refs.bib

@Book{Xie:2015,
  title = {Dynamic Documents with {R} and knitr},
  author = {Yihui Xie},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2015},
  edition = {2nd},
  note = {ISBN 978-1498716963},
  url = {http://yihui.name/knitr/},
}

@Book{Buffalo:2015,
  author =    {Vince Buffalo},
  title =     {Bioinformatics Data Skills},
  publisher = {O'Reilly Media, Inc},
  year =      {2015}
}


@Book{r4ds:2017,
  author =    {Grolemund, Garrett and Wickham, Hadley},
  title =     {R for Data Science},
  publisher = {O'Reilly Media},
  year =      {2017},
  URL = {https://r4ds.had.co.nz/}
}

@Article{biocwp2,
  author =       {Gentleman, Robert and Temple Lang, Duncan},
  title =        {Statistical Analyses and Reproducible Research},
  journal =      {Bioconductor Project Working Papers. Working Paper 2},
  year =         {2004},
  URL =    {https://biostats.bepress.com/bioconductor/paper2}
}

@Article{Pouzat:2015,
  author =       {Pouzat, Christophe and Davison, Andrew and Hinsen, Konrad},
  title =        {La recherche reproductible : une communication scientifique explicite},
  journal =      {Statistique et Société},
  year =         {2015},
  volume =    {3},
  number =    {1},
  month =     {June},
  URL = {http://www.publications-sfds.fr/index.php/stat_soc/article/view/448}
}

@article{Broman:2018,
  author = {Broman, Karl W. and Woo, Kara H.},
  title = {Data Organization in Spreadsheets},
  journal = {The American Statistician},
  volume = {72},
  number = {1},
  pages = {2-10},
  year  = {2018},
  publisher = {Taylor & Francis},
  doi = {10.1080/00031305.2017.1375989},
  URL = {https://doi.org/10.1080/00031305.2017.1375989},
  eprint = {https://doi.org/10.1080/00031305.2017.1375989}
}

@Article{WilsonSayres:2018,
  author =       {Wilson Sayres, M A and Hauser, C and Sierk, M and
                 Robic, S and Rosenwald, A G and Smith, T M and
                 Triplett, E W and Williams, J J and Dinsdale, E
                 and Morgan, W R and Burnette, 3rd, J M and
                 Donovan, S S and Drew, J C and Elgin, SCR and
                 Fowlks, E R and Galindo-Gonzalez, S and Goodman, A
                 L and Grandgenett, N F and Goller, C C and Jungck,
                 J R and Newman, J D and Pearson, W and Ryder, E F
                 and Tosado-Acevedo, R and Tapprich, W and Tobin, T
                 C and Toro-Martínez, A and Welch, L R and Wright,
                 R and Barone, L and Ebenbach, D and McWilliams, M
                 and Olney, K C and Pauley, M A},
  title =        {Bioinformatics core competencies for undergraduate
                 life sciences education.},
  journal =      {PLoS One},
  year =         {2018},
  month =        {},
  number =       {6},
  volume =       {13},
  pages =        {e0196878},
  doi =          {10.1371/journal.pone.0196878},
  URL =          {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0196878},
  PMID =         {29870542}}

@Article{Chang:2015,
  author =       {Chang, J},
  title =        {Core services: Reward bioinformaticians.},
  journal =      {Nature},
  year =         {2015},
  month =        {Apr},
  number =       {7546},
  volume =       {520},
  pages =        {151-2},
  doi =          {10.1038/520151a},
  PMID =         {25855439}}

@Article{Markowetz:2015,
  author="Markowetz, Florian",
  title="Five selfish reasons to work reproducibly",
  journal="Genome Biology",
  year="2015",
  month="Dec",
  day="08",
  volume="16",
  number="1",
  pages="274",
  abstract="And so, my fellow scientists: ask not what you can do for
                  reproducibility; ask what reproducibility can do for
                  you! Here, I present five reasons why working
                  reproducibly pays off in the long run and is in the
                  self-interest of every ambitious, career-oriented
                  scientist.",
  issn="1474-760X",
  doi="10.1186/s13059-015-0850-7",
  url="https://doi.org/10.1186/s13059-015-0850-7"
}

@article{Noble:2009,
    author = {Noble, William Stafford},
    journal = {PLOS Computational Biology},
    publisher = {Public Library of Science},
    title = {A Quick Guide to Organizing Computational Biology Projects},
    year = {2009},
    month = {07},
    volume = {5},
    url = {https://doi.org/10.1371/journal.pcbi.1000424},
    pages = {1-5},
    abstract = {},
    number = {7},
    doi = {10.1371/journal.pcbi.1000424}
}


