diff --git a/02-why-R.Rmd b/02-why-R.Rmd index 0ba411de..2aca9afa 100644 --- a/02-why-R.Rmd +++ b/02-why-R.Rmd @@ -21,9 +21,9 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g21a84b32106_0_9") ``` -[R](https://www.r-project.org/) is a [programming language](https://en.wikipedia.org/wiki/Programming_language) for working with data, performing statistical analyses, and for creating plots and graphics that was developed in 1991 by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand [@r_2023; @r_project]. Countless contributors have made R what it is today. +[R](https://www.r-project.org/) is a [programming language](https://en.wikipedia.org/wiki/Programming_language) for working with data, performing statistical analyses, and for creating plots and graphics that was developed in 1991 by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand [@r_2023; @r_project]. Countless contributors have made R what it is today. -There are some especially useful aspects about R that make it a great option for creating reproducible data analyses. +There are some especially useful aspects about R that make it a great option for creating reproducible data analyses. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "Why is R useful for Reproducibility? 1.It is free and open source, 2. The community, 3. It is designed for data wrangling and stats"} ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.gcf1264c749_0_135") @@ -31,7 +31,7 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ ## It is free and open source -The first is that R is free and [open source](https://opensource.com/resources/what-open-source). +The first is that R is free and [open source](https://opensource.com/resources/what-open-source). ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "Cartoon of parrot saying: What!? R is free!! That's awesome!"} ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g21c5ab757ec_1_0") @@ -39,9 +39,9 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ The term **open source** means that the code is publicly available. -Thus all of the code involved in creating R is actually publicly available! This enables users to check what code is used in a particular **package** (a set of code that allows you to do various things) so that they can modify or build upon the code if they would like to. +Thus all of the code involved in creating R is actually publicly available! This enables users to check what code is used in a particular **package** (a set of code that allows you to do various things) so that they can modify or build upon the code if they would like to. -In fact, many users create their own R **packages** to share their code with others. There are places such as the Comprehensive R Archive Network ([CRAN](https://cran.r-project.org/)) and elsewhere that allow users to publish their own packages for others to use. +In fact, many users create their own R **packages** to share their code with others. There are places such as the Comprehensive R Archive Network ([CRAN](https://cran.r-project.org/)) and elsewhere that allow users to publish their own packages for others to use.
- **programming language** - A specified set of notations to tell a computer what to do @@ -51,7 +51,7 @@ In fact, many users create their own R **packages** to share their code with oth
-Why are these aspects good for reproducibility? +Why are these aspects good for reproducibility? - Since R is free, it is accessible to anyone. Therefore, anyone could run your code if you shared it with them, without them needing to buy software. - Since R is open source, if you use packages from others, people can determine what underlying code your code used (if you tell them what version you used - more on that later!) @@ -60,7 +60,7 @@ Why are these aspects good for reproducibility? R has a very rich and active community! -This makes it easier to reach out to others for help, find support, find tutorials, and more. +This makes it easier to reach out to others for help, find support, find tutorials, and more. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "Cartoon of parrot saying: The R community can support me to learn about R"} ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g21c5ab757ec_0_6") @@ -70,19 +70,19 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ There are several R community groups that are especially helpful: -- [R Ladies](https://www.rladies.org/) - a support group that is not just for ladies, but is open to anyone who wants to improve their R skills! There are local chapters in many large cities that often have in-person meetings. +- [R Ladies](https://rladies.org/) - a support group that is not just for ladies, but is open to anyone who wants to improve their R skills! There are local chapters in many large cities that often have in-person meetings. - There are lots of useful resources, such as the [R for Data Science book](https://r4ds.had.co.nz/) (written by two developers at Posit (formally called RStudio) which develops lots of core R packages), resources and online courses from the [Johns Hopkins Data Science Lab](https://jhudatascience.org/courses.html) including [Open Case Studies](https://www.opencasestudies.org/), resources and workshops from [Data Carpentry](https://datacarpentry.org/), [Dataquest](https://www.dataquest.io/v2/), [DataTrail](https://datatrail-jhu.github.io/DataTrail/) and more! See this [link](https://jhudatascience.org/intro_to_r/resources.html) for more R resources. Why is this rich community good for reproducibility? -- Overall your code has a better chance of being more accessible than if it were written in a language that is not open source or that has limited support. +- Overall your code has a better chance