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CIBB 2026: FREE PRE-CONFERENCE TUTORIAL ON
SINGLE-CELL DATA ANALYSIS
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Dear all,
We would like to bring to your attention a free pre-conference event that may be of particular interest to the statistical machine learning community
Tutorial on Single-Cell Data Analysis, taking place on September 1, 2026, at Sapienza University of Rome.
The tutorial, organized by young-SIS (young group of the Italian Statistical Society) in collaboration with CIBB 2026, provides a hands-on introduction to the statistical foundations and practical workflow of single-cell data analysis in R. It addresses the methodological challenges specific to this type of data (sparsity, high dimensionality, technical variability, appropriate type I error control in differential expression analysis) that require careful adaptations of classical statistical methods.
The event is free of charge and open to anyone, including those not attending the main conference. Registration is required due to limited seats.
The tutorial is part of CIBB 2026, the 21st International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, taking place at Sapienza University of Rome from September 2 to 4, 2026, with Biostatistics as one of its three main tracks. Confirmed invited speakers include Per Kragh Andersen (University of Copenhagen). Registration to the main conference is now open, with special rates for students and PhD candidates.
Best regards,
CIBB 2026 General Chairs
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KEY INFORMATION
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Tutorial date: September 1, 2026
Conference dates: September 2-4, 2026
Location: Sapienza University of Rome, Rome, Italy
Website:
https://cibb2026.teralab.aiContact:
cibb...@uniroma1.itTutorial details and registration:
https://cibb2026.teralab.ai/satellite-events/statistical-principles-and-practice-of-single-cell-data-analysis/Conference registration:
https://cibb2026.teralab.ai/registration==================================================================
TUTORIAL CONTENT
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Speakers: Andrea Sottosanti and Dario Righelli, University of Padova.
Topics: statistical challenges of single-cell data; normalization and dimensionality reduction (GLM-PCA, t-SNE, UMAP); clustering and cell-type identification (SingleR + unsupervised methods); differential expression with Count Splitting; complete workflow in R with Bioconductor SingleCellExperiment.
Format: bring-your-own-laptop. Familiarity with R and basic statistics recommended; no prior single-cell experience required.
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For full details on the conference, Special Sessions, the other pre-conference satellite events, and the Organizing Committee, please visit:
https://cibb2026.teralab.ai