@article{Wickham:2014,
   author = {Wickham, Hadley},
   title = {Tidy Data},
   journal = {Journal of Statistical Software, Articles},
   volume = {59},
   number = {10},
   year = {2014},
   keywords = {},
   abstract = {A huge amount of effort is spent cleaning data to get
                  it ready for analysis, but there has been little
                  research on how to make data cleaning as easy and
                  effective as possible. This paper tackles a small,
                  but important, component of data cleaning: data
                  tidying. Tidy datasets are easy to manipulate, model
                  and visualize, and have a specific structure: each
                  variable is a column, each observation is a row, and
                  each type of observational unit is a table. This
                  framework makes it easy to tidy messy datasets
                  because only a small set of tools are needed to deal
                  with a wide range of un-tidy datasets. This
                  structure also makes it easier to develop tidy tools
                  for data analysis, tools that both input and output
                  tidy datasets. The advantages of a consistent data
                  structure and matching tools are demonstrated with a
                  case study free from mundane data manipulation
                  chores.},
   issn = {1548-7660},
   pages = {1--23},
   doi = {10.18637/jss.v059.i10},
   url = {https://www.jstatsoft.org/v059/i10}
}


@Article{Huber:2015,
  author =       {Huber, W and Carey, V J and Gentleman, R and
                 Anders, S and Carlson, M and Carvalho, B S and
                 Bravo, H C and Davis, S and Gatto, L and Girke, T
                 and Gottardo, R and Hahne, F and Hansen, K D and
                 Irizarry, R A and Lawrence, M and Love, M I and
                 MacDonald, J and Obenchain, V and Ole{\'s}, A K
                 and Pagès, H and Reyes, A and Shannon, P and
                 Smyth, G K and Tenenbaum, D and Waldron, L and
                 Morgan, M},
  title =        {Orchestrating high-throughput genomic analysis
                 with {Bioconductor}.},
  journal =      {Nat Methods},
  year =         {2015},
  month =        {Jan},
  number =       {2},
  volume =       {12},
  pages =        {115-21},
  doi =          {10.1038/nmeth.3252},
  PMID =         {25633503}}

@article{Gentleman:2004,
        author = {Gentleman, Robert C. and Carey, Vincent J. and
                  Bates, Douglas M.  and Bolstad, Ben and Dettling,
                  Marcel and Dudoit, Sandrine and Ellis, Byron and
                  Gautier, Laurent and Ge, Yongchao and Gentry, Jeff
                  and Hornik, Kurt and Hothorn, Torsten and Huber,
                  Wolfgang and Iacus, Stefano and Irizarry, Rafael and
                  Leisch, Friedrich and Li, Cheng and Maechler, Martin
                  and Rossini, Anthony J. and Sawitzki, Gunther and
                  Smith, Colin and Smyth, Gordon and Tierney, Luke and
                  Yang, Jean Y. H. and Zhang, Jianhua},
        title = {Bioconductor: open software development for computational biology
        and bioinformatics.},
        journal = {Genome Biol},
        year = {2004},
        volume = {5},
        pages = {-80},
        number = {10},
        abstract = {The Bioconductor project is an initiative for the collaborative creation
        of extensible software for computational biology and bioinformatics.
        The goals of the project include: fostering collaborative development
        and widespread use of innovative software, reducing barriers to entry
        into interdisciplinary scientific research, and promoting the achievement
        of remote reproducibility of research results. We describe details
        of our aims and methods, identify current challenges, compare Bioconductor
        to other open bioinformatics projects, and provide working examples.},
        doi = {10.1186/gb-2004-5-10-r80},
        file = {Gentleman_et_al_GenomeBiology_2004.pdf:/home/lgatto/Biblio/Gentleman_et_al_GenomeBiology_2004.pdf:PDF},
        keywords = {Computational Biology; Internet; Repro; Software; ducibility of Results},
        owner = {lgatto},
        pii = {gb-2004-5-10-r80},
        pmid = {15461798},
        tags = {reproducible research, software, R, Bioconductor, statistics},
        timestamp = {2006.09.27},
        url = {http://dx.doi.org/10.1186/gb-2004-5-10-r80}
}

@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2019},
    url = {https://www.R-project.org/},
  }

