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diff --git a/lectures/putting-it-together/putting-it-together.Rmd b/lectures/putting-it-together/putting-it-together.Rmd
deleted file mode 100644
index 553b22c0..00000000
--- a/lectures/putting-it-together/putting-it-together.Rmd
+++ /dev/null
@@ -1,322 +0,0 @@
----
-title: "Putting it all together"
-subtitle: "Tools for Reproducible Research NBIS course"
-output:
- xaringan::moon_reader:
- self-contained: true
- seal: false
- css: ["default", "../template.css"]
- nature:
- slideNumberFormat: ""
----
-
-```{r Setup, include = FALSE}
-# Chunk options
-knitr::opts_chunk$set(include = FALSE,
- echo = FALSE)
-```
-
-layout: true
-
-
-
----
-
-class: center, middle
-.HUGE[Putting it all together]
-
----
-
-class: center, middle
-
-Take control of your research project
-by making its different components reproducible
-
-
-
----
-
-class: center, middle
-
-By working reproducibly you will also make your life a lot easier!
-
-
-
----
-
-# What have we learned?
-
-
-
-* How to use the version control system .green[Git] to track changes to code
-* How to use the package and environment manager .green[Conda]
-* How to use the workflow managers .green[Snakemake] and .green[Nextflow]
-* How to use .green[R Markdown] and .green[Jupyter] to generate automated reports and to document your analyses
-* How to use .green[Docker] and .green[Singularity] to distribute containerized
- computational environments
-
----
-
-# Divide your work into distinct projects
-
---
-
-* Keep all .green[files] needed to go from raw data to final results in a dedicated directory
-
---
-
-* Use relevant .green[subdirectories]
-
---
-
-* Use .green[Git] to version control your projects
-
---
-
-* Do not store data and results/output in your Git repository
-
---
-
-* When in doubt, commit often instead of seldom
-
----
-
-# Find your own project structure
-
-.pull-left[
-.small[An example .green[Snakemake]-based project:]
-```no-highlight
-project/
- ├── code/
- ├── data/
- │ ├── meta/
- │ ├── raw_external/
- │ └── raw_internal/
- ├── doc/
- ├── intermediate/
- ├── logs/
- ├── notebooks/
- │ └── Untitled.ipynb
- ├── results/
- │ ├── figures/
- │ ├── reports/
- │ └── tables/
- ├── scratch/
- ├── .gitignore
- ├── config.yml
- ├── environment.yml
- ├── Dockerfile
- ├── README.md
- └── Snakefile
-```
-]
-
-.pull-right[
-.small[An example .green[Nextflow]-based project:]
-```no-highlight
-project/
- ├── bin/
- │ └── report.qmd
- ├── data/
- │ └── metadata.csv
- ├── doc/
- ├── env/
- │ ├── Dockerfile
- │ └── environment.yml
- ├── results/
- ├── .gitignore
- ├── main.nf
- ├── nextflow.config
- └── README.md
-```
-]
-
- * https://github.com/NBISweden/project_template
- * https://github.com/fasterius/nbis-support-template
- * https://github.com/snakemake-workflows/snakemake-workflow-template
-
----
-
-# Treasure your data
-
---
-
-* Keep your input data .green[read-only] - consider it static
-
---
-
-* Don't create different versions of the input data - write a .green[script],
- .green[R Markdown] document, .green[Jupyter] notebook or a .green[Snakemake]
- / .green[Nextflow] workflow if you need to pre-process your input data so that
- the steps can be recreated
-
---
-
-* .green[Backup]! Keep redundant copies in different physical locations
-
---
-
-* Upload your raw data as soon as possible to a .green[public data repository]
-
----
-
-# Organize your coding
-
---
-
-* Avoid generating files .green[interactively] or doing things .green[by hand]
-
- - There is no way to track how they were made
-
---
-
-* Write .green[scripts], .green[R Markdown] documents, .green[Jupyter]
- notebooks or .green[Snakemake] / .green[Nextflow] workflows for reproducible
- results to connect raw data to final results
-
---
-
-* Keep the .green[parameters] separate (*e.g.* at top of file or in a separate configuration file)
-
----
-
-# What is reasonable for your project?
