11.10.2023 DDLS education and training

# 11.10.2023 DDLS education and training ## 4th meeting with DDLS fellows ## **Welcome** ## **Code of Conduct reminder** * Be respectful, honest, inclusive, accommodating, appreciative, and open to learning from everyone else. * Do not attack, demean, disrupt, harass, or threaten others or encourage such behavior. * Be patient, allow others to speak, and use the zoom reactions & chat if you would like to voice something. --------- ## **Links & Resources** **Zoom link** https://www.google.com/url?q=https://stockholmuniversity.zoom.us/j/67177687102&sa=D&source=calendar&ust=1697366929408086&usg=AOvVaw1xnAe0eGp-Ew4HMhh9ACCL **Miro board** https://miro.com/app/board/uXjVPZVPbOU=/?share_link_id=7147612421 **Training collection** https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit?usp=sharing **NBIS course catalogue** (https://uppsala.instructure.com/courses/48087/pages/nbis-training-catalogue) **ELIXIR TeSS (European training event catalogue)** (https://tess.elixir-europe.org/) **SciLifeLab training events** (https://www.scilifelab.se/events/#calendar) *email (education@scilifelab.uu.se) if you like to add a course/event to the SciLifeLab calendar* **GU and GU core facility training** (https://www.gu.se/en/core-facilities/bioinformatics-and-data-center-bdc/education-and-training) **Glittr.org: Github repository for Bioinformatics training materials** (https://glittr.org/?per_page=25&sort_by=stargazers&sort_direction=desc) **SIB (Swiss Insitute for Bioinformatics): e-learning collection** (https://www.sib.swiss/training/e-learning) --- ## Rollcall: 🗣 Name/🐸 pronouns/✍Reseach Area/🏼 Affiliation/ favourite candy * Jessica Lindvall / she-her/ Head of Training/ SciLifeLab and NBIS/ Sura kryptoniter * Johan Bengtsson-Palme / he-him / CellMolBio / Chalmers / chocolate * Nicholas Pearce / hehim / CellMolBio / Sour cadillacs * Avlant Nilsson / / Precision medicine / KI / Tyrkisk Peber * Clemens Wittenbecher/Precision medicine/CUT * Patrick Bryant//CellMolBio/SU/chocolate * Cemal Erdem / he-him / Precision medicine / Umeå / All things chocolate * Camila Consiglio / sheher / Infection Biology / Lund / chocolate --- ## **AGENDA** | Duration | Activity | | -------- | -------- | | 5 mins | Welcome, housekeeping, round the table introductions| | 5 mins | Re-cap previous meetings| | 10 mins | **Wei Ouyang et al** short description on the collaborative DDLS fellows course -Super-Resolution Microscopy and Analytics to Investigate Complex Cellular Processes and Diseases | |20 mins | **Discussion and capture** - What knowledge and skills do your PhD students (group members) require? [Gdoc](https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit?usp=sharing) | | 10 mins | **Break** | | 20 mins | **Discussion and capture** - What courses could you co-create? (advanced courses as fellows) [Gdoc](https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit?usp=sharing) | | 10 mins | **Action points** from the discussion and capture | |10 mins | **Elin Kronander (NBIS)** short description of NBIS course catalogue (focus foundational topics)| |10 mins | **Lars Eklund (Uppmax/NBIS)** short description of the Programming Formalism course| | 10 mins | Next steps and wrap-up | --- # Re-cap previous meetings ## [Collaborative training opportunities - add ideas](https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit?usp=sharing) ## Outline Data-driven Life Science knowledge, skills, abilities ![](https://i.imgur.com/Sto1PlA.jpg) #### **Foundational topics** * Data science and Bioinformatics * Mathematics and (bio)statistics * Open Science and FAIR * Research Data Management * ELSI/A and Data ### What knowledge and skills are required? Identifying KSAs (knowledge, skills, abilities) i.e. content/topics/knowledge across foundational categories of what core knowledge is needed to be a Data-driven life scientist ### Mapping existing courses *from the captured excel document [Training collection](https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit?usp=sharing)* **Data science & Bioinformatics courses:** * RaukR (NBIS intermediate/advanced R course/summer school): https://nbisweden.github.io/workshop-RaukR-2206/ * Workshop on Data visualization in R (NBIS/ELIXIR-SE course): (https://uppsala.instructure.com/courses/46547) * Introduction to Python - with application to bioinformatics (NBIS course): (https://uppsala.instructure.com/courses/71521) * Quick and clean: Data Science in Biology using Advanced Python (NBIS advanced Python course): (https://github.com/NBISweden/workshop-advanced-python) * Basic Data Handling and Visualization with R (LU PhD course) * GU and GU Core Facility courses: (https://www.gu.se/en/core-facilities/bioinformatics-and-data-center-bdc/education-and-training) * Unix applied to genomic data * R Programming * Python for biologists * Gene Expression Analysis Using R * Bioinformatics I and II **Mathematics and Biostatistics courses:** * Introduction to Biostatistics and Machine Learning (NBIS course): (https://uppsala.instructure.com/courses/74597) * Neural