of being more accessible than if it were written in a language that is not open source or that has limited support. - You can also find support to make sure your code does what you want it to, as well as support to make your code as reproducible as possible. ## Designed for data -R is a statistical programming language, meaning it was designed to help you analyze data. It is the main focus of the language. This is one of the major advantages of using R over other programming languages that have more general purposes. +R is a statistical programming language, meaning it was designed to help you analyze data. It is the main focus of the language. This is one of the major advantages of using R over other programming languages that have more general purposes. Because of this many people have designed useful packages that are especially relevant to: @@ -92,7 +92,7 @@ Because of this many people have designed useful packages that are especially re Although other options like [SPSS](https://www.ibm.com/products/spss-statistics) and [SAS](https://www.sas.com/) (which are not free!) can also be helpful for statistical analysis, R is especially powerful at getting messy data ready to analyze and for creating useful plots to represent patterns in data. Conveniently, R can do all of these steps in a data project and does not require users to switch between different programs to perform these tasks. R also helps create reports that can demonstrate to collaborators and others exactly how analysis was performed, aiding in the transparency of how the data was used from start to finish. -R can also import data from many different sources that other statistical software can't handle (including scraping data from websites or [PDFs](https://www.adobe.com/acrobat/about-adobe-pdf.html)). This allows users much more flexibility to use data as close to the source as possible. This can enable users to stop copy and pasting data and reduce the risk of human error. If you are interested, see [Open Case Studies](https://www.opencasestudies.org/) for more guidance on importing many different kinds of data. +R can also import data from many different sources that other statistical software can't handle (including scraping data from websites or [PDFs](https://www.adobe.com/acrobat/about-adobe-pdf.html). This allows users much more flexibility to use data as close to the source as possible. This can enable users to stop copy and pasting data and reduce the risk of human error. If you are interested, see [Open Case Studies](https://www.opencasestudies.org/) for more guidance on importing many different kinds of data. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "I created errors copying my data into Excel and spent hours figuring it out later! I’m glad R can help!"} ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g21c5ab757ec_0_78") @@ -101,7 +101,7 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ Why are these design features especially helpful for creating reproducible analyses? -1. It enables users to work with messy data and get it ready for analysis, as opposed to requiring users to use other programs. The `tidyverse` a suite of very helpful packages has many data wrangling packages that are especially intuitive for others to read and understand your code. +1. It enables users to work with messy data and get it ready for analysis, as opposed to requiring users to use other programs. The `tidyverse` a suite of very helpful packages has many data wrangling packages that are especially intuitive for others to read and understand your code. 1. Users can create effective plots using the same program as for data prep and analysis. The `ggplot2` package is famous for making really effective and customizable plots. 1. It helps create reports that can show the entire data analysis process from importing the data to making plots. `R Markdown` reports are very helpful for this. 1. It is easier to import data closer to the original source, rather than converting files or copy and pasting data, which can result in accidental modifications of the data. @@ -115,12 +115,3 @@ In summary, R can be especially useful if you want to make your data analyses mo 2. There is a rich R community that can help you make the most out of your code and learn how to write your code in a more reproducible manner. 3. R is particularly powerful for preparing data for analysis and for creating visual representations of data. Beyond being free, these unique benefits make R a particularly good statistical tool. 4. R is especially designed to analyze data and for the entirety of the process, which makes it great for creating transparent information about how you actually worked with data from start to finish. - - - - - - - - - diff --git a/04-rstudio-tour.Rmd b/04-rstudio-tour.Rmd index a0a9a9a7..6eacbcff 100644 --- a/04-rstudio-tour.Rmd +++ b/04-rstudio-tour.Rmd @@ -1,7 +1,7 @@ # A Tour of RStudio -In this chapter we will talk about a very useful R-related tool called RStudio. RStudio is an environment for using R that can be extremely helpful for writing code and making your analyses reproducible. +In this chapter we will talk about a very useful R-related tool called RStudio. RStudio is an environment for using R that can be extremely helpful for writing code and making your analyses reproducible. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "A Tour of RStudio, Learning Objectives are to be able to, Recognize why RStudio is useful, Install RStudio and get started with it, Navigate RStudio"} @@ -18,16 +18,16 @@ It is designed to make working in R easier in a variety of ways by helping you: - view the output of your code, this is especially true for creating reports or viewing plots - find errors in your code - keep track of any objects that you have assigned in R -- orient yourself in terms of the files on your computer -- track changes in your code and other files over time +- orient yourself in terms of the files on your computer +- track changes in your code and other files over time