@Misc{DCRecol,
  author = {Achaz {von Hardenberg} and Adam Obeng and Aleksandra
                  Pawlik and Alex Pletzer and Alexey Shiklomanov and
                  Anne Fouilloux and April Wright and Auriel Fournier
                  and Ben Marwick and C. Titus Brown and Carolina
                  Johnson and Carolyn Voter and Catherine Hulshof and
                  Christie Bahlai and Clara Shaw and Daijiang Li and
                  Daina Bouquin and Daniel Stubbs and Danielle Quinn
                  and Darya Vanichkina and Dmytro Fishman and Earle
                  Wilson and Edmund Hart and Eilis Hannon and Elena
                  Sügis and Eli Strauss and Emilia Gan and Erin Becker
                  and Ethan White and Francisco Rodriguez-Sanchez and
                  Francois Michonneau and Fred Boehm and {GMoncrieff}
                  and Hao Ye and Harriet Dashnow and Hilmar Lapp and
                  {JSurman} and Jaime Ashander and Jarrett Byrnes and
                  Jeffrey W Hollister and Jieming Chen and Jillian
                  Dunic and {Jon} and Jonathan Keane and Joseph
                  Stachelek and Josh Herr and K. A. S. Mislan and Kara
                  Woo and Karen Cranston and Kari L. Jordan and
                  Karthik Ram and Kate Hertweck and Kathe Todd-Brown
                  and Katie Lotterhos and Kayla Peck and Kenan Direk
                  and Kevin Hall and Kristian Tylén and Kyriakos
                  Chatzidimitriou and Lachlan Deer and Laurent Gatto
                  and Leah Wasser and Leszek Tarkowski and Lisa
                  Breckels and M. Foos and Marco Chiapello and Mark
                  Robinson and Markus J. Akenbrand and Mateusz Kuzak
                  and Matthias Grenié and Matthias Grenié and Maëlle
                  Salmon and Meghan Duffy and Michael Koontz and
                  Myfanwy Johnston and Nicholas Marino and Nick
                  Carchedi and Olivia Burge and Philip Lijnzaad and
                  Philip Lijnzaad and Ryan Peek and Sarah Supp and
                  Shawn Taylor and Stephanie Labou and Steve Pederson
                  and Tara Webster and Taylor Reiter and Thomas
                  Sandmann and Tracy Teal and Will Furnass and Will
                  Pearse and Ye Li and Zena Lapp and {ab604} and
                  {ashander} and {cengel} and Brian Seok and {sfn_brt}
                  and {suparee}},
  title = {{Data Carpentry}: {R} for data analysis and visualization of Ecological Data},
  editor = {Francois Michonneau and Auriel Fournier},
  month = {January},
  year = {2019},
  url = {http://datacarpentry.org/R-ecology-lesson/},
  doi = {10.5281/zenodo.569338},
}

@article{Perez-Riverol:2016,
    author = {Perez-Riverol, Yasset and Gatto, Laurent and Wang, Rui
                  and Sachsenberg, Timo and Uszkoreit, Julian and
                  Leprevost, Felipe da Veiga and Fufezan, Christian
                  and Ternent, Tobias and Eglen, Stephen J. and Katz,
                  Daniel S. and Pollard, Tom J. and Konovalov,
                  Alexander and Flight, Robert M. and Blin, Kai and
                  Vizcaíno, Juan Antonio},
    journal = {PLOS Computational Biology},
    publisher = {Public Library of Science},
    title = {Ten Simple Rules for Taking Advantage of Git and {GitHub}},
    year = {2016},
    month = {07},
    volume = {12},
    url = {https://doi.org/10.1371/journal.pcbi.1004947},
    pages = {1-11},
    abstract = {},
    number = {7},
    doi = {10.1371/journal.pcbi.1004947}
}

@article{White:2013,
 title = {Nine simple ways to make it easier to (re)use your data},
 author = {White, Ethan P. and Baldridge, Elita and Brym, Zachary T. and Locey, Kenneth J. and McGlinn, Daniel J. and Supp, Sarah R.},
 year = 2013,
 month = jul,
 keywords = {data sharing, data reuse, repository, license, data format},
 abstract = { Sharing data is increasingly considered to be an
                  important part of the scientific process. Making
                  your data publicly available allows original results
                  to be reproduced and new analyses to be
                  conducted. While sharing your data is the first step
                  in allowing reuse, it is also important that the
                  data be easy to understand and use. We describe nine
                  simple ways to make it easy to reuse the data that
                  you share and also make it easier to work with it
                  yourself. Our recommendations focus on making your
                  data understandable, easy to analyze, and readily
                  available to the wider community of scientists.  },
 volume = 1,
 pages = {e7v2},
 journal = {PeerJ PrePrints},
 issn = {2167-9843},
 url = {https://doi.org/10.7287/peerj.preprints.7v2},
 doi = {10.7287/peerj.preprints.7v2}
}

