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@misc{Aaberge2021,
title = {Stop {Using} {Magic} {Numbers} and {Variables} in {Your} {Code}},
url = {https://betterprogramming.pub/stop-using-magic-numbers-and-variables-in-your-code-4e86f008b84c},
abstract = {No one will understand your program. Not even you},
language = {en},
urldate = {2021-11-02},
journal = {Medium},
author = {Aaberge, Martin Andersson},
month = January,
year = {2021},
}
@article{Baker2009,
title = {1,500 scientists lift the lid on reproducibility},
volume = {533},
copyright = {2016 Nature Publishing Group},
issn = {1476-4687},
url = {https://www.nature.com/articles/533452a},
doi = {10.1038/533452a},
abstract = {Survey sheds light on the ‘crisis’ rocking research.},
language = {en},
number = {7604},
urldate = {2021-10-06},
journal = {Nature},
author = {Baker, Monya},
month = {May},
year = {2016},
pages = {452--454},
}
@article{Baker2016,
title = {1,500 scientists lift the lid on reproducibility},
volume = {533},
copyright = {2016 Nature Publishing Group},
issn = {1476-4687},
url = {https://www.nature.com/articles/533452a},
doi = {10.1038/533452a},
abstract = {Survey sheds light on the ‘crisis’ rocking research.},
language = {en},
number = {7604},
urldate = {2021-10-06},
journal = {Nature},
author = {Baker, Monya},
month = {May},
year = {2016},
pages = {452--454},
}
@article{BeaulieuJones2017,
doi = {10.1038/nbt.3780},
url = {https://doi.org/10.1038/nbt.3780},
year = {2017},
month = {Mar},
publisher = {Springer Science and Business Media {LLC}},
volume = {35},
number = {4},
pages = {342--346},
author = {Brett K Beaulieu-Jones and Casey S Greene},
title = {Reproducibility of computational workflows is automated using continuous analysis},
journal = {Nature Biotechnology}
}
@article{Benureau2018,
title = {Re-run, {Repeat}, {Reproduce}, {Reuse}, {Replicate}: {Transforming} {Code} into {Scientific} {Contributions}},
volume = {11},
issn = {1662-5196},
shorttitle = {Re-run, {Repeat}, {Reproduce}, {Reuse}, {Replicate}},
url = {https://www.frontiersin.org/article/10.3389/fninf.2017.00069},
doi = {10.3389/fninf.2017.00069},
abstract = {Scientific code is different from production software. Scientific code, by producing results that are then analyzed and interpreted, participates in the elaboration of scientific conclusions. This imposes specific constraints on the code that are often overlooked in practice. We articulate, with a small example, five characteristics that a scientific code in computational science should possess: re-runnable, repeatable, reproducible, reusable, and replicable. The code should be executable (re-runnable) and produce the same result more than once (repeatable); it should allow an investigator to reobtain the published results (reproducible) while being easy to use, understand and modify (reusable), and it should act as an available reference for any ambiguity in the algorithmic descriptions of the article (replicable).},
urldate = {2021-10-06},
journal = {Frontiers in Neuroinformatics},
author = {Benureau, Fabien C. Y. and Rougier, Nicolas P.},
year = {2018},
pages = {69},
}
@misc{Bernardo2021,
title = {Best {Practices} for {R} {Programming}},
url = {https://towardsdatascience.com/best-practices-for-r-programming-ec0754010b5a},
abstract = {Writing clean code is a great skill to have when you are working collaboratively— here are some tips for making your R code a bit cleaner},
language = {en},
urldate = {2021-11-02},
journal = {Medium},
author = {Bernardo, Ivo},
month = August,
year = {2021},
}
@misc{Biostars2021,
title = {How Do You Manage Your Files & Directories For Your Projects?},
url = {www.biostars.org/p/821/},
urldate = {2021-10-12},
year = {2010},
}
@article{Brito2020,
doi = {10.1093/gigascience/giaa056},
url = {https://doi.org/10.1093/gigascience/giaa056},
year = {2020},
month = June,
publisher = {Oxford University Press ({OUP})},
volume = {9},
number = {6},
author = {Jaqueline J Brito and Jun Li and Jason H Moore and Casey S Greene and Nicole A Nogoy and Lana X Garmire and Serghei Mangul},
title = {Recommendations to enhance rigor and reproducibility in biomedical research},
journal = {{GigaScience}}
}
@misc{Broman,
title = {Tools for {Reproducible} {Research}},
url = {https://kbroman.org/Tools4RR/},
author = {Karl Broman},
abstract = {A course on tools for reproducible research, UW-Madison},
urldate = {2021-10-11},
year = {2016},
}
@website{Bryan2017,
author = {Jenny Bryan},
year = {2017},
month = {December},
title = {Project-oriented workflow},
url = {https://www.tidyverse.org/blog/2017/12/workflow-vs-script/},
journal = {Tidyverse Blog},
}
@website{Bryan2021,
author = {Jenny Bryan and Jim Hester},
title = {Happy Git and GitHub for the useR},
url = {https://happygitwithr.com/},
year = {2021},
}
@book{Cannell2021,