-- **IDE** - Integrated Development Environment - a computing environment for writing code, debugging code, and looking at the output of your code +- **IDE** - Integrated Development Environment - a computing environment for writing code, debugging code, and looking at the output of your code - **RStudio** - an IDE designed especially for writing R code - **function** - a specific piece of code that performs a task - packages in R often have several functions -- **objects** - objects in R could be anything that you can refer to with some name to recall again such as a data tables, vectors, functions, plots and more. +- **objects** - objects in R could be anything that you can refer to with some name to recall again such as a data tables, vectors, functions, plots and more.
@@ -39,9 +39,9 @@ In case you don't yet have RStudio on your computer, we will walk you through th ### Installing and Updating R -You first need to make sure that you have R. R is not the same as RStudio. R is instead the libraries needed to use R code on your computer and it is needed so that you can use RStudio. It is also a good idea to update the version of R that you are using periodically. +You first need to make sure that you have R. R is not the same as RStudio. R is instead the libraries needed to use R code on your computer and it is needed so that you can use RStudio. It is also a good idea to update the version of R that you are using periodically. -
Click here for directions if you have never installed R before on your computer. +
Click here for directions if you have never installed R before on your computer. You can install the latest version of R from the R project site located here: https://www.r-project.org/ @@ -51,7 +51,7 @@ From here you can click on the menu option that says CRAN on the far left to sta ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g20ed7630a13_1_0") ``` -This will take you to a website with a list of what are called [mirrors](https://cran.r-project.org/mirrors.html), which are locations that have the same exact copy of R but are dispersed geographically mostly to improve download speeds for users. Nothing bad will happen if you click on a mirror that isn't closest to you, but it can improve download speeds for everyone overall if people use appropriate mirrors. +This will take you to a website with a list of what are called [mirrors](https://cran.r-project.org/mirrors.html), which are locations that have the same exact copy of R but are dispersed geographically mostly to improve download speeds for users. Nothing bad will happen if you click on a mirror that isn't closest to you, but it can improve download speeds for everyone overall if people use appropriate mirrors. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "CRAN mirror list"} @@ -64,24 +64,24 @@ Once you click on one of the mirror links you will be taken to a new page to dow ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g20ed7630a13_1_19") ``` -You would want to click on the appropriate link for your computer. For example, if you have a Windows machine, click the link for Windows. +You would want to click on the appropriate link for your computer. For example, if you have a Windows machine, click the link for Windows. -This will take you to a new page to select the appropriate link to download R. For Mac users this might be the most recent version of R which will look like R and several numbers afterwards. +This will take you to a new page to select the appropriate link to download R. For Mac users this might be the most recent version of R which will look like R and several numbers afterwards. -
+
Click here for instructions on how to update R. To update R, if you are using a Mac or Linux computer, you can follow the directions of installing R the first time. -If you have a Windows computer, you can use the following code to update your version of R within an R session. You can start an R session by typing `R` into Command Prompt window. If you have not used the Command Prompt window, [read instructions here](https://www.makeuseof.com/tag/a-beginners-guide-to-the-windows-command-line/) about how to find it. After opening your Command Prompt window, copy and paste this code and press enter. +If you have a Windows computer, you can use the following code to update your version of R within an R session. You can start an R session by typing `R` into Command Prompt window. If you have not used the Command Prompt window, [read instructions here](https://www.makeuseof.com/tag/a-beginners-guide-to-the-windows-command-line/) about how to find it. After opening your Command Prompt window, copy and paste this code and press enter. ```{r, eval=FALSE} # Check for the install r package and install if needed if(!require(installr)) { - install.packages("installr"); + install.packages("installr"); require(installr) #load installr pakage -} +} updateR()#update your version of R ``` @@ -90,7 +90,7 @@ updateR()#update your version of R ### Installing RStudio -Next we want to download and install RStudio. You can do so by going to the Posit website at this link: https://posit.co/. Note that you can likely accomplish all you need with the completely free option. +Next we want to download and install RStudio. You can do so by going to the Posit website at this link: https://posit.co/. Note that you can likely accomplish all you need with the completely free option.
