diff --git a/docs/404.html b/docs/404.html index 656d269..43bb1fd 100644 --- a/docs/404.html +++ b/docs/404.html @@ -4,25 +4,25 @@ - Page not found | Microbiome data science with R/Bioconductor + Page not found | Microbiome Data Science & Multi-Omics with R/Bioconducto - + - + - + @@ -132,7 +132,7 @@
diff --git a/docs/index.html b/docs/index.html index 3d5d96e..01c2144 100644 --- a/docs/index.html +++ b/docs/index.html @@ -4,25 +4,25 @@ - Microbiome data science with R/Bioconductor + Microbiome Data Science & Multi-Omics with R/Bioconducto - + - + - + @@ -132,7 +132,7 @@
@@ -141,9 +141,9 @@

1 Overview

diff --git a/docs/index.md b/docs/index.md index 55af8ea..0064ca4 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,7 +1,7 @@ --- -title: "Microbiome data science with R/Bioconductor" +title: "Microbiome Data Science & Multi-Omics with R/Bioconducto" subtitle: "Oulu, December 2024" -date: "2024-10-23" +date: "2024-10-24" site: bookdown::bookdown_site documentclass: book bibliography: [packages.bib] diff --git a/docs/program.html b/docs/program.html index 36bc2a1..d91fd37 100644 --- a/docs/program.html +++ b/docs/program.html @@ -4,25 +4,25 @@ - 2 Program | Microbiome data science with R/Bioconductor + 2 Program | Microbiome Data Science & Multi-Omics with R/Bioconducto - + - + - + @@ -132,7 +132,7 @@
diff --git a/docs/search_index.json b/docs/search_index.json index e52cff3..a668292 100644 --- a/docs/search_index.json +++ b/docs/search_index.json @@ -1 +1 @@ -[["index.html", "Microbiome data science with R/Bioconductor Oulu, December 2024 1 Overview 1.1 Contents and learning goals 1.2 Schedule 1.3 How to apply 1.4 Teachers and organizers 1.5 Code of Conduct 1.6 Acknowledgments", " Microbiome data science with R/Bioconductor Oulu, December 2024 2024-10-23 1 Overview 1.1 Contents and learning goals Contents and learning goals: This course provides an introduction to microbiome data science with R/Bioconductor, a popular open source environment for scientific data analysis. A special emphasis is given to multi-omic data integration methods. After the course you will know how to organize multiple data sources into a coherent framework, implement reproducible data science workflows, and approach common data analysis tasks by utilizing available documentation and R tools. Whereas the primary focus is on microbiome research, the covered data science methods are generally applicable and we will discuss links with other application domains such as transcriptomics, metabolomics, and single cell sequencing. Target audience: MSc students, PhD, postdoctoral, and other researchers who wish to learn new skills in statistical programming and data analysis. Academic students and researchers from Finland and abroad are welcome and encouraged to apply. Teaching material: We will follow open online documentation created by the course teachers, primarily the Orchestrating Microbiome Analysis (OMA) book. The training material walks you through the standard steps of omics data analysis covering data access, exploration, analysis, visualization, and reproducible workflows. Preparatory material and video clips, and online support are available before the course. All teaching materials are shared openly. Figure source: Moreno-Indias et al. (2021) Frontiers in Microbiology 12:11. 1.2 Schedule Venue: University of Oulu. December 18-20, 2024 (Wed-Fri). The course is organized in a live format; no remote option available. Costs: Registration is free. Participants are expected to cover their own travel and accommodation. Accommodation: Housing tips can be found at https://visitoulu.fi/en/arrival-overnight/. Schedule: Contact teaching daily between 9am – 5pm, including lectures, demos, practicals, and breaks. For a detailed schedule, see Section 2. The course can be extended by an independent assignment (details to be agreed with the main teacher). 1.3 How to apply Send a brief motivation letter to Anna Kaisanlahti anna.kaisanlahti@oulu.fi. In your letter, please describe your skill level in R coding using scale 1-5 (1 = no previous experience, 5 = advanced level), and your previous experience related to bioinformatics. Applications from local students, and applications sent before 11 November 2024 will be given priority. The course has maximum capacity of 20 participants. The enrollment to the course will be confirmed within few days after the application deadline (Nov 11). Applications received after 11.11 will also be considered in case there are slots still available. 1.4 Teachers and organizers Teachers: Leo Lahti is the main teacher and Professor in Data Science at the University of Turku, and a certified Carpentries Instructor. PhD researcher Tuomas Borman is a co-teacher and main developer of the data science framework used in the course. Anna Kaisanlahti (Oulu) is a course assistant, and Docent Justus Reunanen is the course coordinator. The course is organized by Health and Biosciences Doctoral Programme (HBS-DP) University of Oulu Graduate School, Research Unit of Translational Medicine, University of Oulu. We thank the Finnish IT Center for Science (CSC) supports the course by providing cloud computing services. This is a Bioconductor course Drnevich et al. (2024) and we follow the best practices recommended by Software carpentries. 