@Article{Zeeberg:2004,
   author="Zeeberg, Barry R.  and Riss, Joseph and Kane, David W.  and
                  Bussey, Kimberly J.  and Uchio, Edward and Linehan,
                  W. Marston and Barrett, J. Carl and Weinstein, John
                  N.",
   title="Mistaken Identifiers: Gene name errors can be introduced
                  inadvertently when using Excel in bioinformatics",
   journal="BMC Bioinformatics",
   year="2004",
   month="Jun",
   day="23",
   volume="5",
   number="1",
   pages="80",
   abstract="When processing microarray data sets, we recently noticed
                  that some gene names were being changed
                  inadvertently to non-gene names.",
   issn="1471-2105",
   doi="10.1186/1471-2105-5-80",
   url="https://doi.org/10.1186/1471-2105-5-80"
}

@book{Wilkinson:2005,
 author = {Wilkinson, Leland},
 title = {The Grammar of Graphics (Statistics and Computing)},
 year = {2005},
 isbn = {0387245448},
 publisher = {Springer-Verlag},
 address = {Berlin, Heidelberg},
}


@Book{latticebook,
    title = {Lattice: Multivariate Data Visualization with R},
    author = {Deepayan, Sarkar},
    publisher = {Springer},
    address = {New York},
    year = {2008},
    note = {ISBN 978-0-387-75968-5},
    url = {http://lmdvr.r-forge.r-project.org},
  }


@Book{ggplot2book,
    author = {Wickham, Hadley},
    title = {{ggplot2}: Elegant Graphics for Data Analysis},
    publisher = {Springer-Verlag New York},
    year = {2016},
    isbn = {978-3-319-24277-4},
    url = {http://ggplot2.org},
  }

@book{advancedR,
  title = {Advanced {R}},
  author = {Wickham, Hadley},
  isbn = {9781466586963},
  series = {Chapman \& Hall/CRC The R Series},
  year = {2014},
  publisher = {Taylor \& Francis}
}

@book{rpkgs:2015,
 author = {Wickham, Hadley},
 title = {R Packages},
 year = {2015},
 isbn = {1491910593, 9781491910597},
 edition = {1st},
 publisher = {O'Reilly Media, Inc.},
}

@Book{MSMB,
  author =	 {Holmes, Susan and Huber, Wolfgang},
  title =	 {Modern Statistics for Modern Biology},
  publisher =	 {Cambridge Univeristy Press},
  year =	 {2019},
  isbn = {9781108705295}
}

@book{ISLR,
 author = {James, Gareth and Witten, Daniela and Hastie, Trevor and Tibshirani, Robert},
 title = {An Introduction to Statistical Learning: With Applications in R},
 year = {2014},
 isbn = {1461471370, 9781461471370},
 publisher = {Springer Publishing Company, Incorporated},
}

@Article{Ohnishi:2014,
  author =       {Ohnishi, Y and Huber, W and Tsumura, A and Kang, M
                 and Xenopoulos, P and Kurimoto, K and Ole{\'s}, A
                 K and Araúzo-Bravo, M J and Saitou, M and
                 Hadjantonakis, A K and Hiiragi, T},
  title =        {Cell-to-cell expression variability followed by
                 signal reinforcement progressively segregates
                 early mouse lineages.},
  journal =      {Nat Cell Biol},
  year =         {2014},
  month =        {Jan},
  number =       {1},
  volume =       {16},
  pages =        {27-37},
  doi =          {10.1038/ncb2881},
  PMID =         {24292013}}

@Article{Himes:2014,
  author =       {Himes, B E and Jiang, X and Wagner, P and Hu, R
                 and Wang, Q and Klanderman, B and Whitaker, R M
                 and Duan, Q and Lasky-Su, J and Nikolos, C and
                 Jester, W and Johnson, M and Panettieri, Jr, R A
                 and Tantisira, K G and Weiss, S T and Lu, Q},
  title =        {RNA-Seq transcriptome profiling identifies
                 CRISPLD2 as a glucocorticoid responsive gene that
                 modulates cytokine function in airway smooth
                 muscle cells.},
  journal =      {PLoS One},
  year =         {2014},
  month =        {},
  number =       {6},
  volume =       {9},
  pages =        {e99625},
  doi =          {10.1371/journal.pone.0099625},
  PMID =         {24926665\cite{Himes:2014}}}


@article{Majumder2013,
  author = {Majumder, Mahbubul and Hofmann, Heike and Cook, Dianne},
  title = {Validation of Visual Statistical Inference, Applied to Linear Models},
  journal = {Journal of the American Statistical Association},
  volume = {108},
  number = {503},
  pages = {942-956},
  year  = {2013},
  publisher = {Taylor & Francis},
  doi = {10.1080/01621459.2013.808157},
  URL = {https://doi.org/10.1080/01621459.2013.808157},
  eprint = {https://doi.org/10.1080/01621459.2013.808157}
}