title = {9 {Coding} best practices {\textbar} {R} for {Epidemiology}},
url = {https://brad-cannell.github.io/r4epi/},
abstract = {This is the textbook for Brad Cannell’s Introduction to R Programming for Epidemiologic Research course.},
urldate = {2021-11-02},
author = {Cannell, Brad},
year = {2021},
}
@book{Chacon2014,
title={Pro git},
author={Chacon, Scott and Straub, Ben},
year={2014},
publisher={Apress}
}
@misc{Chang2021,
author = {Winston Chang},
title = {Generating random numbers},
url = {http://www.cookbook-r.com/Numbers/Generating_random_numbers/},
urldate = {2021-11-02},
year = {2021}
}
@misc{Cronin2019,
title = {What {Makes} a {Good} {Code} {Comment}?},
url = {https://itnext.io/what-makes-a-good-code-comment-5267debd2c24},
abstract = {How comments can clarify things code can’t},
language = {en},
urldate = {2021-10-29},
journal = {Medium},
author = {Cronin, Mike},
month = October,
year = {2019},
}
@misc{Csendes2020,
title = {15 common coding mistakes data scientist make in {Python} (and how to fix them)},
url = {https://towardsdatascience.com/15-common-coding-mistakes-data-scientist-make-in-python-and-how-to-fix-them-7760467498af},
abstract = {Data scientists are known for writing bad code. Start improving your code quality by not making these mistakes.},
language = {en},
urldate = {2021-11-02},
journal = {Medium},
author = {Csendes, Gerold},
month = December,
year = {2020},
}
@misc{DataCarpentry2019,
title = {Introduction to the Command Line for Genomics},
url = {https://bioinformatics-core-shared-training.github.io/shell-genomics/07-organization/index.html},
chapter = {Project Organization},
urldate = {2021-10-12},
year = {2019},
}
@misc{DataCarpentry2021,
title = {Project {Organization} and {Management} for {Genomics}},
url = {https://datacarpentry.org/organization-genomics/},
urldate = {2021-10-12},
year = {2021},
}
@misc{DataCarpentry2021b,
title = {Best {Practices} for {Writing} {R} {Code} – {Programming} with {R}},
url = {https://swcarpentry.github.io/r-novice-inflammation/06-best-practices-R/},
urldate = {2021-11-02},
year = {2021},
}
@misc{Diederich2012,
title = {Stop {Writing} {Classes}},
url = {https://pyvideo.org/pycon-us-2012/stop-writing-classes.html},
language = {en},
urldate = {2021-10-29},
journal = {PyVideo.org},
author = {Diederich, Jack},
year = {2012},
}
@misc{DRY,
title = {How {To} {Keep} {Your} {Code} {Dry}},
url = {http://www.drycode.io},
abstract = {How to keep your code DRY},
urldate = {2021-10-29},
year = {2021},
}
@misc{DRY2013,
title = {Don't {Repeat} {Yourself} - {Programmer} 97-things},
url = {https://web.archive.org/web/20131204221336/http://programmer.97things.oreilly.com/wiki/index.php/Don't_Repeat_Yourself},
urldate = {2021-10-29},
month = December,
year = {2013},
}
@misc{Dubel2021,
title = {5 {Tips} for {Writing} {Clean} {R} {Code} - {Leave} {Your} {Code} {Reviewer} {Commentless}},
author = {Marcin Dubel},
url = {https://appsilon.com/write-clean-r-code/},
abstract = {Writing readable and maintainable R code is no small task. Here are our top 5 tips for making your code reviewer commentless - from basic comments to best programming practices.},
language = {en-GB},
urldate = {2021-11-02},
journal = {Appsilon {\textbar} End to End Data Science Solutions},
month = {Mar},
year = {2021},
}
@misc{Driscoll2021,
title = {Jupyter {Notebook}: {An} {Introduction} – {Real} {Python}},
shorttitle = {Jupyter {Notebook}},
url = {https://realpython.com/jupyter-notebook-introduction/},
abstract = {In this step-by-step Python tutorial, you learn how to get started with The Jupyter Notebook, an open source web application that you can use to create and share documents that contain live code, equations, visualizations, and text.},
language = {en},
urldate = {2021-11-16},
author = {Mike, Driscoll},
note = {publisher: Real Python},
year = {2021},
}
@article{Essawy2020,
title = {A taxonomy for reproducible and replicable research in environmental modelling},
volume = {134},
issn = {1364-8152},
url = {https://www.sciencedirect.com/science/article/pii/S1364815219311612},
doi = {10.1016/j.envsoft.2020.104753},
language = {en},
urldate = {2021-10-06},
journal = {Environmental Modelling \& Software},
author = {Essawy, Bakinam T. and Goodall, Jonathan L. and Voce, Daniel and Morsy, Mohamed M. and Sadler, Jeffrey M. and Choi, Young Don and Tarboton, David G. and Malik, Tanu},
month = {December},
year = {2020},
keywords = {Reproducibility, Replicability, Containers, Docker, Singularity},
pages = {104753},
}
@misc{Fangohr2021,
title = {Jupyter for {Computational} {Science} and {Data} {Science}},
url = {https://fangohr.github.io/blog/jupyter-for-computational-science-and-data-science.html},
journal = {Computational Science and Data Science},
author = {Fangohr, Hans},
month = April,
year = {2021},
}