-
---
-
-.pull-left[
code/ Code needed to go from input files to final results
+data/ Raw data - this should never edited
+doc/ Documentation of the project
+env/ Environment-related files, e.g. Conda environments or Dockerfiles
+results/ Output from workflows and analyses
+README.md Project description and instructions
Don’t create different versions of the input data - write a script, Quarto document, Jupyter notebook or a Snakemake / Nextflow workflow if you need to pre-process your input data so that the steps can be recreated
+
Backup! Keep redundant copies in different physical locations
+
Upload your raw data as soon as possible to a public data repository
+
+
+
+
+
Organize your coding
+
+
+
Avoid generating files interactively or doing things by hand
+
Write scripts, R Markdown documents, Jupyter notebooks or Snakemake / Nextflow workflows for reproducible results to connect raw data to final results
+
Keep the parameters separate (e.g. at top of file or in a separate configuration file)
+
+
+
+
+
What is reasonable for your project?
+
+
+
+
+
+
+
+
+
What is reasonable for your project?
+
Minimal
+
Write code in a reproducible way and track your environment
+
+
Track your projects with a Git repository each; publish code with your results on e.g.GitHub
+
Use Conda to install software in environments that can be exported and installed on a different system
+
Publish your environment.yml file along with your code
+
+
+
+
What is reasonable for your project?
+
Good
+
Structure and document your code with notebooks
+
+
Use Quarto or Jupyter notebooks to better keep track of and document your code
+
Track your notebooks with Git
+
+
+
+
What is reasonable for your project?
+
Great
+
Track the full environment and connect your code in a workflow
+
+
Go one step beyond in tracking your environment using Docker or Apptainer
+
Convert your code into a Snakemake / Nextflow workflow
+
Track both your image definitions (e.g. Dockerfiles) as well as your workflows with Git
+
+
+
+
Alternatives
+
Version control
+
+
Git – Widely used and a lot of tools available + GitHub/BitBucket.
+
Mercurial – Distributed model just like Git, close to sourceforge.
+
Subversion – Centralized model unlike git/mercurial; no local repository on your computer and somewhat easier to use.
+
+
+
+
Alternatives
+
Environment / package managers
+
+
Conda – General purpose environment and package manager. Community-hosted collections of tools at bioconda or conda-forge.
+
Pip – Package manager for Python, has a large repository at pypi.
+
Apt/yum/brew – Native package managers for different OS. Integrated in OS and might deal with e.g. update notifications better.
+
Virtualenv – Environment manager used to set up semi-isolated python environments.
+
+
+
+
Alternatives
+
Workflow managers
+
+
Snakemake – Based on Python, easily understandable format, relies on file names.
+
Nextflow – Based on Groovy, uses data pipes rather than file names to construct the workflow.
+
Make – Used in software development and has been around since the 70s. Flexible but notoriously obscure syntax.
+
Galaxy - attempts to make computational biology accessible to researchers without programming experience by using a GUI.
+
+
+
+
Alternatives
+
Literate programming
+
+
Quarto - Developed by Posit (previously RStudio), command-line tool focused on generating high-quality documents in a language-agnostic way
+
Jupyter – Create and share notebooks in a variety of languages and formats by using a web browser.
+
R Markdown – Developed by Posit (previously RStudio), focused on generating high-quality documents.
+
Zeppelin – Developed by Apache. Closely integrated with Spark for distributed computing and Big Data applications.
+
Beaker – Newcomer based on Ipython, just as Jupyter. Has a focus on integrating multiple languages in the same notebook.
+
+
+
+
Alternatives
+
Containerization / virtualization
+
+
Docker – Used for packaging and isolating applications in containers. Dockerhub allows for convenient sharing. Requires root access.
+
Singularity/Apptainer – Simpler Docker alternative geared towards high performance computing. Does not require root.
+
Podman - open source daemonless container tool similar to docker in many regards
+
Shifter – Similar ambition as Singularity, but less focus on mobility and more on resource management.
+
VirtualBox/VMWare – Virtualization rather than containerization. Less lightweight, but no reliance on host kernel.
+
+
class: center, middle
+
+
+
“What’s in it for me?”
+
+
+
+
+
+
+
+
+
NBIS Bioinformatics drop-in
+
Any questions related to reproducible research tools and concepts? Talk to an NBIS expert!
