:application/pdf;PubMed Central Full Text PDF:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\ZFIH49TJ\\Hickey et al. - 2011 - A combined long-range phasing and long haplotype i.pdf:application/pdf;Snapshot:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\6D2ZAC78\\12.html:text/html;Snapshot:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\WNBUNT2S\\12.html:text/html}
}
@article{hickey_phasing_2012,
title = {A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation},
volume = {44},
issn = {1297-9686},
url = {http://dx.doi.org/10.1186/1297-9686-44-9},
doi = {10.1186/1297-9686-44-9},
abstract = {Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation.},
number = {9},
urldate = {2016-06-11},
journal = {Genetics Selection Evolution},
author = {Hickey, John M. and Kinghorn, Brian P. and Tier, Bruce and van der Werf, Julius HJ and Cleveland, Matthew A.},
year = {2012},
note = {bibtex: hickey\_phasing\_2012},
pages = {11},
file = {1297-9686-44-9.pdf:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\SVDD8WJI\\1297-9686-44-9.pdf:application/pdf;Full Text PDF:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\6I36GUQR\\Hickey et al. - 2012 - A phasing and imputation method for pedigreed popu.pdf:application/pdf;[PDF] from biomedcentral.com:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\XBJW3EZS\\Hickey et al. - 2012 - A phasing and imputation method for pedigreed popu.pdf:application/pdf;Snapshot:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\DKAJJ5FD\\1297-9686-44-9.html:text/html}
}
@article{kerr_efficient_1996,
title = {An efficient algorithm for segregation analysis in large populations},
volume = {113},
issn = {1439-0388},
url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1439-0388.1996.tb00636.x/abstract},
doi = {10.1111/j.1439-0388.1996.tb00636.x},
abstract = {Summary
A computationally tractable approach to complex segregation analysis for large data sets is described. This is then used to extend the value of DNA tests for major locus genotype, by calculating probabilities of belonging to each genotype class for all animals not DNA tested. Under the conditions simulated, this approach led to an approximate doubling of the number of animals genotyped with 100\% confidence, the ability to exclude many more animals from one genotype class, plus a high probability ({\textgreater} 90\%) of belonging to a given genotype class for many other animals.
Zusammenfassung
Verwendung von Spaltungsanalyse für rationelle Anwendung von DNA Tests für HauptgeneEin rechnermäßig traktabler Ansatz zu komplexer Spaltungsanalyse großer Datenmengen wird beschrieben. Dieser wird verwendet, um den Wert der DNA Tests für Hauptgene zu erweitern und zwar dadurch, daß die Wahrscheinlichkeiten der Zugehörigkeit zu jeder Genotypenklasse für Tiere ohne DNA Diagnose berechnet wird. Die Simulation ergab eine Verdopplung der Zahl der Tiere, die mit 100\% Sicherheit genotypisiert werden konnten sowie Ausschluß von mehr Tieren aus einer gegebenen Genotypenklasse und schließlich eine hohe Wahrscheinlichkeit ({\textgreater} 90\%) der Zuweisung vieler Tiere zu gegebenen Genotypenklassen.},
language = {en},
number = {1-6},
urldate = {2016-09-20},
journal = {Journal of Animal Breeding and Genetics},
author = {Kerr, R. J. and Kinghorn, B. P.},
month = jan,
year = {1996},
note = {bibtex: kerr\_efficient\_1996},
pages = {457--469}
}
@article{li_mach:_2010,
title = {{MaCH}: using sequence and genotype data to estimate haplotypes and unobserved genotypes},
volume = {34},
issn = {1098-2272},
shorttitle = {{MaCH}},
doi = {10.1002/gepi.20533},
abstract = {Genome-wide association studies (GWAS) can identify common alleles that contribute to complex disease susceptibility. Despite the large number of SNPs assessed in each study, the effects of most common SNPs must be evaluated indirectly using either genotyped markers or haplotypes thereof as proxies. We have previously implemented a computationally efficient Markov Chain framework for genotype imputation and haplotyping in the freely available MaCH software package. The approach describes sampled chromosomes as mosaics of each other and uses available genotype and shotgun sequence data to estimate unobserved genotypes and haplotypes, together with useful measures of the quality of these estimates. Our approach is already widely used to facilitate comparison of results across studies as well as meta-analyses of GWAS. Here, we use simulations and experimental genotypes to evaluate its accuracy and utility, considering choices of genotyping panels, reference panel configurations, and designs where genotyping is replaced with shotgun sequencing. Importantly, we show that genotype imputation not only facilitates cross study analyses but also increases power of genetic association studies. We show that genotype imputation of common variants using HapMap haplotypes as a reference is very accurate using either genome-wide SNP data or smaller amounts of data typical in fine-mapping studies. Furthermore, we show the approach is applicable in a variety of populations. Finally, we illustrate how association analyses of unobserved variants will benefit from ongoing advances such as larger HapMap reference panels and whole genome shotgun sequencing technologies.},
language = {eng},
number = {8},
journal = {Genetic epidemiology},
author = {Li, Yun and Willer, Cristen J and Ding, Jun and Scheet, Paul and Abecasis, Gonçalo R},
month = dec,
year = {2010},