@misc{Frazee2014,
author = {Alyssa Frazee},
title = {Some internet wisdom on {R} documentation},
url = {http://alyssafrazee.com/2014/04/20/rdocs.html},
abstract = {I spent a lot of last week documenting an R package. I’m still learning how to write good user-facing features (including documentation) in my software, so I...},
urldate = {2021-10-29},
year = {2014},
}
@misc{Frey2021,
title = {How and why to share scientific code},
url = {https://towardsdatascience.com/how-and-why-to-share-scientific-code-64fbd385a67},
abstract = {A simple guide to reproducible research without becoming a software engineer},
language = {en},
urldate = {2021-10-06},
journal = {Medium},
author = {Nathan C. Frey},
month = April,
year = {2021},
}
@misc{Ganderson2016,
author = {Alexander Ganderson},
title = {Writing {Great} {Scientific} {Code}},
url = {http://alexanderganderson.github.io/code/2016/10/12/coding_tips.html},
abstract = {Introduction},
urldate = {2021-11-02},
year = {2016},
month = {October},
}
@misc{Geeksforgeeks2018,
author = {Geeks for Geeks},
title = {f-strings in {Python}},
url = {https://www.geeksforgeeks.org/formatted-string-literals-f-strings-python/},
abstract = {A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.},
language = {en-us},
urldate = {2021-11-02},
journal = {GeeksforGeeks},
month = April,
year = {2018},
}
@misc{GenoFab2021,
title = {Repeatability \& {Reproducibility}},
url = {https://blog.genofab.com/repeatability-vs-reproducibility},
abstract = {Repeatability vs Reproducibility – In science, reproducibility, not just repeatability, is key. Find out how to make research more reproducible.},
language = {en},
urldate = {2021-10-06},
year = {2021},
}
@misc{Goldberg2016,
author = {Zachary Goldberg},
title = {The {Six} {Commandments} of {Good} {Code}: {Write} {Code} that {Stands} the {Test} of {Time}},
shorttitle = {The {Six} {Commandments} of {Good} {Code}},
url = {https://www.toptal.com/software/six-commandments-of-good-code},
abstract = {How do you define good code? Is it 100\% test coverage, or is it backwards compatibility with decade-old hardware? We may not be able to reach an end to this debate yet, but good software always seems to conform to a few certain qualities of code.
In this article, Toptal Freelance Software Engineer Zachary Goldber...},
language = {en},
urldate = {2021-11-02},
journal = {Toptal Engineering Blog},
year = {2016},
}
@book{Good2021,
title = {Chapter 5 {Reproducible} research \#1 {\textbar} {R} {Programming} for {Research}},
url = {https://geanders.github.io/RProgrammingForResearch/reproducible-research-1.html},
abstract = {This is a bookdown version of the course notes for R Programming for Research, Colorado State University, Fall 2016.},
urldate = {2021-11-02},
year = {2021},
author = {Good, Rachel Severson, {and} Nicholas, Brooke Anderson},
}
@misc{GooglePython,
title = {styleguide},
url = {https://google.github.io/styleguide/pyguide.html},
abstract = {Style guides for Google-originated open-source projects},
language = {en-US},
urldate = {2021-10-29},
journal = {styleguide},
year = {2021},
}
@misc{GoogleR,
title = {Google’s {R} {Style} {Guide}},
url = {https://google.github.io/styleguide/Rguide.html},
abstract = {Style guides for Google-originated open-source projects},
language = {en-US},
urldate = {2021-10-29},
journal = {styleguide},
year = {2021},
}
@misc{Hauer2018,
title = {Code {Review} {Guidelines} for {Humans}},
url = {https://phauer.com/2018/code-review-guidelines/},
abstract = {Guidelines describing the required mindset and phrasing techniques for effective and respectful code reviews},
language = {en-US},
urldate = {2021-11-02},
journal = {Philipp Hauer's Blog},
author = {Hauer, Philipp},
month = July,
year = {2018},
}
misc{Harvie2018,
title = {Version {Control} — {Why} {Do} {We} {Need} {It}?},
url = {https://medium.com/lanceharvieruntime/version-control-why-do-we-need-it-1681f4888cec},
abstract = {Complex code development is impossible without a Version Control System (VCS). Version Control is used to track and control changes to…},
language = {en},
urldate = {2021-10-20},
journal = {Medium},
author = {Harvie, Lance},
month = December,
year = {2018},
}
@misc{Heil2020,
title={Reproducible Programming for Biologists Who Code - Part 1: Must Dos},
url={https://autobencoder.com/2020-06-16-mustdo/}, journal={AutoBenCoding},
author={Heil, Benjamin J.},
year={2020},
month={June},
}
@misc{Heil2020b,
title = {Reproducible Programming for Biologists Who Code - Part 2: Should Dos},
url = {https://autobencoder.com/2020-06-30-shoulddo/},
journal = {AutoBenCoding},
author = {Heil, Benjamin J.},
year = {2020},
month = {June},
}
@misc{Heroux2018,
title = {Don’t repeat yourself: {Python} functions},
shorttitle = {Don’t repeat yourself},
url = {https://scientificallysound.org/2018/07/19/python-functions/},
