From 329cf42a2abdbd8dddb1258e75869877e99d445d Mon Sep 17 00:00:00 2001 From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com> Date: Thu, 7 Mar 2024 12:02:29 +0000 Subject: [PATCH 1/6] starter! --- learning-pathways/beyond_single_cell.md | 54 +++++++++++++++++++++++++ 1 file changed, 54 insertions(+) create mode 100644 learning-pathways/beyond_single_cell.md diff --git a/learning-pathways/beyond_single_cell.md b/learning-pathways/beyond_single_cell.md new file mode 100644 index 00000000000000..440544fe665a8e --- /dev/null +++ b/learning-pathways/beyond_single_cell.md @@ -0,0 +1,54 @@ +--- +layout: learning-pathway +tags: [beginner] +cover-image: assets/images/wab-annotatedcells-2.png +cover-image-alt: "Image of cells in different coloured clusters" +type: use + +editorial_board: +- nomadscientist +- pavanvidem + +title: Introduction to Galaxy and Single Cell RNA Sequence analysis +description: | + These tutorials take you from raw scRNA sequencing reads to inferred trajectories to replicate a published analysis. The data is messy. The decisions are tough. The interpretation is meaningful. Come here to advance your single cell skills! Note that you get two options for inferring trajectories. + + This learning path aims to teach you the basics of Galaxy and analysis of Single Cell RNA-seq data. + You will learn how to use Galaxy for analysis, and an important Galaxy feature for iterative single cell analysis. You'll tbe guided through the general theory of single analysis and then perform a basic analysis of 10X chromium data. For support throughout these tutorials, join our Galaxy [single cell chat group on Matrix](https://matrix.to/#/#Galaxy-Training-Network_galaxy-single-cell:gitter.im) to ask questions! + +priority: 9 + +pathway: + - section: "Module 1: Introduction to Galaxy" + description: | + Get a first look at the Galaxy platform for data analysis. We start with a + short introduction (video slides & practical) to familiarize you with the Galaxy + interface, and then proceed with a short tutorial of how to tag - and organise! - your history. + tutorials: + - name: galaxy-intro-short + topic: introduction + - name: name-tags + topic: galaxy-interface + + - section: "Module 2: Theory of Single-Cell RNA-seq" + description: | + When analysing sequencing data, you should always start with a quality control step to clean your data and make sure your data is good enough to answer your research question. After this step, you will often proceed with a mapping (alignment) or genome assembly step, depending on whether you have a reference genome to work with. + tutorials: + - name: scrna-intro + topic: single-cell + + - section: "Module 3: Time to analyse data!" + description: | + It's time to apply your skills! You'll now analyse some clean data from the 10X Chromium platform. + tutorials: + - name: scrna-preprocessing-tenx + topic: single-cell + - name: scrna-scanpy-pbmc3k + topic: single-cell + + - section: "The End!" + description: | + And now you're done! There are still loads of resources to take you from basic analysis to more difficult decision-making, deconvolution, multiomics, or ingesting from different data sources. See the [Galaxy Single Cell Training page](/training-material/topics/single-cell/index.html) for more! +--- + +New to Galaxy and/or the field of scRNA-seq? Follow this learning path to get familiar with the basics! From 06b1d729a3530205191d8e9ce7e7b403f72d430c Mon Sep 17 00:00:00 2001 From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com> Date: Thu, 7 Mar 2024 12:36:21 +0000 Subject: [PATCH 2/6] adding in this intermediate path --- learning-pathways/beyond_single_cell.md | 23 ++++++++++------------- 1 file changed, 10 insertions(+), 13 deletions(-) diff --git a/learning-pathways/beyond_single_cell.md b/learning-pathways/beyond_single_cell.md index 440544fe665a8e..cc634c7f57e280 100644 --- a/learning-pathways/beyond_single_cell.md +++ b/learning-pathways/beyond_single_cell.md @@ -1,6 +1,6 @@ --- layout: learning-pathway -tags: [beginner] +tags: [intermediate] cover-image: assets/images/wab-annotatedcells-2.png cover-image-alt: "Image of cells in different coloured clusters" type: use @@ -9,26 +9,23 @@ editorial_board: - nomadscientist - pavanvidem -title: Introduction to Galaxy and Single Cell RNA Sequence analysis +title: Applying single-cell RNA-seq analysis description: | - These tutorials take you from raw scRNA sequencing reads to inferred trajectories to replicate a published analysis. The data is messy. The decisions are tough. The interpretation is meaningful. Come here to advance your single cell skills! Note that you get two options for inferring trajectories. + Gone is the pre-annotated, high quality tutorial data - now you have real, messy data to deal with. You have decisions to make and parameters to decide. This learning pathway challenges you to replicate a published analysis as if this were your own dataset. You will be introduced to a few more tools available for scRNA-seq in Galaxy. Finally, if our tool offerings are not enough for you, you will be directed towards how to use coding notebooks within Galaxy, setting you up to analyse scRNA-seq in R or python notebooks. - This learning path aims