@@ -121,7 +121,7 @@ Note that by the time you read this the versions will likely have changed and th You should then be directed by your computer on how to install RStudio once the download is complete. You may need to go to your downloads first and click on the RStudio file that was downloaded to start this process. -For Mac users, note that you will need to move the RStudio icon into the icon that looks like the Applications folder. +For Mac users, note that you will need to move the RStudio icon into the icon that looks like the Applications folder. Drag and drop RStudio into the Applications folder to install on a Mac @@ -130,15 +130,15 @@ Drag and drop RStudio into the Applications folder to install on a Mac ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g20ed7630a13_1_58") ``` -See[here](https://jhudatascience.org/intro_to_r/modules/Setup/R_and_RStudio_installation.html) for more information on the process of installing RStudio. +See[here](https://jhudatascience.org/intro_to_r/modules/RStudio/RStudio.html#1) for more information on the process of installing RStudio. If you run into trouble, check the following: - Did you install the correct version of software for your operating system? - Check that you installed the version right for your type of system, (`macOS` vs `Windows` for example) - - Check if maybe you need a different version for the age of your system. First check that your version of R was right - there are multiple versions for different `macOS` systems for example. You can check the apple icon (top left corner) and "About This Mac" to learn more about the age of your operating system. - -If your operating system is older (and you can't update it), try installing progressively older versions found [here](https://www.rstudio.com/products/rstudio/older-versions/) until it works. You will know if it worked if you try to open RStudio and you see an interface without a message about things going poorly. Here you can see an [example](https://community.rstudio.com/t/rstudio-desktop-crashes-on-startup-with-library-not-loaded/130296) of this. + - Check if maybe you need a different version for the age of your system. First check that your version of R was right - there are multiple versions for different `macOS` systems for example. You can check the apple icon (top left corner) and "About This Mac" to learn more about the age of your operating system. + +If your operating system is older (and you can't update it), try installing progressively older versions found [here](https://www.rstudio.com/products/rstudio/older-versions/) until it works. You will know if it worked if you try to open RStudio and you see an interface without a message about things going poorly. Here you can see an [example](https://community.rstudio.com/t/rstudio-desktop-crashes-on-startup-with-library-not-loaded/130296) of this.