1.5 Code of Conduct The Bioconductor community values an open approach to science that promotes the sharing of ideas, code, software and expertise open collaboration and community contributions diversity and inclusivity a kind and welcoming environment More details on its enforcement are available here. 1.6 Acknowledgments Citation: We thank all developers and contributors who have contributed open resources that supported the development of the training material. Kindly cite the course material as Tuomas Borman and Leo Lahti (2024). Contact: Refer to https://microbiome.github.io. License and source code: All material is released under the open CC BY-NC-SA 3.0 License and available online during and after the course, following the recommendations on open teaching materials of the national open science coordination in Finland. References "],["program.html", "2 Program 2.1 Day 1 - Open data science 2.2 Day 2 - Tabular data analysis 2.3 Day 3 - Multi-assay data integration", " 2 Program The course takes place daily from 9am – 5pm (CEST), including coffee, lunch, and short breaks. Most of the time will be dedicated to practical exercises, complemented by short lectures and demos. We expect that participants will prepare for the course in advance. Instructions will be sent to the registered participants. Online support is available. The material follows open online book created by the course teachers, Orchestrating Microbiome Analysis, which supports R/Bioconductor framework for multi-omic data integration and analysis. Figure source: Moreno-Indias et al. (2021) Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions. Frontiers in Microbiology 12:11. 2.1 Day 1 - Open data science Reproducible workflows with R/Bioconductor and Quarto Morning 10-11 Coffee, Welcome & Practicalities 11-12 Learning environment (CSC RStudio notebook and reproducible reporting with Quarto) 12-13 Lunch break Afternoon 13-14 Lecture: open data science 14-16 Working with data containers and workflows 16-17 Q & A 2.2 Day 2 - Tabular data analysis Morning 9-10 Lecture: analysis & visualization of tabular data (single omics) 10-12 Data wrangling, exploration, and summaries 12-13 Lunch break Afternoon 13-14 Univariate data analysis and visualization 14-16 Multivariate data analysis and visualization 16-17 Q & A Evening Course dinner (optional; own cost) 2.3 Day 3 - Multi-assay data integration Morning 9-10 Lecture: analysis & visualization of multi-assay data (multi-omics) 10-12 Multi-assay data analysis and visualization 12-13 Lunch break Afternoon 13-15: Advanced methods (e.g. time series, machine learning, simulation) 15-16: Summary and wrap-up 16-17: Q & A "],["venue.html", "3 Venue 3.1 Tips for visiting Oulu 3.2 Arrival to Oulu 3.3 Public transport 3.4 Electric boards and bikes 3.5 Accommodation", " 3 Venue 3.1 Tips for visiting Oulu Tourist info/city website can be found here. 3.2 Arrival to Oulu Airplane: Airport is located in Oulunsalo, approx. 15km distance away from Oulu city center and the course venue. From the airport it is possible to take a buss (lines 8 and 9) or taxi to Oulu. Train: Train station is located close to the city center (address: Rautatienkatu 11). The train operator, schedules and tickets are available through VR website. 3.3 Public transport General information is available on the ouka website Routes and timetables When traveling by bus you can buy your ticket directly from the bus via contactless payment with debit/credit card, or in advance through either mobile ticket application or ticket machine: Contactless payment. You can use your debit or credit card (Visa, Visa Electron, Mastercard and Eurocard) or mobile (Google Pay and Apple Pay) to pay for your fare. You can use contactless card or device to pay for your own travels only. Mobile ticket (application named Waltti Mobiili): Install Waltti Mobiili application and add your debit/credit card into it, make sure you have enabled online payments. Available payment methods include Visa, Visa Electron or Mastercard. You do not need to register to buy tickets. When you make your first purchase, choose region ”Oulu”. Show the ticket to the driver when you board. At the Waltti ticket machines, you can buy single tickets as well as add more value and seasons to your Waltti travel card. You can find a Waltti ticket machine in example at the following locations: Valkea Shopping Centre, Kesäkatu (next to the ATM) OYS, N-entrance (formerly A3: 1) - photo Oulu Airport, Arrivals Hall (next to screens) 3.4 Electric boards and bikes Below are listed companies offering electric boards and bikes in Oulu area with their websites with instructions for use and rental: Voi Tier Lime 3.5 Accommodation Hotel information in Oulu area can be found here. Below suggestion for hotels in Oulu city centre (via booking.com): Best