+
+
Online (Zoom)
+
Every Tuesday, 14.00-15.00 (except public holidays)
+
Check www.nbis.se/events for Zoom link and more info
+
+
+
+
Questions?
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/lectures/putting-it-together/putting-it-together.pdf b/lectures/putting-it-together/putting-it-together.pdf
deleted file mode 100644
index 54970ed5..00000000
Binary files a/lectures/putting-it-together/putting-it-together.pdf and /dev/null differ
diff --git a/lectures/putting-it-together/putting-it-together.qmd b/lectures/putting-it-together/putting-it-together.qmd
new file mode 100644
index 00000000..1d31d02c
--- /dev/null
+++ b/lectures/putting-it-together/putting-it-together.qmd
@@ -0,0 +1,191 @@
+---
+title: "Putting it all together"
+format: nbis-revealjs
+---
+
+## Working reproducibly will make your research life a lot easier!
+
+
+
+{height=400 fig-align=center}
+
+## Take control of your research by making its different components reproducible
+
+
+
+{height=400 fig-align=center}
+
+## What have we learned? {.smaller}
+
+{height=300 fig-align=center}
+
+- How to use the version control system [Git]{.green} to track changes to code
+- How to use the package and environment manager [Conda]{.green}
+- How to use the workflow managers [Snakemake]{.green} and [Nextflow]{.green}
+- How to use [Quarto]{.green} and [Jupyter]{.green} to generate automated
+ reports and to document your analyses
+- How to use [Docker]{.green} and [Apptainer]{.green} to distribute
+ containerized computational environments
+
+## Divide your work into distinct projects
+
+::: {.incremental}
+- Keep all [files]{.green} needed to go from raw data to final results in a dedicated directory
+- Use relevant [subdirectories]{.green}
+- Use [Git]{.green} to version control your projects
+- Do not store data and results/output in your Git repository
+- When in doubt, [commit often]{.green} rather than not
+:::
+
+## Find your own project structure
+
+For example:
+```bash
+code/ Code needed to go from input files to final results
+data/ Raw data - this should never edited
+doc/ Documentation of the project
+env/ Environment-related files, e.g. Conda environments or Dockerfiles
+results/ Output from workflows and analyses
+README.md Project description and instructions
+```
+
+
+
+More examples:
+
+- [https://github.com/NBISweden/project_template]()
+- [https://github.com/fasterius/nbis-support-template]()
+- [https://github.com/snakemake-workflows/snakemake-workflow-template]()
+
+## Treasure your data
+
+::: {.incremental}
+- Keep your raw data [read-only]{.green} and static
+- Don't create different versions of the input data - write a [script]{.green},
+ [Quarto]{.green} document, [Jupyter]{.green} notebook or a [Snakemake]{.green}
+ / [Nextflow]{.green} workflow if you need to pre-process your input data so that
+ the steps can be recreated
+- [Backup]{.green}! Keep redundant copies in different physical locations
+- Upload your raw data as soon as possible to a [public data repository]{.green}
+:::
+
+## Organize your coding
+
+::: {.incremental}
+- Avoid generating files [interactively]{.green} or doing things [by
+ hand]{.green}
+- Write [scripts]{.green}, [R Markdown]{.green} documents, [Jupyter]{.green}
+ notebooks or [Snakemake]{.green} / [Nextflow]{.green} workflows for
+ reproducible results to connect raw data to final results
+- Keep the [parameters]{.green} separate (_e.g._ at top of file or in a separate
+ configuration file)
+:::
+
+## What is reasonable for your project?
+
+
+
+{height=450 fig-align=center}
+
+## What is reasonable for your project?
+
+[Minimal]{.green}
+
+_Write code in a reproducible way and track your environment_
+
+- Track your projects with a [Git]{.green} repository each; publish code with
+ your results on _e.g._ [GitHub](https://github.com)
+- Use [Conda]{.green} to install software in environments that can be exported
+ and installed on a different system
+- Publish your `environment.yml` file along with your code
+
+## What is reasonable for your project?