pmid = {21058334},
pmcid = {PMC3175618},
note = {bibtex: li\_mach:\_2010},
keywords = {Alleles, Base Sequence, Chromosomes, Genetic Markers, Genome, Human, Genome-Wide Association Study, Genotype, Haplotypes, Humans, Markov Chains, Polymorphism, Single Nucleotide, Sensitivity and Specificity, Software},
pages = {816--834}
}
@article{chang_second-generation_2015,
title = {Second-generation {PLINK}: rising to the challenge of larger and richer datasets},
volume = {4},
issn = {2047-217X},
shorttitle = {Second-generation {PLINK}},
url = {https://academic.oup.com/gigascience/article-lookup/doi/10.1186/s13742-015-0047-8},
doi = {10.1186/s13742-015-0047-8},
language = {en},
number = {1},
urldate = {2017-10-12},
journal = {GigaScience},
author = {Chang, Christopher C and Chow, Carson C and Tellier, Laurent CAM and Vattikuti, Shashaank and Purcell, Shaun M and Lee, James J},
month = dec,
year = {2015}
}
@article{purcell_plink:_2007,
title = {{PLINK}: {A} {Tool} {Set} for {Whole}-{Genome} {Association} and {Population}-{Based} {Linkage} {Analyses}},
volume = {81},
issn = {0002-9297},
shorttitle = {{PLINK}},
url = {http://www.sciencedirect.com/science/article/pii/S0002929707613524},
doi = {10.1086/519795},
abstract = {Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.},
number = {3},
urldate = {2016-07-04},
journal = {The American Journal of Human Genetics},
author = {Purcell, Shaun and Neale, Benjamin and Todd-Brown, Kathe and Thomas, Lori and Ferreira, Manuel A. R. and Bender, David and Maller, Julian and Sklar, Pamela and de Bakker, Paul I. W. and Daly, Mark J. and Sham, Pak C.},
month = sep,
year = {2007},
note = {bibtex: purcell\_plink:\_2007},
pages = {559--575},
file = {ScienceDirect Full Text PDF:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\TVD57W9H\\Purcell et al. - 2007 - PLINK A Tool Set for Whole-Genome Association and.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\8EXKZAJF\\S0002929707613524.html:text/html}
}
@article{kong_detection_2008,
title = {Detection of sharing by descent, long-range phasing and haplotype imputation},
volume = {40},
issn = {1061-4036},
doi = {10.1038/ng.216},
abstract = {Uncertainty about the phase of strings of SNPs creates complications in genetic analysis, although methods have been developed for phasing population-based samples. However, these methods can only phase a small number of SNPs effectively and become unreliable when applied to SNPs spanning many linkage disequilibrium (LD) blocks. Here we show how to phase more than 1,000 SNPs simultaneously for a large fraction of the 35,528 Icelanders genotyped by Illumina chips. Moreover, haplotypes that are identical by descent (IBD) between close and distant relatives, for example, those separated by ten meioses or more, can often be reliably detected. This method is particularly powerful in studies of the inheritance of recurrent mutations and fine-scale recombinations in large sample sets. A further extension of the method allows us to impute long haplotypes for individuals who are not genotyped.},
language = {eng},
number = {9},
journal = {Nature Genetics},
author = {Kong, Augustine and Masson, Gisli and Frigge, Michael L. and Gylfason, Arnaldur and Zusmanovich, Pasha and Thorleifsson, Gudmar and Olason, Pall I. and Ingason, Andres and Steinberg, Stacy and Rafnar, Thorunn and Sulem, Patrick and Mouy, Magali and Jonsson, Frosti and Thorsteinsdottir, Unnur and Gudbjartsson, Daniel F. and Stefansson, Hreinn and Stefansson, Kari},
month = sep,
year = {2008},
pmid = {19165921},
note = {bibtex: kong\_detection\_2008},
keywords = {Algorithms, Base Sequence, Female, Gene Deletion, Genetic Markers, Genetics, Population, Haplotypes, Humans, Iceland, Inheritance Patterns, Major Histocompatibility Complex, Male, Models, Genetic, Polymorphism, Single Nucleotide},
pages = {1068--1075},
file = {ng.216.pdf:C\:\\Users\\shojedw\\AppData\\Roaming\\Zotero\\Zotero\\Profiles\\a1inju6b.default\\zotero\\storage\\CHPSAT2M\\ng.216.pdf:application/pdf}
}
@article{ferdosi_hsphase:_2014,
title = {hsphase: an {R} package for pedigree reconstruction, detection of recombination events, phasing and imputation of half-sib family groups},
volume = {15},
issn = {1471-2105},
shorttitle = {hsphase},
url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-172},
doi = {10.1186/1471-2105-15-172},
language = {en},
number = {1},
urldate = {2017-11-13},
journal = {BMC Bioinformatics},
author = {Ferdosi, Mohammad H and Kinghorn, Brian P and van der Werf, Julius HJ and Lee, Seung and Gondro, Cedric},
year = {2014},
pages = {172}
}
@article{ferdosi_detection_2014,
title = {Detection of recombination events, haplotype reconstruction and imputation of sires using half-sib {SNP} genotypes},
volume = {46},
issn = {1297-9686},
url = {http://www.gsejournal.org/content/46/1/11},
doi = {10.1186/1297-9686-46-11},
language = {en},
number = {1},
urldate = {2017-11-13},
journal = {Genetics Selection Evolution},
author = {Ferdosi, Mohammad H and Kinghorn, Brian P and van der Werf, Julius H J and Gondro, Cedric},
year = {2014},
pages = {11}
}
@article{marchini_genotype_2010,
title = {Genotype imputation for genome-wide association studies},
volume = {11},
issn = {1471-0056, 1471-0064},
url = {http://www.nature.com/doifinder/10.1038/nrg2796},
doi = {10.1038/nrg2796},
number = {7},
urldate = {2017-11-13},
journal = {Nature Reviews Genetics},
author = {Marchini, Jonathan and Howie, Bryan},
month = jun,
year = {2010},
pages = {499--511}
}