Western Hotel Apollo De Gamlas Hem Hotel & Restaurant Forenom Aparthotel Oulu Radisson Blu Hotel, Oulu Scandic Oulu City Original Sokos Hotel Arina Oulu "],["404.html", "Page not found", " Page not found The page you requested cannot be found (perhaps it was moved or renamed). You may want to try searching to find the page's new location, or use the table of contents to find the page you are looking for. "]] +[["index.html", "Microbiome Data Science & Multi-Omics with R/Bioconducto Oulu, December 2024 1 Overview 1.1 Contents and learning goals 1.2 Schedule 1.3 How to apply 1.4 Teachers and organizers 1.5 Code of Conduct 1.6 Acknowledgments", " Microbiome Data Science & Multi-Omics with R/Bioconducto Oulu, December 2024 2024-10-24 1 Overview 1.1 Contents and learning goals Contents and learning goals: This course provides an introduction to microbiome data science with R/Bioconductor, a popular open source environment for scientific data analysis. A special emphasis is given to multi-omic data integration methods. After the course you will know how to organize multiple data sources into a coherent framework, implement reproducible data science workflows, and approach common data analysis tasks by utilizing available documentation and R tools. Whereas the primary focus is on microbiome research, the covered data science methods are generally applicable and we will discuss links with other application domains such as transcriptomics, metabolomics, and single cell sequencing. Target audience: MSc students, PhD, postdoctoral, and other researchers who wish to learn new skills in statistical programming and data analysis. Academic students and researchers from Finland and abroad are welcome and encouraged to apply. Teaching material: We will follow open online documentation created by the course teachers, primarily the Orchestrating Microbiome Analysis (OMA) book. The training material walks you through the standard steps of omics data analysis covering data access, exploration, analysis, visualization, and reproducible workflows. Preparatory material and video clips, and online support are available before the course. All teaching materials are shared openly. Figure source: Moreno-Indias et al. (2021) Frontiers in Microbiology 12:11. 1.2 Schedule Venue: University of Oulu. December 18-20, 2024 (Wed-Fri). The course is organized in a live format; no remote option available. Costs: Registration is free. Participants are expected to cover their own travel and accommodation. Accommodation: Housing tips can be found at https://visitoulu.fi/en/arrival-overnight/. Schedule: Contact teaching daily between 9am – 5pm, including lectures, demos, practicals, and breaks. For a detailed schedule, see Section 2. The course can be extended by an independent assignment (details to be agreed with the main teacher). 1.3 How to apply Send a brief motivation letter to Anna Kaisanlahti anna.kaisanlahti@oulu.fi. In your letter, please describe your skill level in R coding using scale 1-5 (1 = no previous experience, 5 = advanced level), and your previous experience related to bioinformatics. Applications from local students, and applications sent before 11 November 2024 will be given priority. The course has maximum capacity of 20 participants. The enrollment to the course will be confirmed within few days after the application deadline (Nov 11). Applications received after 11.11 will also be considered in case there are slots still available. 1.4 Teachers and organizers Teachers: Leo Lahti is the main teacher and Professor in Data Science at the University of Turku, and a certified Carpentries Instructor. PhD researcher Tuomas Borman is a co-teacher and main developer of the data science framework used in the course. Anna Kaisanlahti (Oulu) is a course assistant, and Docent Justus Reunanen is the course coordinator. The course is organized by Health and Biosciences Doctoral Programme (HBS-DP) University of Oulu Graduate School, Research Unit of Translational Medicine, University of Oulu. We thank the Finnish IT Center for Science (CSC) supports the course by providing cloud computing services. This is a Bioconductor course Drnevich et al. (2024) and we follow the best practices recommended by Software carpentries. 1.5 Code of Conduct The Bioconductor community values an open approach to science that promotes the sharing of ideas, code, software and expertise open collaboration and community contributions diversity and inclusivity a kind and welcoming environment More details on its enforcement are available here. 1.6 Acknowledgments Citation: We thank all developers and contributors who have contributed open resources that supported the development of the training material. Kindly cite the course material as Tuomas Borman and Leo Lahti (2024). Contact: Refer to https://microbiome.github.io. License and source code: All material is released under the open CC BY-NC-SA 3.0 License and available online during and after the course, following the recommendations on open teaching materials of the national