@Manual{rcoreteam,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2017},
    url = {https://www.R-project.org/},
  }

@Article{Schulze2012,
author="Schulze, Stefan K.
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and G{\"o}lzenleuchter, Meike
and Therneau, Terry M.
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journal="BMC Genomics",
year="2012",
volume="13",
number="1",
pages="524",
issn="1471-2164",
doi="10.1186/1471-2164-13-524",
url="http://dx.doi.org/10.1186/1471-2164-13-524"
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@Article{Gentleman2004,
author="Gentleman, Robert C.
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and Iacus, Stefano
and Irizarry, Rafael
and Leisch, Friedrich
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and Maechler, Martin
and Rossini, Anthony J.
and Sawitzki, Gunther
and Smith, Colin
and Smyth, Gordon
and Tierney, Luke
and Yang, Jean YH
and Zhang, Jianhua",
title="Bioconductor: open software development for computational biology and bioinformatics",
journal="Genome Biology",
year="2004",
volume="5",
number="10",
pages="R80",
issn="1474-760X",
doi="10.1186/gb-2004-5-10-r80",
url="http://dx.doi.org/10.1186/gb-2004-5-10-r80"
}

@Article{Anders2010,
author="Anders, Simon and Huber, Wolfgang",
title="Differential expression analysis for sequence count data",
journal="Genome Biology",
year="2010",
volume="11",
number="10",
pages="R106",
issn="1474-760X",
doi="10.1186/gb-2010-11-10-r106",
url="http://dx.doi.org/10.1186/gb-2010-11-10-r106"
}

@Article{Love2014,
author="Love, Michael I. and Huber, Wolfgang and Anders, Simon",
title="Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2",
journal="Genome Biology",
year="2014",
volume="15",
number="12",
pages="550",
issn="1474-760X",
doi="10.1186/s13059-014-0550-8",
url="http://dx.doi.org/10.1186/s13059-014-0550-8"
}

@article{cook1977,
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@article{cox1897,
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@article{BH1995,
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 author = {Yoav Benjamini and Yosef Hochberg},
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 publisher = {Royal Statistical Society, Wiley},
 title = {Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing},
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}

@article{BY2001,
 ISSN = {00905364},
 URL = {http://www.jstor.org/stable/2674075},
 author = {Yoav Benjamini and Daniel Yekutieli},
 journal = {The Annals of Statistics},
 number = {4},
 pages = {1165-1188},
 publisher = {Institute of Mathematical Statistics},
 title = {The Control of the False Discovery Rate in Multiple Testing under Dependency},
 volume = {29},
 year = {2001}
}

@article{robinson2010,
author = {Robinson, Mark and McCarthy, Davis and Smyth, Gordon},
title = {edgeR: a Bioconductor package for differential expression analysis of digital gene expression data},
journal = {Bioinformatics},
volume = {26},
number = {1},
pages = {139},
year = {2010},
doi = {10.1093/bioinformatics/btp616},
URL = {http://dx.doi.org/10.1093/bioinformatics/btp616},
eprint = {/oup/backfile/content_public/journal/bioinformatics/26/1/10.1093/bioinformatics/btp616/2/btp616.pdf}
}

@article{dillies2013,
author = {Dillies, Marie-Agnès and Rau, Andrea and Aubert, Julie and Hennequet-Antier, Christelle and Jeanmougin, Marine and Servant, Nicolas and Keime, Céline and Marot, Guillemette and Castel, David and Estelle, Jordi and Guernec, Gregory and Jagla, Bernd and Jouneau, Luc and Laloë, Denis and Le Gall, Caroline and Schaëffer, Brigitte and Le Crom, Stéphane and Guedj, Mickaël and Jaffrézic, Florence},
title = {A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis},
journal = {Briefings in Bioinformatics},
volume = {14},
number = {6},
pages = {671},
year = {2013},
doi = {10.1093/bib/bbs046},
URL = {http://dx.doi.org/10.1093/bib/bbs046},
eprint = {/oup/backfile/content_public/journal/bib/14/6/10.1093/bib/bbs046/2/bbs046.pdf}
}

@article{robinson2008,
author = {Robinson, Mark and Smyth, Gordon},
title = {Small-sample estimation of negative binomial dispersion, with applications to SAGE data},
journal = {Biostatistics},
volume = {9},
number = {2},
pages = {321},
year = {2008},
doi = {10.1093/biostatistics/kxm030},
URL = {http://dx.doi.org/10.1093/biostatistics/kxm030},
eprint = {/oup/backfile/content_public/journal/biostatistics/9/2/10.1093/biostatistics/kxm030/2/kxm030.pdf}
}

@article{robinson2007,
author = {Robinson, Mark and Smyth, Gordon},
title = {Moderated statistical tests for assessing differences in tag abundance},
journal = {Bioinformatics},
volume = {23},
number = {21},
pages = {2881},
year = {2007},
doi = {10.1093/bioinformatics/btm453},
URL = {http://dx.doi.org/10.1093/bioinformatics/btm453},
eprint = {/oup/backfile/content_public/journal/bioinformatics/23/21/10.1093_bioinformatics_btm453/2/btm453.pdf}
}

@article{wu2013,
author = {Wu, Hao and Wang, Chi and Wu, Zhijin},
title = {A new shrinkage estimator for dispersion improves differential expression detection in RNA-seq data},
journal = {Biostatistics},
volume = {14},
number = {2},
pages = {232},
year = {2013},
doi = {10.1093/biostatistics/kxs033},
URL = {http://dx.doi.org/10.1093/biostatistics/kxs033},
eprint = {/oup/backfile/content_public/journal/biostatistics/14/2/10.1093/biostatistics/kxs033/2/kxs033.pdf}
}

@article{mccarthy2012,
author = {McCarthy, Davis and Chen, Yunshun and Smyth, Gordon},
title = {Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation},
journal = {Nucleic Acids Research},
volume = {40},
number = {10},
pages = {4288},
year = {2012},
doi = {10.1093/nar/gks042},
URL = {http://dx.doi.org/10.1093/nar/gks042},
eprint = {/oup/backfile/content_public/journal/nar/40/10/10.1093_nar_gks042/2/gks042.pdf}
}

@article{korbinian2008,
    author = {Strimmer, Korbinian},
    title = "{fdrtool: a versatile R package for estimating local and tail area-based false discovery rates}",
    journal = {Bioinformatics},
    volume = {24},
    number = {12},
    pages = {1461-1462},
    year = {2008},
    month = {04},
    abstract = "{Summary: False discovery rate (FDR) methodologies are essential in the study of high-dimensional genomic and proteomic data. The R package ‘fdrtool’ facilitates such analyses by offering a comprehensive set of procedures for FDR estimation. Its distinctive features include: (i) many different types of test statistics are allowed as input data, such as P-values, z-scores, correlations and t-scores; (ii) simultaneously, both local FDR and tail area-based FDR values are estimated for all test statistics and (iii) empirical null models are fit where possible, thereby taking account of potential over- or underdispersion of the theoretical null. In addition, ‘fdrtool’ provides readily interpretable graphical output, and can be applied to very large scale (in the order of millions of hypotheses) multiple testing problems. Consequently, ‘fdrtool’ implements a flexible FDR estimation scheme that is unified across different test statistics and variants of FDR.Availability: The program is freely available from the Comprehensive R Archive Network (http://cran.r-project.org/) under the terms of the GNU General Public License (version 3 or later).Contact:strimmer@uni-leipzig.de}",
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btn209},
    url = {https://doi.org/10.1093/bioinformatics/btn209},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/24/12/1461/493586/btn209.pdf},
}