abstract = {Learning to program is not easy. We have to learn a new language and a new way of thinking. We have to learn the grammatical rules of the programming language we are learning, and the logic of our …},
language = {en},
urldate = {2021-11-29},
journal = {Scientifically Sound},
author = {Martin Héroux},
month = July,
year = {2018},
}
@misc{Hildebr2020,
title = {Your {Code} {Sucks}! – {Code} {Review} {Best} {Practices}},
url = {https://quickbirdstudios.com/blog/code-review-best-practices-guidelines/},
abstract = {Plenty of things can go wrong in code reviews that can render the entire process useless. We waste time, money, energy and patience without really improving the quality of our code. There are tons of online courses and tutorials available writing code – but almost none for reviewing code. We intend to change that: Here's your ultimate guide for how to get the most of code reviews!},
language = {en-US},
urldate = {2021-11-02},
journal = {QuickBird Studios Blog},
author = {Hildebr, Mischa},
month = mar,
year = {2020},
}
@misc{Hobert2018,
title = {Writing {Variable} — {Informative}, {Descriptive} \& {Elegant}},
url = {https://medium.datadriveninvestor.com/writing-variable-informative-descriptive-elegant-1dd6f3f15db3},
abstract = {There are only two hard things in Computer Science: cache invalidation and naming things. — Phil Karlton},
language = {en},
urldate = {2021-10-29},
journal = {Medium},
author = {Hobert, Kevin},
month = September,
year = {2018},
}
@article{Hothorn2011,
title = {Case studies in reproducibility},
volume = {12},
issn = {1467-5463},
url = {https://doi.org/10.1093/bib/bbq084},
doi = {10.1093/bib/bbq084},
abstract = {Reproducible research is a concept of providing access to data and software along with published scientific findings. By means of some case studies from different disciplines, we will illustrate reasons why readers should be given the possibility to look at the data and software independently from the authors of the original publication. We report results of a survey comprising 100 papers recently published in Bioinformatics. The main finding is that authors of this journal share a culture of making data available. However, the number of papers where source code for simulation studies or analyzes is available is still rather limited.},
number = {3},
urldate = {2021-10-06},
journal = {Briefings in Bioinformatics},
author = {Hothorn, Torsten and Leisch, Friedrich},
month = May,
year = {2011},
pages = {288--300},
}
@article{Ioannidis2009,
title = {Repeatability of published microarray gene expression analyses},
volume = {41},
issn = {1546-1718},
doi = {10.1038/ng.295},
abstract = {Given the complexity of microarray-based gene expression studies, guidelines encourage transparent design and public data availability. Several journals require public data deposition and several public databases exist. However, not all data are publicly available, and even when available, it is unknown whether the published results are reproducible by independent scientists. Here we evaluated the replication of data analyses in 18 articles on microarray-based gene expression profiling published in Nature Genetics in 2005-2006. One table or figure from each article was independently evaluated by two teams of analysts. We reproduced two analyses in principle and six partially or with some discrepancies; ten could not be reproduced. The main reason for failure to reproduce was data unavailability, and discrepancies were mostly due to incomplete data annotation or specification of data processing and analysis. Repeatability of published microarray studies is apparently limited. More strict publication rules enforcing public data availability and explicit description of data processing and analysis should be considered.},
language = {eng},
number = {2},
journal = {Nature Genetics},
author = {Ioannidis, John P. A. and Allison, David B. and Ball, Catherine A. and Coulibaly, Issa and Cui, Xiangqin and Culhane, Aedín C. and Falchi, Mario and Furlanello, Cesare and Game, Laurence and Jurman, Giuseppe and Mangion, Jon and Mehta, Tapan and Nitzberg, Michael and Page, Grier P. and Petretto, Enrico and van Noort, Vera},
month = February,
year = {2009},
pmid = {19174838},
keywords = {Animals, Data Interpretation, Statistical, Databases, Genetic, Gene Expression Profiling, Genome-Wide Association Study, Humans, Oligonucleotide Array Sequence Analysis, Peer Review, Research, Publications, Reproducibility of Results},
pages = {149--155},
}
@misc{Joseph2017,
author = {Max Joseph, Leah Wasser, Software Carpentry, Reproducible Science Curriculum Community, Bryce Mecum},
title = {Write {Efficient} {Scientific} {Code} - the {DRY} ({Don}’t {Repeat} {Yourself}) {Principle}},
