BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260715T175315Z UID:8abbfca6-1cb9-4c06-91f8-85e48dd7f0a8 DTSTART:20261111T090000Z DTEND:20261113T170000Z DESCRIPTION:## Overview\n\nSingle-cell RNA sequencing (scRNAseq) allows res earchers to study gene expression at the single cell level. For example\, scRNAseq can help to identify expression patterns that differ between cond itions 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 tec hnologies as well as the main aspects to consider while designing a scRNAs eq experiment. In addition\, it will cover the theoretical background of a nalysis methods with hands-on practical data analysis sessions applied to droplet-based methods.\n\n## Audience\n\nThis course is designed for PhD s tudents\, postdoctoral and other researchers in the life sciences from bot h academia and industry who are familiar with next-generation sequencing ( NGS) and want to acquire the necessary skills to analyse scRNA-seq gene ex pression data.\n\n## Learning outcomes\n\nAt the end of the course\, the p articipants should be able to:\n\n* **Distinguish** advantages and pitfall s of scRNA-seq\, including its applications in experimental design.\n* **D esign** their own scRNA-seq experiment\, by using common technologies like 10X Genomics.\n* **Apply** quality control (QC) measures and utilize anal ysis tools to preprocess scRNA-seq data.\n* **Apply** normalization\, scal ing\, dimensionality reduction\, and integration and clustering on single- cell transcriptomics data techniques using R.\n* **Differentiate** between cell annotation techniques to identify and characterize cell populations. \n* **Use** differential gene expression analysis methods on single-cell t ranscriptomics data to gain biological insights.\n* **Select** enrichment analysis methods appropriate to the biological question and data.\n* **Dev elop** a single-cell transcriptomics data analysis workflow from raw count matrix to differential gene expression with peer support and light guidan ce.\n\n## Prerequisites\n\n### Knowledge / competencies\n\n**Participants must have basic knowledge in UNIX\, R and Next-Generation Sequencing (NGS) techniques.**\n\nThis course is part of the [Omics Data Analysis learning path](https://www.sib.swiss/training/learning-paths?path=omics-data-analy sis). To get the most out of this course\, you should meet the learning ou tcomes of [Introduction to bulk RNA-Seq: From Quality Control to Pathway A nalysis](https://www.sib.swiss/training/course/IRNAS)\, [NGS - Quality con trol\, Alignment\, Visualisation](https://www.sib.swiss/training/course/NG SQC)\, [First Steps with R in Life Sciences](https://www.sib.swiss/trainin g/course/FSWRR) and [UNIX Fundamentals](https://www.sib.swiss/training/cou rse/2012_UNIXF). Upon completion of this course\, you may wish to attend t he [\nIntroduction to Sequencing-based Spatial Transcriptomics Data Analys is\n](https://www.sib.swiss/training/course/SBSRT).\n\nIn case of doubt\, evaluate your **R skills** [here](https://docs.google.com/forms/d/e/1FAIpQ LSdIyeuabd_ZOWXgI1MWHapmaOMu20L9ESkLDZiWnpmkpujyOg/viewform?usp=sf_link) a nd your **UNIX skills** [here](https://docs.google.com/forms/d/e/1FAIpQLSd 2BEWeOKLbIRGBT_aDEGPce1FOaVYBbhBiaqcaHoBKNB27MQ/viewform?usp=sf_link).\n\n \n### Technical\n\nAttendees should have a Wi-Fi enabled computer. **An on line R and RStudio environment will be provided.** However\, in case you w ish to perform the practical exercises on your own computer\, please insta ll an [R version >\; 4.0](https://www.r-project.org/) and the [latest RS tudio version](https://www.rstudio.com/products/rstudio/download/#download ) (the free version is perfectly fine) before the course.\n\n## Schedule – CE(S)T time zone\n\nThe course schedule will be communicated in due ti me\; that for past occurences is found on [GitHub](https://sib-swiss.githu b.io/single-cell-training/course_schedule.html).\n\n## Application\n\nThe registration fees for academics are **300 CHF** and **1500 CHF** for for-p rofit companies.\n\nWhile participants are registered on a first come\, fi rst served basis\, exceptions may be made to ensure diversity and equity\, which may increase the time before your registration is confirmed.\n\nApp lications will close on **04.11.2026** or as soon as the places will be fi lled up. Cancellation after **04.11.2026** will not be reimbursed. Please note that participation in SIB courses is subject to our [general conditio ns](https://www.sib.swiss/legal-documents).\n\nYou will be informed by ema il of your registration confirmation. Upon reception of the confirmation e mail\, participants will be asked to confirm attendance by paying the fees within **5 working 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 d ay.\n\nPrecise information will be provided to the participants in due tim e.\n\n## Additional information\n\nCoordination: Geert van Geest\, SIB Tra ining group.\n\nA **Certificate of Attendance** will be sent provided you were present at the course\, whereas a **Certificate of Achievement** reco mmending 0.75 ECTS will be sent provided you passed the exam.\n\nYou are w elcome to register to the SIB courses mailing list to be informed of all f uture courses and workshops\, as well as all important deadlines using the form [here](https://lists.sib.swiss/mailman/listinfo/courses).\n\nSIB abi des 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 [training@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