Note: 10x Genomics does not provide support for community-developed tools and makes no guarantees regarding their function or performance. Please contact tool developers with any questions. If you have feedback about Analysis Guides, please email analysis-guides@10xgenomics.com.
The journey from experimental design to publication-ready figures is one of the most challenging aspects of modern biology. While researchers often have deep expertise in their respective fields, the steep learning curve of bioinformatics can create significant barriers to discovery. To help biologists overcome these challenges, 10x Genomics is introducing a comprehensive, 8-week online data analysis course.
This course is specifically designed to prepare researchers with the skills needed to independently analyze 10x Genomics Chromium Single Cell and In Situ gene expression data. Participants will learn to master a blend of 10x-developed tools and widely-used community resources.
The course is structured into four skill-based stages that guide students through the entire analysis workflow:
- Stage 1 (Pre-work to Week 2): The Foundations: Establish a core toolkit using Linux and Python for bioinformatics.
- Stage 2 (Week 2 to Week 4): Single Cell Analysis: Learn the essentials of data pre-processing, quality control, and cell-type annotation, data integration, and downstream analysis using community tools.
- Stage 3 (Week 5 to Week 7): Spatial Analysis: Deep dive into Xenium raw data processing, decoding, quality control, and advanced cell segmentation.
- Stage 4 (Week 8): Synthesis and Wrap-Up: Approach new tools in the field, create a publication-quality figure, and write up the analysis.
Here is a breakdown of all the topics covered in this course by week (2 modules per week):
| Weeks 1–4 | Weeks 5–8 |
|---|---|
| 1a: Analysis-Aware Experimental Design | 5a: Single Cell Downstream Analyses |
| 1b: The Bioinformatician's Toolkit | 5b: Transitioning to Spatial Logic |
| 2a: Single Cell Raw Data Processing | 6a: Spatial Raw Data Processing |
| 2b: Introduction to Python | 6b: Spatial Quality Control |
| 3a: Preprocessing and Plotting in Python | 7a: Spatial Segmentation Deep-Dive |
| 3b: Single Cell Quality Control | 7b: Spatial Downstream Analysis |
| 4a: Single Cell Annotation | 8a: Spatially-Aware Analyses |
| 4b: Single Cell Multi-Sample Integration | 8b: From Exploration to Effective Communication |
Here are some of the tools you will learn how to use during this course:
- Cell Type Annotation Tools: Cell Ranger; CellTypist; Azimuth; SingleR
- Multi-Sample Integration & Batch Correction: Harmony; scCODA; pyDESeq2
- Enrichment & Pathway Analysis: GSEA; Enrichr
- Cell-Cell Interaction & Communication Analysis: CellChat; COMMOT
- Spatially-Aware Clustering & Analysis: BANKSY; Moran's I; Neighborhood Enrichment Analysis
- Spatial Cell Segmentation: Proseg
- And more
This pilot program follows a flexible but rigorous weekly cadence designed for busy professionals. Participants should expect a weekly commitment of approximately 8 hours* (actual time spent varies depending on past data analysis experience).
- Independent Learning: Access pre-recorded lectures and hands-on assignments that can be completed on your own schedule.
- Real-World Application: Work with example datasets and learn transferable analysis logic applicable to a variety of biological tissues and infectious disease or cancer research.
- Expert Interaction: Join live weekly Zoom sessions and connect with 10x experts on Discord for Q&A and community discussions throughout.
| Feature | Details |
|---|---|
| Duration | 8 Weeks (Commitment: ~8 hours/week*) |
| Format | Online (Pre-recorded videos + Hands-on assignments + Live Zoom + Discord chat) |
| Price | $2,499 USD (Currently only offered in the US) |
| Prerequisites | No prior programming experience required; basics are covered during the course |
| Certification | Certification upon successful completion of all assignments |
*Below is an overview of a typical weekly schedule. We estimate a total time commitment of roughly 8 hours per week, spanning self-paced instruction and assignments from Monday through Thursday, a live discussion on Friday, and active support via Discord all week. Actual time spent may vary depending on your prior data analysis experience.
Whether you are expanding your research to include new 10x assays or facing institutional barriers to bioinformatics support, this course provides the fluency needed for future roles in both academia and industry. By the end of the program, students will have a strong enough foundation in data analysis of 10x technologies to confidently approach emerging analytical tools beyond those explicitly covered in the syllabus.
To join the upcoming cohort running October 5 – December 11, 2026, please fill out this application form.
This upcoming cohort is offered in the US. If you are interested in the course and live outside of the US, or are not able to join this specific cohort, please fill out this interest form. We will contact you regarding details of future cohorts and how to apply.
For more information, you can contact us at support@10xgenomics.com.