url = {https://www.earthdatascience.org/courses/earth-analytics/automate-science-workflows/write-efficient-code-for-science-r/},
abstract = {This lesson will cover the basic principles of using functions and why they are important.},
language = {en},
urldate = {2021-11-29},
journal = {Earth Data Science - Earth Lab},
month = mar,
year = {2017},
}
@inproceedings{Jupyter2016,
booktitle = {Positioning and Power in Academic Publishing: Players, Agents and Agendas},
editor = {Fernando Loizides and Birgit Scmidt},
title = {Jupyter Notebooks - a publishing format for reproducible computational workflows},
author = {Thomas Kluyver and Benjamin Ragan-Kelley and Fernando P{\'e}rez and Brian Granger and Matthias Bussonnier and Jonathan Frederic and Kyle Kelley and Jessica Hamrick and Jason Grout and Sylvain Corlay and Paul Ivanov and Dami{\'a}n Avila and Safia Abdalla and Carol Willing and Jupyter development team},
publisher = {IOS Press},
address = {Netherlands},
year = {2016},
pages = {87--90},
url = {https://eprints.soton.ac.uk/403913/},
abstract = {It is increasingly necessary for researchers in all fields to write computer code, and in order to reproduce research results, it is important that this code is published. We present Jupyter notebooks, a document format for publishing code, results and explanations in a form that is both readable and executable. We discuss various tools and use cases for notebook documents.}
}
@misc{Keeton2019,
author = {BJ Keeton},
month = {April},
year = {2019},
title = {How to {Comment} {Your} {Code} {Like} a {Pro}: {Best} {Practices} and {Good} {Habits}},
url = {https://www.elegantthemes.com/blog/wordpress/how-to-comment-your-code-like-a-pro-best-practices-and-good-habits},
abstract = {Writing code is a lot like writing prose. Every person does it a little differently, and because of that, we all have a distinct voice when our code is read. We have different naming conventions and different problem-solving logic. We all think our code makes sense — especially if it works — but...},
language = {en},
urldate = {2021-10-29},
journal = {Elegant Themes},
}
@misc{Klinefelter2016,
author = {Sarah Klinefelter},
month = {August},
year = {2016},
title = {{DRY} {Programming} {Practices} – {Metova}},
url = {https://metova.com/dry-programming-practices/},
language = {en-US},
urldate = {2021-10-29},
}
@misc{Kostyuk2020,
title = {Data {Science} {Python} {Best} {Practices}},
url = {https://medium.com/bcggamma/data-science-python-best-practices-fdb16fdedf82},
abstract = {Write production-level code!},
language = {en},
urldate = {2021-11-02},
journal = {BCG GAMMA},
author = {Kostyuk, Victor},
month = May,
year = {2020},
}
@misc{Koehrsen2019,
title = {Data {Scientists}: {Your} {Variable} {Names} {Are} {Awful}. {Here}’s {How} to {Fix} {Them}.},
shorttitle = {Data {Scientists}},
url = {https://towardsdatascience.com/data-scientists-your-variable-names-are-awful-heres-how-to-fix-them-89053d2855be},
abstract = {A Simple Way to Greatly Improve Code Quality},
language = {en},
urldate = {2021-10-29},
journal = {Medium},
author = {Koehrsen, Will},
month = July,
year = {2019},
}
@misc{Lee2019,
title = {Why {Git} {And} {How} {To} {Use} {Git} {As} {A} {Data} {Scientist}},
url = {https://towardsdatascience.com/why-git-and-how-to-use-git-as-a-data-scientist-4fa2d3bdc197},
abstract = {Perhaps you’ve heard of Git somewhere else.},
language = {en},
urldate = {2021-10-20},
journal = {Medium},
author = {Lee, Admond},
month = December,
year = {2019},
}
@misc{Meza2018,
title = {The {Value} of {Code} {Documentation}},
url = {https://www.olioapps.com/blog/the-value-of-code-documentation/},
abstract = {Code documentation is the collection of easy to understand images and written descriptions that explain what a codebase does and how it can be used.},
language = {en},
urldate = {2021-10-29},
journal = {Olio Apps},
author = {Meza, Frank},
month = February,
year = {2018},
}
@misc{Mustafeez2021,
author = {Anusheh Zohair Mustafeez},
title = {Absolute vs. relative path},
url = {https://www.educative.io/edpresso/absolute-vs-relative-path},
language = {en-us},
urldate = {2021-11-02},
journal = {Educative},
year = {2021},
}
@misc{Navarro2021,
title = {Project structure},
url = {https://www.youtube.com/playlist?list=PLRPB0ZzEYegPiBteC2dRn95TX9YefYFyy},
language = {english},
urldate = {2021-11-30},
author = {Danielle Navarro},
month = March,
year = {2021},
}
@misc{Neuzerling2018,
title = {{useR}: {Getting} started with {R} and {Docker}},
shorttitle = {{useR}},
url = {https://mdneuzerling.com/post/user-getting-started-with-r-and-docker/},
abstract = {These are my notes for the super helpful tutorial given by Elizabeth Stark on the first day of the UseR 2018 conference. This was an introduction to Docker for R users who have no prior experience with Docker (which was me!).