Networks and Deep Learning (NBIS course): (https://uppsala.instructure.com/courses/75565/pages/schedule) **Open Science and FAIR courses:** * Tools for Reproducible Research (NBIS course): (https://github.com/NBISweden/workshop-reproducible-research/) * Snakemake bring-your-own-code (BYOC) workshop (NBIS course): (https://uppsala.instructure.com/courses/70024) **Research Data Management courses:** * Introduction to Data Management Practices (NBIS course): (https://uppsala.instructure.com/courses/48087/pages/introduction-to-data-management-practices) * Open Science and FAIR (https://github.com/NBISweden/module-open-science-dm-practices) * Data organisation practices (https://github.com/NBISweden/module-organising-data-dm-practices) * Metadata (https://github.com/NBISweden/module-metadata-dm-practices) * Data publication (https://github.com/NBISweden/module-data-publication-dm-practices) * Cleaning tabular data with OpenRefine (https://github.com/NBISweden/module-openrefine-dm-practices) * Introduction to scripted analysis with R (https://github.com/NBISweden/module-r-intro-dm-practices) * Versioning of Data and Code using Git (https://github.com/NBISweden/module-versioning-dm-practices) * Data Management Plans (https://github.com/NBISweden/module-dmp-dm-practices) **ELSI/A and Data courses:** * AI and law (LU MOOC) (https://www.coursera.org/learn/ai-law) * AI, Business & the Future of Work (LU MOOC) (https://www.coursera.org/learn/ai-business-future-of-work) * Artificial Intelligence: Ethical & Societal Challenges (LU MOOC) (https://www.coursera.org/learn/ai-ethics) ---- # Discussion and capture ## What knowledge and skills do your PhD students (group members) require? [Gdoc](https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit#gid=1108957154) ### Notes #### Nick's "two cents" ##### Foundational Courses -- "Primers" - Basic Python - Introduction to programming concepts - Basic plotting (overlap with visualisation) - [Do in their own time? / Offline] - One-week courses for people from different backgrounds (Catchup Courses for "Outsiders") - Bioinformatics in one week - Systems Biology in one week - XXX on one week - Machine Learning for Biologists - A primer for understanding an ML talk - What defines ML, AI? - Types: Supervised, unsupervised, etc. ##### Application Driven Python Courses: - Data Wrangling in Python - Numpy & Pandas - Handing large analyses - Approaches for exploratory data analysis - Large Analyses in Python - Parallelisation patterns - Checkpointing - Containerisation (Is NBIS course already) - Software Development in Python - Sustainable coding/design patterns - Version Control - Use of ChatGPT to power testing and documentation - CI/CD - Automated documentation (e.g. Sphinx) - Code patterns - FAIR by design - Creating and managing complex workflows - Neural Networks in Python - ... - GPU programming in Python (Berzelius) - Advanced Python - GPU programming - Checkpointing - Creating Web(server) resources in Python - Webserver "theory" (components, etc) - Good code patterns to follow (modular, etc, MVC) - Making complex results pages in webservers (Javascript) - Processing on remote compute resoruces and collection of results ##### "Theory" courses - Gold standards for publishing - Publishing FAIR data - Publishing open-source code (licensing) - Publishing reproducible analyses - Scientific Communication - Currently awful basically everywhere - Theory of communication - How to give a talk (how to plan, construct and present) - Scientific Visualisation: theory + practice (in Python) - Currently awful basically everywhere - Concepts & Theory for communicating scienfitic results - How to make good plots - FAIR principles in practice - Currently awful basically everywhere - "The reproducibility crisis" - Reusable code and reproducibile analysis - Publishing the analysis with the data - Data repositories ## What courses could you co-create? (advanced courses as fellows) [Gdoc](https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit#gid=1108957154) ### Notes PUT YOUR NAMES DOWN AS "SIGNUP" - Data interrogation, visualisation and exploration (Data wrangling-adjacent) - Nick - Juliette - Scientific Communication - Nick ---- # Open Discussions Notes: :::success 🏼 *Please add any further notes for the session here:* ::: ____ # Q&A: :::success ❓ *Please add any questions you might have during the course of the session here:* ::: ------- # Wrap up: * * ## Feedback: - How can these meetings be most effective? ## Action points: - Join our [Slack: ](https://scilifelab.slack.com/?redir=%2Farchives%2FC041VD1TL5T) channel: #ddls-education-training - Continue to fill the [Training Collection](https://docs.google.com/spreadsheets/d/18hSpGPnQvnyCeIeT-Ru0nu764Qi8mZWCqfIYgld33Rw/edit?usp=sharing) Google excel - Spread the survey to your local HEI and network '[Training need assessment (data-driven life science)](https://forms.gle/s86Ybzqt8er3EupT7) ## Next meeting 27th of November 2023, 13:00 -- 15_00 --- # Thank you for joining and see you next time!