to teach you the basics of Galaxy and analysis of Single Cell RNA-seq data. - You will learn how to use Galaxy for analysis, and an important Galaxy feature for iterative single cell analysis. You'll tbe guided through the general theory of single analysis and then perform a basic analysis of 10X chromium data. For support throughout these tutorials, join our Galaxy [single cell chat group on Matrix](https://matrix.to/#/#Galaxy-Training-Network_galaxy-single-cell:gitter.im) to ask questions! + The data is messy. The decisions are tough. The interpretation is meaningful. Come here to advance your single cell skills! Note that you get two options for inferring trajectories. -priority: 9 + For support throughout these tutorials, join our Galaxy [single cell chat group on Matrix](https://matrix.to/#/#Galaxy-Training-Network_galaxy-single-cell:gitter.im) to ask questions! pathway: - - section: "Module 1: Introduction to Galaxy" + - section: "Module 1: Case study" description: | - Get a first look at the Galaxy platform for data analysis. We start with a - short introduction (video slides & practical) to familiarize you with the Galaxy - interface, and then proceed with a short tutorial of how to tag - and organise! - your history. + These tutorials take you from raw scRNA sequencing reads to inferred trajectories to replicate a published analysis. Note that you get two options for inferring trajectories. tutorials: - - name: galaxy-intro-short - topic: introduction + - name: scrna-case_alevin + topic: single-cell - name: name-tags - topic: galaxy-interface + topic: single-cell - section: "Module 2: Theory of Single-Cell RNA-seq" description: | From ef41c75bea04b7a5cb0eda8775fb6e5cafee4912 Mon Sep 17 00:00:00 2001 From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com> Date: Thu, 7 Mar 2024 12:49:51 +0000 Subject: [PATCH 3/6] finish LP --- learning-pathways/beyond_single_cell.md | 31 +++++++++++++++---------- 1 file changed, 19 insertions(+), 12 deletions(-) diff --git a/learning-pathways/beyond_single_cell.md b/learning-pathways/beyond_single_cell.md index cc634c7f57e280..5aaca40e6d90dd 100644 --- a/learning-pathways/beyond_single_cell.md +++ b/learning-pathways/beyond_single_cell.md @@ -8,6 +8,7 @@ type: use editorial_board: - nomadscientist - pavanvidem +- pcm32 title: Applying single-cell RNA-seq analysis description: | @@ -20,32 +21,38 @@ description: | pathway: - section: "Module 1: Case study" description: | - These tutorials take you from raw scRNA sequencing reads to inferred trajectories to replicate a published analysis. Note that you get two options for inferring trajectories. + These tutorials take you from raw scRNA sequencing reads to cell cluster plots to replicate a published analysis. tutorials: - name: scrna-case_alevin topic: single-cell - - name: name-tags + - name: scrna-case_alevin-combine-datasets + topic: single-cell + - name: scrna-case_basic-pipeline topic: single-cell - - section: "Module 2: Theory of Single-Cell RNA-seq" + - section: "Module 2: Inferring trajectories" description: | - When analysing sequencing data, you should always start with a quality control step to clean your data and make sure your data is good enough to answer your research question. After this step, you will often proceed with a mapping (alignment) or genome assembly step, depending on whether you have a reference genome to work with. + This isn't strictly necessary, but if you want to infer trajectories - pseudotime relationships between cells - you can try out these tutorials with the same dataset. Note that you get two options for inferring trajectories, you can choose either. tutorials: - - name: scrna-intro + - name: scrna-case_trajectories + topic: single-cell + - name: scrna-case_monocle3-trajectories topic: single-cell - - section: "Module 3: Time to analyse data!" + - section: "Module 3: Moving into coding environments" description: | - It's time to apply your skills! You'll now analyse some clean data from the 10X Chromium platform. + Did you know Galaxy can host coding environments? They don't have the same level of computational power as are allocated our tools, but you can still learn how to use these environments to analyse your data. Sometimes, there will be a tool you want to use that's not available in Galaxy, and ([after requesting it!](https://docs.google.com/spreadsheets/d/15hqgqA-RMDhXR-ylKhRF-Dab9Ij2arYSKiEVoPl2df4/edit?usp=sharing)) you can export your data into a coding environment and run the tool there. Let's start with the basics of running these environments in Galaxy. tutorials: - - name: scrna-preprocessing-tenx - topic: single-cell - - name: scrna-scanpy-pbmc3k - topic: single-cell + - name: jupyterlab + topic: galaxy-interface + - name: galaxy-intro-jupyter + topic: galaxy-interface + - name: rstudio + topic: galaxy-interface - section: "The End!" description: | - And now you're done! There are still loads of resources to take you from basic analysis to more difficult decision-making, deconvolution, multiomics, or ingesting from different data sources. See the [Galaxy Single Cell Training page](/training-material/topics/single-cell/index.html) for more! + And now you're done! If you are interested in trying out the case study analyses in a coding environment, try out our []"Case study: Reloaded" series](/training-material/topics/single-cell#single-cell-CS) next! Otherwise, you will find more features, tips and tricks in our general [Galaxy Single-cell Training page](/training-material/topics/single-cell/index.html). --- New to Galaxy and/or the field of scRNA-seq? Follow this learning path to get familiar with the basics! From 7736a12ee91c019f3cf75f5a98eb759197f774c1 Mon Sep 17 00:00:00 2001 From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com> Date: Thu, 7 Mar 2024 15:24:31 +0000 Subject: [PATCH 4/6] Update learning-pathways/beyond_single_cell.md Co-authored-by: Pavankumar Videm --- learning-pathways/beyond_single_cell.