BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260618T133559Z UID:6e08cba0-21c6-4546-8002-fdd750b6b046 DTSTART:20261111T090000Z DTEND:20261113T170000Z DESCRIPTION:# Overview\n\nSingle-cell RNA sequencing (scRNAseq) allows rese archers to study gene expression at the single cell level. For example\, s cRNAseq can help to identify expression patterns that differ between condi tions within a cell type. To generate and analyze scRNAseq data\, several methods are available\, all with their strengths and weaknesses depending on the researchers’ needs.\n\nThis 3-day course will cover the main tech nologies as well as the main aspects to consider while designing a scRNAse q experiment. In addition\, it will cover the theoretical background of an alysis methods with hands-on practical data analysis sessions applied to d roplet-based methods.\n\n# Audience\nThis course is designed for PhD stude nts\, postdoctoral and other researchers in the life sciences from both ac ademia and industry who are familiar with next-generation sequencing (NGS) and want to acquire the necessary skills to analyse scRNA-seq gene expres sion data.\n\n# Learning outcomes\n\nAt the end of the course\, the partic ipants are expected to:\n\n* Distinguish advantages and pitfalls of scRNA- seq\, including its applications in experimental design.\n* Design their o wn scRNA-seq experiment\, by using common technologies like 10X Genomics.\ n* Apply quality control (QC) measures and utilize analysis tools to prepr ocess scRNA-seq data.\n* Apply normalization\, scaling\, dimensionality re duction\, and integration and clustering on single-cell transcriptomics da ta techniques using R.\n* Differentiate between cell annotation techniques to identify and characterize cell populations.\n* Use differential gene e xpression analysis methods on single-cell transcriptomics data to gain bio logical insights.\n* Select enrichment analysis methods appropriate to the biological question and data.\n* Develop a single-cell transcriptomics da ta analysis workflow from raw count matrix to differential gene expression with peer support and light guidance.\n \n\n# Prerequisites\n##### Knowl edge / competencies\n\n**Participants must have basic knowledge in UNIX\, R and Next-Generation Sequencing (NGS) techniques.**\n\nThis course is par t of the [Omics Data Analysis learning path](https://www.sib.swiss/trainin g/learning-paths?path=omics-data-analysis). To get the most out of this co urse\, you should meet the learning outcomes of [Introduction to bulk RNA- Seq: From Quality Control to Pathway Analysis](https://www.sib.swiss/train ing/course/IRNAS)\, [NGS - Quality control\, Alignment\, Visualisation](ht tps://www.sib.swiss/training/course/NGSQC)\, [First Steps with R in Life S ciences](https://www.sib.swiss/training/course/FSWRR) and [UNIX Fundamenta ls](https://edu.sib.swiss/pluginfile.php/2878/mod_resource/content/4/couse lab-html/content.html). Upon completion of this course\, you may wish to a ttend the [\nIntroduction to Sequencing-based Spatial Transcriptomics Data Analysis\n](https://www.sib.swiss/training/course/SBSRT).\n\nIn case of d oubt\, evaluate your **R skills** [here](https://docs.google.com/forms/d/e /1FAIpQLSdIyeuabd_ZOWXgI1MWHapmaOMu20L9ESkLDZiWnpmkpujyOg/viewform?usp=sf_ link) and your **UNIX skills** [here](https://docs.google.com/forms/d/e/1F AIpQLSd2BEWeOKLbIRGBT_aDEGPce1FOaVYBbhBiaqcaHoBKNB27MQ/viewform?usp=sf_lin k).\n\n\n##### Technical\nAttendees should have a Wi-Fi enabled computer. **An online R and RStudio environment will be provided.** However\, in cas e you wish to perform the practical exercises on your own computer\, pleas e install an [R version >\; 4.0](https://www.r-project.org/) and the [la test RStudio version](https://www.rstudio.com/products/rstudio/download/#d ownload) (the free version is perfectly fine) before the course.\n\n\n\n# Schedule\nThe course schedule will be communicated in due time\; that for past occurences is found on [GitHub](https://sib-swiss.github.io/single-ce ll-training/course_schedule.html).\n\n\n\n# Application\n\n\n\n\nThe regis tration fees for academics are **300 CHF** and **1500 CHF** for for-profit companies. While participants are registered on a first come\, first serv ed basis\, exceptions may be made to ensure diversity and equity\, which m ay increase the time before your registration is confirmed.\n\nApplication s will close once the places will be filled. Deadline for registration and free-of-charge cancellation is set to **09/06/2026**. Cancellation after this date will not be reimbursed. Please note that participation in SIB co urses is subject to our [general conditions](https://www.sib.swiss/trainin g/terms-and-conditions).\n\nYou will be informed by email of your registra tion confirmation. Upon reception of the confirmation email\, participants will be asked to confirm attendance by paying the fees within 5 days.\n\n # Venue and Time\n\nThis course will take place in Bellinzona.\n\nIt will start at 9:00 and end around 17:00 every day.\n\nPrecise information will be provided to the participants in due time.\n\n\n# Additional informatio n\nCoordination: Geert van Geest\, SIB Training group.\n\nWe will recommen d 0.75 ECTS credits for this course (given a passed exam at the end of the course).\n\nYou are welcome to register to the SIB courses mailing list t o be informed of all future courses and workshops\, as well as all importa nt deadlines using the form [here](https://lists.sib.swiss/mailman/listinf o/courses).\n\nPlease note that participation in SIB courses is subject to our [general conditions](https://www.sib.swiss/training/terms-and-conditi ons).\n\nSIB abides by the [ELIXIR Code of Conduct](https://elixir-europe. org/events/code-of-conduct). Participants of SIB courses are also required to abide by the same code.\n\nFor more information\, please contact [trai ning@sib.swiss](mailto://training@sib.swiss). SUMMARY:Single-Cell Transcriptomics with R URL;VALUE=URI:https://www.sib.swiss/training/course/20261111_ISCTR END:VEVENT END:VCALENDAR