--- name: single-cell type: use topic_type: technology title: Single Cell learning_path_ctas: For Beginners: intro_single_cell For Intermediate Users: beyond_single_cell For Coding Enthusiasts: reloaded_single_cell # Using the community CTAs feature opts you into managing your own requirements list here a bit manually community_ctas: - description: | **Pre-requisites:** If you've never used Galaxy before, first try the: link: https://training.galaxyproject.org/training-material/topics/introduction/ link_text: Introduction to Galaxy icon: tutorial width: 3 primary_color: true - description: | The Single Cell & Galaxy learners are on Slack link: https://gxy.io/gtn-slack link_text: GTN Slack Workspace icon: comment width: 3 primary_color: false - description: | Come chat Single Cell with us on Matrix link: https://matrix.to/#/#Galaxy-Training-Network_galaxy-single-cell:gitter.im link_text: Community Matrix Chat icon: comment width: 3 primary_color: false - description: | What else do you want to see? Let us know! link: https://docs.google.com/spreadsheets/d/15hqgqA-RMDhXR-ylKhRF-Dab9Ij2arYSKiEVoPl2df4/edit?usp=sharing link_text: Tool/Tutorial Requests icon: tool width: 3 primary_color: false gitter: Galaxy-Training-Network_galaxy-single-cell:gitter.im summary: | Training material and practicals for all kinds of single cell analysis (particularly scRNA-seq!). # What else do you want to see? You can submit tool or tutorial requests, or upvote other requests, on our [Single-Cell & Spatial Omics Tool Request Spreadsheet](). # {: .alert.alert-success} #docker_image: "quay.io/galaxy/transcriptomics-training" requirements: - type: "internal" topic_name: introduction editorial_board: - pavanvidem - MarisaJL - Nilchia - dianichj - heylf toc: true # create table of contents for the subtopics subtopics: - id: scintroduction title: "Introduction" description: "Start here if you are new to single cell analysis and want to learn the concepts." - id: firstsc title: "Your first analysis" description: "Start here if you are new to single cell analysis in Galaxy and want to try analysing data." - id: single-cell-CS title: "Case study" 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." - id: single-cell-CS-code title: "Case study: Reloaded" description: "These tutorials let you follow the same case study analysis of real, messy data but in a programming environment, hosted on Galaxy. So if you want more flexibility, but the same guided steps as the Case Study, you can skip the Case Study and start here instead. Alternatively, try these after completing the Case Study for an easier jump to a coding environment." - id: end-to-end title: "End-to-end scRNA-seq Analyses" description: "These tutorials use different methods to analyse scRNA-seq samples" - id: deconvo title: "Deconvolution" description: "These tutorials infer cell compositions from bulk RNA-seq data using a scRNA-seq reference" - id: scmultiomics title: "Multiomic Analyses" description: "This section lets you build on mere scRNA analyses into a multiomic future!" crosstopic_tutorials: - topic: proteomics tutorial: bioconductor-scp priority: 4 - id: tricks title: "Tips, tricks & other hints" description: "These tutorials cover helpful skills for scRNA-seq analysis" - id: datamanipulation title: "Changing data formats & preparing objects" description: "These tutorials cover a range of needs for importing data from different sources, to changing data into different formats to move from one analysis to the other." - id: exploratory title: "Exploratory Analyses" description: "You have clusters and you have genes. What can you do now? Come here to explore your results more!" - id: spatial title: "Spatial Transcriptomics" description: "Tutorials for analysing spatially resolved gene expression data, integrating molecular measurements with tissue coordinates, morphology, spatial neighbourhoods, and cell-state annotations." references: - authors: "Loach, Marisa; Naghsh Nilchi, Amirhossein; Chiang, Diana; Howells, Morgan; Heyl, Florian; Rasche, Helena; Jakiela, Julia; Tekman, Mehmet; Gamal, Menna; Moreno, Pablo; Hiltemann, Saskia; Schlegel, Timon; Grüning, Björn; Backofen, Rolf; Videm, Pavankumar; Bacon, Wendi" title: "Galaxy single-cell & spatial omics community update: Navigating new frontiers in 2025" link: "https://doi.org/10.1016/j.xgen.2025.101005" summary: "" - authors: "Tekman, Mehmet and Batut, Bérénice; Ostrovsky, Alexander; Antoniewski, Christophe; Clements, Dave; Ramirez, Fidel; Etherington, Graham J; Hotz, Hans-Rudolf; Scholtalbers, Jelle; Manning, Jonathan R; Bellenger, Lea; Doyle, Maria A; Heydarian, Mohammad; Huang, Ni; Soranzo, Nicola; Moreno, Pablo; Mautner, Stefan; Papatheodorou, Irene; Nekrutenko, Anton; Taylor, James; Blankenberg, Daniel; Backofen, Rolf; Grüning, Björn;" title: "A single-cell RNA-sequencing training and analysis suite using the Galaxy framework" link: "https://doi.org/10.1093/gigascience/giaa102" summary: "" - authors: "Pablo Moreno, Ni Huang, Jonathan R Manning, Suhaib Mohammed, Andrey Solovyev, Krzysztof Polanski, Wendi Bacon, Ruben Chazarra, Carlos Talavera-López, Maria A Doyle, Guilhem Marnier, Björn Grüning, Helena Rasche, Nancy George, Silvie Korena Fexova, Mohamed Alibi, Zhichao Miao, Yasset Perez-Riverol, Maximilian Haeussler, Alvis Brazma, Sarah Teichmann, Kerstin B Meyer, Irene Papatheodorou;" title: "User-friendly, scalable tools and workflows for single-cell RNA-seq analysis" link: "https://www.nature.com/articles/s41592-021-01102-w" summary: ""