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/learning-pathways/beyond_single_cell.md b/learning-pathways/beyond_single_cell.md index 5aaca40e6d90dd..d62d5bf1882e62 100644 --- a/learning-pathways/beyond_single_cell.md +++ b/learning-pathways/beyond_single_cell.md @@ -41,7 +41,7 @@ pathway: - section: "Module 3: Moving into coding environments" description: | - Did you know Galaxy can host coding environments? They don't have the same level of computational power as are allocated our tools, but you can still learn how to use these environments to analyse your data. Sometimes, there will be a tool you want to use that's not available in Galaxy, and ([after requesting it!](https://docs.google.com/spreadsheets/d/15hqgqA-RMDhXR-ylKhRF-Dab9Ij2arYSKiEVoPl2df4/edit?usp=sharing)) you can export your data into a coding environment and run the tool there. Let's start with the basics of running these environments in Galaxy. + Did you know Galaxy can host coding environments? They don't have the same level of computational power as the easy-to-use Galaxy tools, but you can unlock the full freedom in your data analysis. You can install your favourite single-cell tool suite that is not available on Galaxy, export your data into these coding environments and run your analysis there. If you want your favourite tool suite as a Galaxy tool, you can always request [here](https://docs.google.com/spreadsheets/d/15hqgqA-RMDhXR-ylKhRF-Dab9Ij2arYSKiEVoPl2df4/edit?usp=sharing). Let's start with the basics of running these environments in Galaxy. tutorials: - name: jupyterlab topic: galaxy-interface From 5b4d69af6d9086b210de3aaa4e83d6c9b318f19b Mon Sep 17 00:00:00 2001 From: Pavankumar Videm Date: Thu, 7 Mar 2024 16:31:34 +0100 Subject: [PATCH 5/6] Update learning-pathways/beyond_single_cell.md --- learning-pathways/beyond_single_cell.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/learning-pathways/beyond_single_cell.md b/learning-pathways/beyond_single_cell.md index d62d5bf1882e62..406f03aba1c121 100644 --- a/learning-pathways/beyond_single_cell.md +++ b/learning-pathways/beyond_single_cell.md @@ -52,7 +52,7 @@ pathway: - section: "The End!" description: | - And now you're done! If you are interested in trying out the case study analyses in a coding environment, try out our []"Case study: Reloaded" series](/training-material/topics/single-cell#single-cell-CS) next! Otherwise, you will find more features, tips and tricks in our general [Galaxy Single-cell Training page](/training-material/topics/single-cell/index.html). + And now you're done! If you are interested in trying out the case study analyses in a coding environment, try out our ["Case study: Reloaded" series](/training-material/topics/single-cell#single-cell-CS) next! Otherwise, you will find more features, tips and tricks in our general [Galaxy Single-cell Training page](/training-material/topics/single-cell/index.html). --- New to Galaxy and/or the field of scRNA-seq? Follow this learning path to get familiar with the basics! From 1d7699b4f1d5e4d5672c482ba88855ac4c1a2b43 Mon Sep 17 00:00:00 2001 From: Wendi Bacon <44605769+nomadscientist@users.noreply.github.com> Date: Thu, 7 Mar 2024 16:12:02 +0000 Subject: [PATCH 6/6] Update learning-pathways/beyond_single_cell.md --- learning-pathways/beyond_single_cell.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/learning-pathways/beyond_single_cell.md b/learning-pathways/beyond_single_cell.md index 406f03aba1c121..d73808a932d749 100644 --- a/learning-pathways/beyond_single_cell.md +++ b/learning-pathways/beyond_single_cell.md @@ -52,7 +52,7 @@ pathway: - section: "The End!" description: | - And now you're done! If you are interested in trying out the case study analyses in a coding environment, try out our ["Case study: Reloaded" series](/training-material/topics/single-cell#single-cell-CS) next! Otherwise, you will find more features, tips and tricks in our general [Galaxy Single-cell Training page](/training-material/topics/single-cell/index.html). + And now you're done! If you are interested in trying out the case study analyses in a coding environment, try out our ["Case study: Reloaded" series](/training-material/topics/single-cell#st-single-cell-cs-code) next! Otherwise, you will find more features, tips and tricks in our general [Galaxy Single-cell Training page](/training-material/topics/single-cell/index.html). --- New to Galaxy and/or the field of scRNA-seq? Follow this learning path to get familiar with the basics!