Elizabeth’s slides Elizabeth’s exercises and examples This tutorial took me through setting up an RStudio Server container. I’m on a Linux machine, but I’m particularly interested by the idea that you could run these traditionally Linux-only servers on a Windows machine through Docker.},
language = {en},
urldate = {2021-11-17},
month = July,
year = {2018},
author = {David Neuzerling},
}
@article{Orosz2019,
url = {https://blog.pragmaticengineer.com/readable-code/},
year = {2019},
month = December,
author = {Gergely Orosz},
title = {Readable Code},
}
@misc{Okada2021,
title = {How to {Run} {Jupyter} {Notebook} on {Docker}},
url = {https://towardsdatascience.com/how-to-run-jupyter-notebook-on-docker-7c9748ed209f},
abstract = {No more Python env and package update},
language = {en},
urldate = {2021-11-17},
journal = {Medium},
author = {Okada, Shinichi},
month = August,
year = {2021},
}
@misc{openscilabs2021,
title = {Launching {RStudio} in {Docker}},
url = {https://jsta.github.io/r-docker-tutorial/02-Launching-Docker.html},
urldate = {2021-11-17},
author = {openscilabs},
year = {2021},
}
@article{Parker2017,
doi = {10.7287/peerj.preprints.3210v1},
url = {https://doi.org/10.7287/peerj.preprints.3210v1},
year = {2017},
month = August,
publisher = {{PeerJ}},
author = {Hilary Parker},
title = {Opinionated analysis development}
}
@techreport{Patil2016,
title = {A statistical definition for reproducibility and replicability},
copyright = {© 2016, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution 4.0 International), CC BY 4.0, as described at http://creativecommons.org/licenses/by/4.0/},
url = {https://www.biorxiv.org/content/10.1101/066803v1},
abstract = {Everyone agrees that reproducibility and replicability are fundamental characteristics of scientific studies. These topics are attracting increasing attention, scrutiny, and debate both in the popular press and the scientific literature. But there are no formal statistical definitions for these concepts, which leads to confusion since the same words are used for different concepts by different people in different fields. We provide formal and informal definitions of scientific studies, reproducibility, and replicability that can be used to clarify discussions around these concepts in the scientific and popular press.},
language = {en},
urldate = {2021-10-06},
author = {Patil, Prasad and Peng, Roger D. and Leek, Jeffrey T.},
month = July,
year = {2016},
note = {Type: article},
pages = {066803},
}
@misc{PEP8,
title = {{PEP} 8 -- {Style} {Guide} for {Python} {Code}},
url = {https://www.python.org/dev/peps/pep-0008/},
abstract = {The official home of the Python Programming Language},
language = {en},
urldate = {2021-10-29},
journal = {Python.org},
year = {2021},
}
@misc{Python2021,
title = {Python 3's f-{Strings}: {An} {Improved} {String} {Formatting} {Syntax} ({Guide}) – {Real} {Python}},
shorttitle = {Python 3's f-{Strings}},
url = {https://realpython.com/python-f-strings/},
abstract = {As of Python 3.6, f-strings are a great new way to format strings. Not only are they more readable, more concise, and less prone to error than other ways of formatting, but they are also faster! By the end of this article, you will learn how and why to start using f-strings today.},
language = {en},
urldate = {2021-11-02},
author = {Real Python},
year = {2021},
}
@misc{Programcreek2021,
title = {Python {Examples} of pathlib.{Path}.joinpath},
url = {https://www.programcreek.com/python/example/114070/pathlib.Path.joinpath},
abstract = {This page shows Python examples of pathlib.Path.joinpath},
urldate = {2021-11-02},
year = {2021},
}
@misc{ProjectJupyter2018,
title = {Jupyter {Docker} {Stacks} — docker-stacks latest documentation},
url = {https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html},
urldate = {2021-11-17},
year = {2018},
name = {{Project Jupyter}},
}
@misc{Radigan2021,
title = {Why code reviews matter (and actually save time!)},
url = {https://www.atlassian.com/agile/software-development/code-reviews},
abstract = {Code review helps developers learn the code base, as well as help them learn new technologies and techniques that grow their skill sets.},
language = {en},
urldate = {2021-11-02},
journal = {Atlassian},
author = {Dan Radigan},
year = {2021},
}
@website{refinebio,
author = {Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler.},
title = {refine.bio: a resource of uniformly processed publicly available gene expression datasets.},
url = {https://www.refine.bio},
year = {2021},
}
@misc{Riffomonas2021,
author = {{Riffomonas Project}},
title = {Keeping {R} code {DRY} with functions: {Don}'t repeat yourself! ({CC096})},
shorttitle = {Keeping {R} code {DRY} with functions},
url = {https://www.youtube.com/watch?v=XSRO4VKD-pc},
abstract = {Don't repeat yourself or the DRY principle is one of the best practices to writing good R. When you repeat the same block of code you risk introducing errors...},
language = {en},
urldate = {2021-11-29},
year = {2021},
month = {November},
}
@Manual{rmarkdown2021,
title = {rmarkdown: Dynamic Documents for R},
author = {JJ Allaire and Yihui Xie and Jonathan McPherson and Javier Luraschi and Kevin Ushey and Aron Atkins and Hadley Wickham and Joe Cheng and Winston Chang and Richard Iannone},
year = {2021},