@article{Fan:2014,
    author = {Fan, Jianqing and Han, Fang and Liu, Han},
    title = "{Challenges of Big Data analysis}",
    journal = {National Science Review},
    volume = {1},
    number = {2},
    pages = {293-314},
    year = {2014},
    month = {02},
    abstract = "{Big Data bring new opportunities to modern society
                  and challenges to data scientists. On the one hand,
                  Big Data hold great promises for discovering subtle
                  population patterns and heterogeneities that are not
                  possible with small-scale data. On the other hand,
                  the massive sample size and high dimensionality of
                  Big Data introduce unique computational and
                  statistical challenges, including scalability and
                  storage bottleneck, noise accumulation, spurious
                  correlation, incidental endogeneity and measurement
                  errors. These challenges are distinguished and
                  require new computational and statistical
                  paradigm. This paper gives overviews on the salient
                  features of Big Data and how these features impact
                  on paradigm change on statistical and computational
                  methods as well as computing architectures. We also
                  provide various new perspectives on the Big Data
                  analysis and computation. In particular, we
                  emphasize on the viability of the sparsest solution
                  in high-confidence set and point out that exogenous
                  assumptions in most statistical methods for Big Data
                  cannot be validated due to incidental
                  endogeneity. They can lead to wrong statistical
                  inferences and consequently wrong scientific
                  conclusions.}",
    issn = {2095-5138},
    doi = {10.1093/nsr/nwt032},
    url = {https://doi.org/10.1093/nsr/nwt032},
    eprint = {http://oup.prod.sis.lan/nsr/article-pdf/1/2/293/9663410/nwt032.pdf},
}

@article{Kerr:1998,
  author = {Kerr, N. L.},
  title = {{HARKing: hypothesizing after the results are known.}},
  journal = {{Pers Soc Psychol Rev}},
  year = {1998},
  volume = {2},
  pages = {196-217},
  doi = {10.1207/s15327957pspr0203_4}
}

@article{Head:2015,
  author = {Head, M. L. and Holman, L. and Lanfear, R. and Kahn, A. T. and Jennions, M. D.},
  title = {{The extent and consequences of p-hacking in science.}},
  journal = {{PLoS Biol}},
  year = {2015},
  volume = {13},
  pages = {e1002106},
  doi = {10.1371/journal.pbio.1002106}
}

@Article{Mulvey:2015,
  author =       {Mulvey, C M and Schr\"oter, C and Gatto, L and
                 Dikicioglu, D and Baris Fidaner, I and
                 Christoforou, A and Deery, M J and Cho, L T and
                 Niakan, K K and Martinez-Arias, A and Lilley, K S},
  title =        {Dynamic proteomic profiling of extra-embryonic
                 endoderm differentiation in mouse embryonic stem
                 cells.},
  journal =      {Stem Cells},
  year =         {2015},
  month =        {Jun},
  number =       {},
  volume =       {},
  pages =        {},
  doi =          {10.1002/stem.2067},
  PMID =         {26059426}}

@Article{Christoforou:2016,
  author =       {Christoforou, A and Mulvey, C M and Breckels, L M
                 and Geladaki, A and Hurrell, T and Hayward, P C
                 and Naake, T and Gatto, L and Viner, R and
                 Martinez Arias, A and Lilley, K S},
  title =        {A draft map of the mouse pluripotent stem cell
                 spatial proteome.},
  journal =      {Nat Commun},
  year =         {2016},
  month =        {},
  number =       {},
  volume =       {7},
  pages =        {8992},
  doi =          {10.1038/ncomms9992},
  PMID =         {26754106}}

@Article{Dhaeseleer:2005,
  author =       {D'haeseleer, P},
  title =        {How does gene expression clustering work?},
  journal =      {Nat Biotechnol},
  year =         {2005},
  month =        {Dec},
  number =       {12},
  volume =       {23},
  pages =        {1499-501},
  doi =          {10.1038/nbt1205-1499},
  PMID =         {16333293}}

@Article{Key:2012,
  author =       {Key, M},
  title =        {A tutorial in displaying mass spectrometry-based
                 proteomic data using heat maps.},
  journal =      {BMC Bioinformatics},
  year =         {2012},
  month =        {},
  number =       {},
  volume =       {13 Suppl 16},
  pages =        {S10},
  doi =          {10.1186/1471-2105-13-S16-S10},
  PMID =         {23176119}}