open science coordination in Finland. References "],["program.html", "2 Program 2.1 Day 1 - Open data science 2.2 Day 2 - Tabular data analysis 2.3 Day 3 - Multi-assay data integration", " 2 Program The course takes place daily from 9am – 5pm (CEST), including coffee, lunch, and short breaks. Most of the time will be dedicated to practical exercises, complemented by short lectures and demos. We expect that participants will prepare for the course in advance. Instructions will be sent to the registered participants. Online support is available. The material follows open online book created by the course teachers, Orchestrating Microbiome Analysis, which supports R/Bioconductor framework for multi-omic data integration and analysis. Figure source: Moreno-Indias et al. (2021) Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions. Frontiers in Microbiology 12:11. 2.1 Day 1 - Open data science Reproducible workflows with R/Bioconductor and Quarto Morning 10-11 Coffee, Welcome & Practicalities 11-12 Learning environment (CSC RStudio notebook and reproducible reporting with Quarto) 12-13 Lunch break Afternoon 13-14 Lecture: open data science 14-16 Working with data containers and workflows 16-17 Q & A 2.2 Day 2 - Tabular data analysis Morning 9-10 Lecture: analysis & visualization of tabular data (single omics) 10-12 Data wrangling, exploration, and summaries 12-13 Lunch break Afternoon 13-14 Univariate data analysis and visualization 14-16 Multivariate data analysis and visualization 16-17 Q & A Evening Course dinner (optional; own cost) 2.3 Day 3 - Multi-assay data integration Morning 9-10 Lecture: analysis & visualization of multi-assay data (multi-omics) 10-12 Multi-assay data analysis and visualization 12-13 Lunch break Afternoon 13-15: Advanced methods (e.g. time series, machine learning, simulation) 15-16: Summary and wrap-up 16-17: Q & A "],["venue.html", "3 Venue 3.1 Tips for visiting Oulu 3.2 Arrival to Oulu 3.3 Public transport 3.4 Electric boards and bikes 3.5 Accommodation", " 3 Venue 3.1 Tips for visiting Oulu Tourist info/city website can be found here. 3.2 Arrival to Oulu Airplane: Airport is located in Oulunsalo, approx. 15km distance away from Oulu city center and the course venue. From the airport it is possible to take a buss (lines 8 and 9) or taxi to Oulu. Train: Train station is located close to the city center (address: Rautatienkatu 11). The train operator, schedules and tickets are available through VR website. 3.3 Public transport General information is available on the ouka website Routes and timetables When traveling by bus you can buy your ticket directly from the bus via contactless payment with debit/credit card, or in advance through either mobile ticket application or ticket machine: Contactless payment. You can use your debit or credit card (Visa, Visa Electron, Mastercard and Eurocard) or mobile (Google Pay and Apple Pay) to pay for your fare. You can use contactless card or device to pay for your own travels only. Mobile ticket (application named Waltti Mobiili): Install Waltti Mobiili application and add your debit/credit card into it, make sure you have enabled online payments. Available payment methods include Visa, Visa Electron or Mastercard. You do not need to register to buy tickets. When you make your first purchase, choose region ”Oulu”. Show the ticket to the driver when you board. At the Waltti ticket machines, you can buy single tickets as well as add more value and seasons to your Waltti travel card. You can find a Waltti ticket machine in example at the following locations: Valkea Shopping Centre, Kesäkatu (next to the ATM) OYS, N-entrance (formerly A3: 1) - photo Oulu Airport, Arrivals Hall (next to screens) 3.4 Electric boards and bikes Below are listed companies offering electric boards and bikes in Oulu area with their websites with instructions for use and rental: Voi Tier Lime 3.5 Accommodation Hotel information in Oulu area can be found here. Below suggestion for hotels in Oulu city centre (via booking.com): Best Western Hotel Apollo De Gamlas Hem Hotel & Restaurant Forenom Aparthotel Oulu Radisson Blu Hotel, Oulu Scandic Oulu City Original Sokos Hotel Arina Oulu "],["404.html", "Page not found", " Page not found The page you requested cannot be found (perhaps it was moved or renamed). You may want to try searching to find the page's new location, or use the table of contents to find the page you are looking for. "]] diff --git a/docs/venue.html b/docs/venue.html index 01290b3..2be88d1 100644 --- a/docs/venue.html +++ b/docs/venue.html @@ -4,25 +4,25 @@ - 3 Venue | Microbiome data science with R/Bioconductor + 3 Venue | Microbiome Data Science & Multi-Omics with R/Bioconducto - + - + - + @@ -132,7 +132,7 @@
diff --git a/index.Rmd b/index.Rmd index ca1ba40..ee95897 100644 --- a/index.Rmd +++ b/index.Rmd @@ -1,5 +1,5 @@ --- -title: "Microbiome data science with R/Bioconductor" +title: "Microbiome Data Science & Multi-Omics with R/Bioconducto" subtitle: "Oulu, December 2024" date: "`r Sys.Date()`" site: bookdown::bookdown_site