note = {R package version 2.10},
url = {https://github.com/rstudio/rmarkdown},
}
@article{Sandve2013,
title = {Ten {Simple} {Rules} for {Reproducible} {Computational} {Research}},
volume = {9},
issn = {1553-7358},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003285},
doi = {10.1371/journal.pcbi.1003285},
language = {en},
number = {10},
urldate = {2021-10-06},
journal = {PLOS Computational Biology},
author = {Sandve, Geir Kjetil and Nekrutenko, Anton and Taylor, James and Hovig, Eivind},
month = October,
year = {2013},
keywords = {Computer applications, Reproducibility, Archives, Computer and information sciences, Source code, Genome analysis, Habits, Replication studies},
pages = {e1003285},
}
@misc{SoftwareCarpentry2021,
title = {Version {Control} with {Git}},
url = {https://swcarpentry.github.io/git-novice/},
urldate = {2021-10-06},
year = {2021},
}
@book{Savonen2021,
author = {Candace Savonen},
title = {Chapter 8 {Creating} clarifying code comments {\textbar} {Documentation} and {Usability}},
url = {https://jhudatascience.org/Documentation_and_Usability/creating-clarifying-code-comments.html#creating-clarifying-code-comments},
abstract = {A course to cover the basics of creating documentation and tutorials to maximize the usability of ITCR tools.},
urldate = {2021-10-29},
year = {2021},
}
@misc{Savonen2021b,
author = {Candace Savonen},
title = {The {Childhood} {Cancer} {Data} {Lab}'s not-so-secret sauce for efficient workflows — aka {Philadelphia}’s third most famous process},
url = {https://www.ccdatalab.org/blog/2021/10/7/not-so-secret-sauce-for-efficient-workflows},
abstract = {‘Work smarter not harder’ is useless advice if you don’t know how to ‘work smarter’. But the Childhood Cancer Data Lab's work and processes may be the smartest I’ve ever had the pleasure of learning and adopting. Their processes are just as valuable to me now that I’ve moved on to the next stage o},
language = {en-US},
urldate = {2021-11-02},
journal = {Childhood Cancer Data Lab},
month = {October},
year = {2021},
}
@misc{Saxena2021,
title = {6 {Mistakes} {Every} {Python} {Beginner} {Should} {Avoid} {While} {Coding}},
url = {https://towardsdatascience.com/6-mistakes-every-python-beginner-should-avoid-while-coding-e57e14917942},
abstract = {These small improvements can be crucial},
language = {en},
urldate = {2021-11-02},
journal = {Medium},
author = {Saxena, Pranjal},
month = August,
year = {2021},
}
@misc{Spertus2021,
title = {Best practices for writing code comments},
url = {https://stackoverflow.blog/2021/07/05/best-practices-for-writing-code-comments/},
abstract = {While there are many resources to help programmers write better code—such as books and static analyzers—there are few for writing better comments. While it's easy to measure the quantity of comments in a program, it's hard to measure the quality, and the two are not necessarily correlated. A bad comment is worse than no comment at all. Here are some rules to help you achieve a happy medium.},
language = {en-US},
urldate = {2021-10-29},
journal = {Stack Overflow Blog},
author = {Spertus, Ellen},
month = July,
year = {2021},
}
@software{Shapiro2021,
author = {Shapiro, Joshua A. and Savonen, Candace L. and Hawkins, Allegra G. and Bethell, Chante J. and Venkatesh Prasad, Deepashree and Greene, Casey S. and Taroni, Jaclyn N.},
month = {June},
title = {{Childhood Cancer Data Lab Training Modules}},
version = {2021-june},
year = {2021}
}
@misc{Severin2021,
title = {Project {Management}},
url = {https://bioinformaticsworkbook.org/projectManagement/Intro_projectManagement.html},
abstract = {A workbook to help scientists working on bioinformatics projects},
language = {en},
urldate = {2021-10-14},
journal = {Bioinformatics Workbook},
author = {Severin, Andrew},
year = {2021},
}
@article{Shih2017,
doi = {10.1158/2159-8290.cd-16-1049},
url = {https://doi.org/10.1158/2159-8290.cd-16-1049},
year = {2017},
month = February,
publisher = {American Association for Cancer Research ({AACR})},
volume = {7},
number = {5},
pages = {494--505},
author = {Alan H. Shih and Cem Meydan and Kaitlyn Shank and Francine E. Garrett-Bakelman and Patrick S. Ward and Andrew M. Intlekofer and Abbas Nazir and Eytan M. Stein and Kristina Knapp and Jacob Glass and Jeremy Travins and Kim Straley and Camelia Gliser and Christopher E. Mason and Katharine Yen and Craig B. Thompson and Ari Melnick and Ross L. Levine},
title = {Combination Targeted Therapy to Disrupt Aberrant Oncogenic Signaling and Reverse Epigenetic Dysfunction in {IDH}2- and {TET}2-Mutant Acute Myeloid Leukemia},
journal = {Cancer Discovery}
}
@misc{Smartbear2021,
title = {Best {Practices} for {Code} {Review}},
url = {https://smartbear.com/en/learn/code-review/best-practices-for-peer-code-review/},
abstract = {A successful peer review strategy requires balance between strictly documented processes and a non-threatening, collaborative environment. Highly regimented peer reviews can stifle productivity, yet lackadaisical processes are often ineffective. Managers are responsible for finding a middle groun...},
urldate = {2021-11-02},
journal = {smartbear.com},
year = {2021},
author = {Smartbear Team},
}
@misc{Smith2013,
author = {Steve Smith},
title = {Don't {Repeat} {Yourself} - {Programmer} 97-things},