+
+[Good]{.green}
+
+_Structure and document your code with notebooks_
+
+- Use [Quarto]{.green} or [Jupyter]{.green} notebooks to better keep track of
+ and document your code
+- Track your notebooks with Git
+
+## What is reasonable for your project?
+
+[Great]{.green}
+
+_Track the **full** environment and connect your code in a workflow_
+
+- Go one step beyond in tracking your environment using [Docker]{.green} or
+ [Apptainer]{.green}
+- Convert your code into a [Snakemake]{.green} / [Nextflow]{.green} workflow
+- Track both your image definitions (_e.g._ Dockerfiles) as well as your
+ workflows with Git
+
+## Alternatives
+
+[Version control]{.green}
+
+- **Git** – Widely used and a lot of tools available + GitHub/BitBucket.
+- **Mercurial** – Distributed model just like Git, close to sourceforge.
+- **Subversion** – Centralized model unlike git/mercurial; no local repository on your computer and somewhat easier to use.
+
+## Alternatives
+
+[Environment / package managers]{.green}
+
+- **Conda** – General purpose environment and package manager. Community-hosted collections of tools at bioconda or conda-forge.
+- **Pip** – Package manager for Python, has a large repository at pypi.
+- **Apt/yum/brew** – Native package managers for different OS. Integrated in OS and might deal with _e.g._ update notifications better.
+- **Virtualenv** – Environment manager used to set up semi-isolated python environments.
+
+## Alternatives
+
+[Workflow managers]{.green}
+
+- **Snakemake** – Based on Python, easily understandable format, relies on file names.
+- **Nextflow** – Based on Groovy, uses data pipes rather than file names to construct the workflow.
+- **Make** – Used in software development and has been around since the 70s. Flexible but notoriously obscure syntax.
+- **Galaxy** - attempts to make computational biology accessible to researchers without programming experience by using a GUI.
+
+## Alternatives
+
+[Literate programming]{.green}
+
+- **Quarto** - Developed by Posit (previously RStudio), command-line tool focused
+ on generating high-quality documents in a language-agnostic way
+- **Jupyter** – Create and share notebooks in a variety of languages and formats
+ by using a web browser.
+- **R Markdown** – Developed by Posit (previously RStudio), focused on
+ generating high-quality documents.
+- **Zeppelin** – Developed by Apache. Closely integrated with Spark for
+ distributed computing and Big Data applications.
+- **Beaker** – Newcomer based on Ipython, just as Jupyter. Has a focus on
+ integrating multiple languages in the same notebook.
+
+## Alternatives
+
+[Containerization / virtualization]{.green}
+
+- **Docker** – Used for packaging and isolating applications in containers. Dockerhub allows for convenient sharing. Requires root access.
+- **Singularity/Apptainer** – Simpler Docker alternative geared towards high performance computing. Does not require root.
+- **Podman** - open source daemonless container tool similar to docker in many regards
+- **Shifter** – Similar ambition as Singularity, but less focus on mobility and more on resource management.
+- **VirtualBox/VMWare** – Virtualization rather than containerization. Less lightweight, but no reliance on host kernel.
+
+class: center, middle
+
+## "What's in it for me?"
+
+
+
+{height=450 fig-align=center}
+
+## NBIS Bioinformatics drop-in
+
+Any questions related to reproducible research tools and concepts? Talk to an NBIS expert!
+
+- Online ([Zoom]{.green})
+- Every [Tuesday, 14.00-15.00]{.green} (except public holidays)
+- Check [www.nbis.se/events]{.green} for Zoom link and more info
+
+# Questions?
-
----
-
-class: center, middle
-
-By working reproducibly you will also make your life a lot easier!
-
-
-
----
-
-# What have we learned?
-
-
-
----
-
-# NBIS Bioinformatics drop-in
-
-Any questions related to reproducible research tools and concepts? Talk to an NBIS expert!
-
-* Online (.green[Zoom])
-* Every .green[Tuesday, 14.00-15.00] (except public holidays)
-* Check .green[www.nbis.se/events] for Zoom link and more info
diff --git a/lectures/putting-it-together/putting-it-together.html b/lectures/putting-it-together/putting-it-together.html
new file mode 100644
index 00000000..e278a234
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@@ -0,0 +1,2590 @@
+
+
+
+
+
+
+
+
+
+
+
+
+ 
+