@@ -146,7 +146,7 @@ If your operating system is older (and you can't update it), try installing prog It is also a good idea to keep RStudio up-to-date. New features become available as the Posit team works on developing RStudio. So if you already have RStudio, you might want to check to see if your version is up-to-date. -To check for updates you can go to the `Help` menu at the top of RStudio and then click on `Check for Updates`. +To check for updates you can go to the `Help` menu at the top of RStudio and then click on `Check for Updates`. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "Check for updates for RStudio in the Help menu of RStudio."} ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g20ed7630a13_1_50") @@ -196,7 +196,7 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ -The pane on the left (labeled "Pane 1" in the image) is where we can work on code interactively. There are two tabs here. The Terminal tab and the Console tab. The Terminal tab is for interacting with the computer outside of R. Whereas the Console tab is for interacting with R. We'll focus on the Console tab for now. +The pane on the left (labeled "Pane 1" in the image) is where we can work on code interactively. There are two tabs here. The Terminal tab and the Console tab. The Terminal tab is for interacting with the computer outside of R. Whereas the Console tab is for interacting with R. We'll focus on the Console tab for now. The Console tab is where we can 'talk' to R and interactively work on our code. The code we write here will **not be saved** to a script or file, but instead the code will immediately be performed when we click `enter` and any resulting output that can be printed will be shown. @@ -218,7 +218,7 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ ``` -While there are other tabs, don't worry about those for now. We will go deeper into RStudio as we continue. +While there are other tabs, don't worry about those for now. We will go deeper into RStudio as we continue. Let's try some examples to get started. @@ -237,9 +237,9 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_
-- **Console** - The window that allows us to interactively give R code and press enter to run it but **not save** the code. +- **Console** - The window that allows us to interactively give R code and press enter to run it but **not save** the code. - **Environment** - R's working memory of objects you have assigned -- need to tell R to remember using `<-` -- **Assignment** - How we tell R to remember something using the `<-` characters. +- **Assignment** - How we tell R to remember something using the `<-` characters.
### The Hidden Pane @@ -267,9 +267,9 @@ ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_ This pane is where we can write code that we keep in files like scripts or reports (in files like R Markdowns). -Thus the lower left pane is where we can test out code (although we don't recommend it), but the top pane is where we can write code that we wish to save (and also test it!). Since it can be easy to forget to save code, we suggest that instead you use a special file type that will allow you to test code that you save. We will discuss that in the next section. +Thus the lower left pane is where we can test out code (although we don't recommend it), but the top pane is where we can write code that we wish to save (and also test it!). Since it can be easy to forget to save code, we suggest that instead you use a special file type that will allow you to test code that you save. We will discuss that in the next section. -In order to make our analysis truly reproducible we will need to have **every single step** written down. This is why using the Console is great for testing things, but not so great for actually performing your analysis. +In order to make our analysis truly reproducible we will need to have **every single step** written down. This is why using the Console is great for testing things, but not so great for actually performing your analysis. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "The new pane will open on the upper left and is for writing code we want to save, while the bottom pane is for writing code we want to test."} ottrpal::include_slide("https://docs.google.com/presentation/d/1MNHf8JpolaEP_vQ_kB-1xRBF9wo3haCArRu117hBoHA/edit#slide=id.g20ed7630a13_1_186") @@ -295,12 +295,12 @@ R Markdown files allow you to have the code for your analysis, the output from t ## Find Errors -Another nice thing about RStudio, is that it can help you troubleshoot your code. +Another nice thing about RStudio, is that it can help you troubleshoot your code. It helps to identify common coding mistakes. It will indicate a potential problem by showing a red circle with an "x" in it on the far left of the Editor near the line of code that it thinks is problematic. Note that sometimes errors may occur earlier in your code than where RStudio starts to notice an issue. -Here is an example of such a case. Here we have an extra parentheses in our code. +Here is an example of such a case. Here we have an extra parentheses in our code. ```{r, fig.align='center', out.width="100%", echo = FALSE, fig.alt= "An example of RStudio showing a potential coding error. Hovering over the red circle with the x near the line of code that it sees an issue with, will give a message about what might be wrong."