Merge pull request #19 from albarema/main

update news

_quarto.yml

@@ -14,8 +14,8 @@ website:
         text: HPC access
       - href: modules/index.qmd
         text: Modules
-      - href: workshop/workshop_june24.qmd
-        text: RNAseq Workshop
+#      - href: workshop/workshop_june24.qmd
+#        text: RNAseq Workshop
       - text: Datasets
         menu:
           - href: datasets/datapolicy.qmd

news.qmd

@@ -6,7 +6,7 @@ format:
 listing:
   - id: "upcoming_event"
     image-height: 300px
-    grid-columns: 4
+    grid-columns: 3
     image-placeholder: "./img/logo.png"
     fields: [image,title, description,categories, date]
     contents: news/upcoming/*.qmd

news/upcoming/2024-07-01-NGS-analysis.qmd → news/past/2024-07-01-NGS-analysis.qmd

@@ -1,8 +1,5 @@
 ---
 title: "Intro to NGS data analysis - Summer School"
-description: "Fully booked"
-image: "./ngs-july-24.png"
-author: Samuele Soraggi
 Organizers:  Samuele Soraggi
 date: 2024-07-01
 Dates: "01-05 July 2024"

news/upcoming/2024-08-21-BinfConference.qmd

@@ -0,0 +1,19 @@
+---
+title: "How I learned to stop worrying and love RDM"
+image: "binfConference_24.png"
+author: "ARM and JB"
+Organizers: Jennifer Bartell
+date: 2024-08-21
+categories: [HPC, RDM, KU, workshop]
+description: Conference workshop
+---
+
+Research data management involves more than just writing your DMP (Data Management Plan). We can assist you in crafting a more meaningful DMP with some practical tips. While DMP are essential in research, they may sometimes seem too general or not directly applicable to the specific challenges you face daily.
+
+Join our workshop to make your research data more FAIR (Findable, Acessible, Interoperable and Reusable). We will cover various topis to enhance your data analysis work and go through several good practices for:
+
+- data organization (incl. file naming)
+- data documentation and file formats
+- data analysis 
+- data storage 
+- data archiving 

news/upcoming/2024-10-30-hpcLaunch.qmd

@@ -8,4 +8,6 @@ categories: [HPC, RDM, KU, course]
 description: "Click to sign-up"
 ---
 
-[Sign-up](). 
+[Sign-up](https://eventsignup.ku.dk/hpc-launch)
+
+The goal of the course HPC-Launch is to support the launch (and/or reconfiguration) of health data projects from an efficient and modern computing and data management perspective. Targeting trainees and researchers in bioinformatics and large-scale health records, the course will consist of two modules: High-Performance Computing (HPC) and Research Data management (RDM). With the HPC module, we want to expand understanding and efficient use of HPC resources for complex health data science projects. We will fill gaps in technical understanding for beginner to intermediate users of supercomputing platforms and share up-to-date information on computing resources available to Danish researchers and how to get access. With the RDM module, we will introduce the importance of research data management practices and demonstrate practical tips and tools for its implementation at a local research group level. Overall, the course will be a mix of theory, discussion of real-world use cases and participant needs, and active practice/exercises conducted on the HPC platform UCloud (SDU) using bash and relevant IDEs.

news/upcoming/2024-11-15-hpcPipes.qmd

@@ -2,10 +2,13 @@
 title: "HPC Pipes"
 author: "ARM and JB"
 Organizers: Alba
-date: 2024-11-15
+date: 2024-11-04
 categories: [snakemake, conda, KU, course]
 description: "Click to sign-up"
 ---
 
-[Sign-up](). 
+[Sign-up](https://eventsignup.ku.dk/hpc-pipes)
 
+The course HPC-Pipes introduces best practices for setting up, running, and sharing reproducible bioinformatics pipelines and workflows. Rather than instruct on the whys and wherefores of using particular tools for a bioinformatics analysis, we will cover the general process of building a robust pipeline (regardless of data type) using workflow languages, environment/package managers, optimized HPC resources, and FAIRly managed data and tools. On course completion, participants will be able to  use this knowledge to design their own custom pipelines with tools appropriate for their individual analysis needs.
+
+The course will provide guidance on how to automate data analysis using common workflow languages such as Snakemake or Nextflow. Subsequently, we will delve into ensuring the reproducibility of pipelines and explore available options. Participants will learn how to share their data analysis and software with the research community. We will also delve into different strategies for managing the produced research data. This includes addressing the challenges posed by large volumes of data and exploring computational approaches that aid in data organization, documentation, processing, analysis, storing, sharing, and preservation. These discussions will encompass the reasons behind the increasing popularity of Docker and other containers, along with demonstrations on how to effectively utilize package and environment managers like Conda to control the software environment within a workflow. Finally, participants will learn how to manage and optimize their pipeline projects on HPC platforms, using compute resources efficiently.