Virtual Cell Challenge

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Arc has developed dedicated datasets to map single cell genetic perturbations. Competitors are welcome to use these data, along with other relevant public or proprietary data, to build a predictive model. This page describes the Challenge datasets in detail, including how they were created, how they are structured, and the shape of the datasets that will be available for training, validation and the final test. For this challenge, we used single-cell functional genomics to generate approximately 300,000 single-cell RNA-seq profiles by silencing 300 carefully selected genes using CRISPR interference (CRISPRi). To obtain single-cell gene expression profiles we used 10x Genomics GEM-X Flex and Illumina sequencing. The data are split into three groups for the Virtual Cell Challenge, to allow for training, validation of initial results, and developing a final entry for the competition. Participants will receive: Competitors will be able to download the training and validation datasets once

Advances in single-cell RNA-seq technologies now enable large-scale measurements of cellular responses to genetic and chemical perturbations, fueling this exciting era of predictive cellular modeling. The Virtual Cell Challenge is a recurring, open, community-driven challenge aimed at evaluating and improving computational models that predict cellular responses to genetic or chemical perturbations. In 2026, the Challenge raises the bar to multi-context generalization and zero-shot prediction. We are not providing any net-new training dataset this year. Participants are free to use the H1…

Virtual Cell Challenge

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