class: center, middle, inverse, title-slide # Welcome to the R
course! --- layout: true <!-- Introduce instructors and helpers. --> --- # Please do these as we get ready: - ✅ Go to your assigned table and group (see list) - ✅ Introduce yourself to your group members - ✅ Re-install r3 `remotes::install_gitlab("rostools/r3")` - ✅ Accept the GitHub Organization invite --- class: center, middle # Question: ## Before this course... ## How many knew or have heard about <u>reproducibility</u>? ??? Raise your hands. --- class: center, middle # Question: ## Before this course... ## How many knew or have heard about <u>open science</u>? --- class: center, middle # Question: ## Before this course... ## ...or even <u>open access, open data, open methods/protocols, or open source</u>? --- class: middle, center # How many have read a method in a paper and wondered how they <u>actually</u> did it? -- ## ... you've probably realize by now, way more is done than shown in the "Methods" ??? Because you are trying to do the same or similar? --- class: center, middle # Have you ever received confusing code? Or maybe have written your own confusing code? ??? I definitely have in my research career. We want to change the culture around code by encouraging and teaching how to share code and to write better code in general. --- ## Code sharing: From scientific principle of "reproducibility" ... often confused with "replicability" [(https://doi.org/10.3389/fninf.2017.00076)]<sup>1</sup> -- .pull-left[ ### Replicability - Repeating a study by *independently* performing another identical study - Difficult, usually needs funding - Linked to the "irreproducibility crisis"<sup>2</sup> ] -- .pull-right[ ### Reproducibility - Generating the exact same results when using the same data and code - Should be easy right? Wrong, often just as hard - *Question*: If we can't even *reproduce* a studies results, how can we expect to replicate it? ] .footnote[ 1. Also from an American Statistical Association [statement](https://www.amstat.org/asa/files/pdfs/POL-ReproducibleResearchRecommendations.pdf). 2. Or rather "irreplicability crisis". ] --- class: middle, center # Biomedical studies almost entirely don't publish code with the published paper ??? Very few papers provide code [(https://doi.org/10.1146/annurev-statistics-060116-054104); (https://doi.org/10.1007/s11306-017-1299-3)]. Except maybe bioinformatics, where about 60% of studies do. Why? Likely due to: - Lack of awareness and training - Difficulty of adoption - No incentive or reward - Little to no culture to do it --- class: middle, center # These issues can be fixed by creating and nurturing a culture of openness --- class: middle, center # Goal of this course? Start changing the culture by providing the training --- ## Often asked: So why are we using R and why learn it? .pull-left[ - Open source, free - Very large online community - Learning resources, support, help - Massive selection of packages - Latest statistical methods - Productivity tools - Report writing - Visualization ] .pull-right[ - Recent push to improve teaching, usability - e.g. with tidyverse, RStudio - One of best visualization tools available - Powerful capabilities - Big Data - Programming - Reproducibility ] ??? Regarding it being free, that means that you can take the knowledge and skills for using R anywhere you go. --- ## Course setup and layout - Course is mix of: - "Code-alongs" (we type and explain, you type along) - Hands-on exercises - Final group work for [assignment](assignment.html) - Use r3 package to help with learning - True to our mission, material publicly accessible and [openly licensed](https://r-cubed.rostools.org/license.html) - <https://r-cubed.rostools.org/> ??? With the final group project, you'll be in the same group for the course, working together on it and on the final exercises. As a team, you'll help each other out with learning and overcoming any struggles, with of course our help too! --- ## Getting or asking for help 🙋 .pull-left[ - Put the sticky on your laptop to get help - There are lots of helpers - Team members, try to help out too ] .pull-right[ - We're all learning here! - This is a supportive and safe environment - Remember our [Code of Conduct](conduct.html) ] --- class: middle, center ## Practice using stickies: Have you re-installed r3 and joined the GitHub Organization? --- class: middle, center ## Activity: Stand and arrange based on question ??? We're going to do a "stand and re-arrange yourself" activity based on some questions I ask. --- class: middle, center ## Who has not yet used R? ??? Go into different corners for "yes" and "no". --- class: middle, center ## Those who've used R, how do you perceive your skill in R? ??? Along the wall, arrange to one side is "novice/basic" and other side is "advanced". --- class: middle, center ## Those who've used R, have you had formal training in "coding" in R or in general? ??? Raise hands. --- class: middle, center ## Who has struggled with using R? ??? Raise hands. --- class: middle, center ## How do you perceive your general skill in data analysis? ??? Along the wall, arrange from "novice/basic" to "advanced". --- class: middle, center ## Get back into your groups and get to know each other a bit more ??? I've tried to organize the groups to include a range of skills and experiences, so there is a mix of novice and more experienced users. So, as we prepare for the next session, introduce yourselves to the group and get to know each other more. You'll be relying on them for help, so find out who is the "more experienced" R user. --- # References <a name=bib-Plesser2018a></a>[](#cite-Plesser2018a) H. E. Plesser. "Reproducibility Vs. Replicability: A Brief History of a Confused Terminology". In: _Frontiers in Neuroinformatics_ 11 (Jan. 2018). DOI: [10.3389/fninf.2017.00076](https://doi.org/10.3389%2Ffninf.2017.00076). <a name=bib-Leek2017a></a>[](#cite-Leek2017a) J. T. Leek and L. R. Jager. "Is Most Published Research Really False?" In: _Annual Review of Statistics and Its Application_ 4.1 (Mar. 2017), pp. 109-122. DOI: [10.1146/annurev-statistics-060116-054104](https://doi.org/10.1146%2Fannurev-statistics-060116-054104). <a name=bib-Considine2017a></a>[](#cite-Considine2017a) E. C. Considine, G. Thomas, et al. "Critical Review of Reporting of the Data Analysis Step in Metabolomics". In: _Metabolomics_ 14.1 (Dec. 2017). DOI: [10.1007/s11306-017-1299-3](https://doi.org/10.1007%2Fs11306-017-1299-3).