} @@ -312,7 +312,7 @@ Note that just because RStudio thinks your code is free of errors, it does not n ## Keyboard Shortcuts -There are lots of useful keyboard shortcuts for RStudio that can save you time. +There are lots of useful keyboard shortcuts for RStudio that can save you time. Check out this [link](https://support.posit.co/hc/en-us/articles/200711853-Keyboard-Shortcuts) if you are interested! @@ -327,4 +327,3 @@ In summary... - When we open a file like an R Markdown file, the top left pane called the Editor is for writing code we wish to save. - After opening a file, the lower left pane contains the Console which is where we test code. - R Markdown files are files that create reports of an analysis that can demonstrate more about what you did than a simple script and test to make sure that your code works. - diff --git a/09-software-versions.Rmd b/09-software-versions.Rmd index d27eac14..44781df0 100644 --- a/09-software-versions.Rmd +++ b/09-software-versions.Rmd @@ -69,7 +69,7 @@ Printing out session info is an easy way to record your computing environment in However, you may realize that while session info is useful for recording this information, it doesn't mitigate the frustration of setting up a computing environment in R. Nor does it help us with being able to directly share our computing environments. -It can be incredibly handy for reproducibility purposes to be able to share the R computing environment you used for completing an analysis. This is not only helpful for others who may be interested in reproducing your analysis, but also for future you! If you come back to this analysis and attempt to re-run it, it is likely you've changed your R computing environment over time by installing or removing packages. `renv` will allow you to return to the environment you used at the time that you ran the analysis. +It can be incredibly handy for reproducibility purposes to be able to share the R computing environment you used for completing an analysis. This is not only helpful for others who may be interested in reproducing your analysis, but also for future you! If you come back to this analysis and attempt to re-run it, it is likely you've changed your R computing environment over time by installing or removing packages. `renv` will allow you to return to the environment you used at the time that you ran the analysis. For that, we need a slightly more involved solution of using [`renv`](https://rstudio.github.io/renv/articles/renv.html). `renv` is an R package that allows you to take 'snapshots' of your R computing environment and use those to track, share, and build R environments. @@ -111,7 +111,7 @@ In order to truly reproduce a result with an identical computing environment you One of the most popular containerization softwares is Docker. Docker allows you to build your computing environment and share it on its online platform in the form of images that you can download and run. In fact, this book is rendered by a Docker container!
-If you will be using a container with PHI or PII or other protected information, we recommend you take a look at [this resource](https://www.cleardata.com/wp-content/uploads/2017/07/SET-MKTG-WP-36_HIPAA_Compliant_Containers_05-04-2017.pdf) to understand best practices for using Docker with sensitive data. +If you will be using a container with PHI or PII or other protected information, we recommend you take a look at [this resource](https://www.cleardata.com/resources/hipaa-compliant-containers/) to understand best practices for using Docker with sensitive data.
@@ -125,7 +125,7 @@ We will not cover Docker here but if you are interested in using a containerized - [ITCR Training Network chapters about Docker](https://jhudatascience.org/Adv_Reproducibility_in_Cancer_Informatics/launching-a-docker-image.html) - [Docker documentation about getting started](https://www.docker.com/get-started/) - [How to ensure your Docker usage is HIPAA-Compliant](https://www.atlantic.net/hipaa-compliant-hosting/best-practices-for-creating-a-hipaa-compliant-docker-host/) -- [HIPAA Compliant Containers](https://www.cleardata.com/wp-content/uploads/2017/07/SET-MKTG-WP-36_HIPAA_Compliant_Containers_05-04-2017.pdf) +- [HIPAA Compliant Containers](https://www.cleardata.com/resources/hipaa-compliant-containers/) - [Singularity is a different container platform that does some encryption](https://docs.sylabs.io/guides/latest/user-guide/) -- this can help if you are using data that needs to be protected. ## Conclusion diff --git a/resources/dictionary.txt b/resources/dictionary.txt index fd616479..5b482a35 100644 --- a/resources/dictionary.txt +++ b/resources/dictionary.txt @@ -1,3 +1,7 @@ +chatbots +ChatBots +ChatGPT +primetime Cmd Ctrl declutter @@ -80,4 +84,4 @@ underserved VCS www YAML -Yay \ No newline at end of file +Yay