Workshops and courses

Tutorial on Single-Cell Data Analysis (CIBB 2026 satellite)

Statistical foundations and practical workflow in R

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Date: 1 September 2026 @ 14:00 - 17:30

Timezone: Rome

Language of instruction: English

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A free pre-conference tutorial organized by young-SIS (young group of the Italian Statistical Society) in collaboration with CIBB 2026, the 21st International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics.

The tutorial provides a hands-on introduction to the statistical foundations and practical workflow of single-cell data analysis in R, suitable also for participants approaching this type of data for the first time.

Topics covered:

  • statistical challenges of single-cell data (sparsity, high dimensionality, technical variability)
  • normalization and dimensionality reduction (GLM-PCA, t-SNE, UMAP)
  • clustering and cell-type identification (supervised approaches including SingleR, and unsupervised clustering algorithms)
  • differential expression analysis with appropriate type I error control via Count Splitting
  • a complete analytical workflow in R using the Bioconductor SingleCellExperiment framework

Speakers:

  • Andrea Sottosanti, Department of Statistical Sciences, University of Padova
  • Dario Righelli, Department of Biology, University of Padova

Format: bring-your-own-laptop; required R packages will be communicated in advance for participants to install.

The event is part of CIBB 2026, taking place at Sapienza University of Rome on September 2-4, 2026.

Conference website: https://cibb2026.teralab.ai

Contact: [email protected]

Keywords: single-cell, scRNA-seq, Biostatistics, R, UMAP

Venue: Sapienza University of Rome

City: Roma

Region: Lazio

Country: Italy

Postcode: 00185

Prerequisites:

  • Familiarity with R recommended
  • Basic statistical concepts recommended
  • No prior experience with single-cell data required

Learning objectives:

By the end of the course, participants will be able to:

  • understand the main statistical challenges of single-cell data, including sparsity, high dimensionality, and technical variability
  • apply standard normalization and dimensionality reduction techniques to real datasets
  • perform clustering and cell type identification using both supervised and unsupervised methods
  • run differential expression analysis while appropriately controlling the type I error
  • conduct a complete analytical workflow in R using the Bioconductor SingleCellExperiment framework

Organizer: young-SIS (young group of the Italian Statistical Society) and CIBB 2026

Host institutions: Sapienza University of Rome

Eligibility:

  • First come first served

Target audience: PhD Students, Post-Doc research scientists

Capacity: 50

Event types:

  • Workshops and courses

Tech requirements:

  • Participants must bring their own laptop
  • A list of required R packages will be circulated to registered participants prior to the event
  • Working R installation (version 4.0 or higher recommended) and RStudio

Credit / Recognition: A certificate of attendance can be issued on request.

Cost basis: Free to all

Instructors: Andrea Sottosanti, Dario Righelli

Scientific topics: Statistics and probability, RNA-Seq, Transcriptomics, Gene expression

External resources:
Main conference site
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