url = {https://web.archive.org/web/20131204221336/http://programmer.97things.oreilly.com/wiki/index.php/Don't_Repeat_Yourself},
urldate = {2021-11-02},
month = December,
year = {2013},
}
@misc{Soage2020,
author = {Jose Carlos Soage},
title = {{SET} {SEED} in {R} with set.seed() function ▷ [{WITH} {EXAMPLES}]},
url = {https://r-coder.com/set-seed-r/},
abstract = {Set seed in R to generate reproducible pseudorandom numbers 🌱🌱 Learn the meaning of setseed in R, why to use the set.seed function and how it works},
language = {en-US},
urldate = {2021-11-02},
journal = {R CODER},
month = July,
year = {2020},
}
@blog{Spielman,
author = {Stephanie Spielman},
title = {Introduction to R - CB2R Data Science Workshop, Summer 2020},
url = {https://github.com/sjspielman/cb2r-ds-summer2020/blob/71cb11277e7383292bf727841ab5fa4ed43cfcbe/resources/introduction_to_R.Rmd#L92},
}
@misc{Srivastav2018,
title = {A {Docker} {Tutorial} for {Beginners}},
url = {https://docker-curriculum.com/},
abstract = {Learn to build and deploy your distributed applications easily to the cloud with Docker},
language = {en-us},
urldate = {2021-11-17},
journal = {A Docker Tutorial for Beginners},
author = {Srivastav, Prakhar},
year = {2018},
}
@misc{Tayo2019,
title = {How to {Organize} {Your} {Data} {Science} {Project}},
url = {https://towardsdatascience.com/how-to-organize-your-data-science-project-dd6599cf000a},
abstract = {A tutorial on data science project organization},
language = {en},
urldate = {2021-10-12},
journal = {Medium},
author = {Benjamin Obi Tayo},
month = December,
year = {2019},
}
@misc{Tidyverse2021,
title = {Read a delimited file (including {CSV} and {TSV}) into a tibble — read\_delim},
url = {https://readr.tidyverse.org/reference/read_delim.html},
abstract = {read\_csv() and read\_tsv() are special cases of the more general
read\_delim(). They're useful for reading the most common types of
flat file data, comma separated values and tab separated values,
respectively. read\_csv2() uses ; for the field separator and , for the
decimal point. This format is common in some European countries.},
language = {en},
urldate = {2021-11-02},
}
@misc{Tran2021,
title = {Python {Clean} {Code}: 6 {Best} {Practices} to {Make} your {Python} {Functions} more {Readable}},
shorttitle = {Python {Clean} {Code}},
url = {https://towardsdatascience.com/python-clean-code-6-best-practices-to-make-your-python-functions-more-readable-7ea4c6171d60},
abstract = {Stop Writing Python Functions that Take more than 3 Minutes to Understand},
language = {en},
urldate = {2021-11-05},
journal = {Medium},
author = {Tran, Khuyen},
month = January,
year = {2021},
}
@misc{Vidhya2019,
author = {Analytics Vidhya Team},
title = {What is {Tidyverse} {\textbar} {Tidyverse} {Package} in {R}},
url = {https://www.analyticsvidhya.com/blog/2019/05/beginner-guide-tidyverse-most-powerful-collection-r-packages-data-science/},
abstract = {Tidyverse is the most powerful collection of R packages. Learn about the tidyverse package in R and how each package works and get the full code here.},
language = {en},
urldate = {2021-11-02},
journal = {Analytics Vidhya},
month = May,
year = {2019},
}
@misc{Vickery2021,
title = {4 {Tools} for {Reproducible} {Jupyter} {Notebooks}},
url = {https://towardsdatascience.com/4-tools-for-reproducible-jupyter-notebooks-d7423721bd04},
abstract = {Jupyter notebooks have a somewhat poor reputation in the wider programming community. Joel Grus’ famous “I don’t like notebooks” talk, which he bravely gave at JupyterCon in 2018, covered many of the…},
language = {en},
urldate = {2021-10-06},
journal = {Medium},
author = {Vickery, Rebecca},
month = May,
year = {2021},
}
@misc{Wasser2019,
author = {Leah Wasser, Jenny Palomino},
title = {{DRY} {Code} and {Modularity}},
url = {https://www.earthdatascience.org/courses/intro-to-earth-data-science/write-efficient-python-code/intro-to-clean-code/dry-modular-code/},
abstract = {DRY (Do Not Repeat Yourself) code supports reproducibility by removing repetition and making code easier to read. Learn about key strategies to write DRY code in Python.},
language = {en},
urldate = {2021-11-29},
journal = {Earth Data Science - Earth Lab},
month = September,
year = {2019},
}
@misc{Wickham,
author = {Hadley Wickham},
title = {Style guide · {Advanced} {R}.},
url = {http://adv-r.had.co.nz/Style.html},
urldate = {2021-10-29},
year = {2019},
}
@book{Wright2021,
title = {Chapter 1 {Introduction} to the {Tidyverse} {\textbar} {Tidyverse} {Skills} for {Data} {Science}},
url = {http://jhudatascience.org/tidyversecourse/intro.html},
abstract = {This book demonstrates how to use the Tidyverse collection of packages for doing data science.},
urldate = {2021-11-02},
author = {Carrie Wright, Shannon E. Ellis, Stephanie C. Hicks {and} Roger D. Peng},
}
@Book{Xie2018,
title = {R Markdown: The Definitive Guide},
author = {Yihui Xie and J.J. Allaire and Garrett Grolemund},
publisher = {Chapman and Hall/CRC},
address = {Boca Raton, Florida},
year = {2018},
note = {ISBN 9781138359338},
url = {https://bookdown.org/yihui/rmarkdown},
}
@Book{Xie2020,
title = {R Markdown Cookbook},
author = {Yihui Xie and Christophe Dervieux and Emily Riederer},
publisher = {Chapman and Hall/CRC},
address = {Boca Raton, Florida},
year = {2020},
note = {ISBN 9780367563837},