Virtual Cell Challenge
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
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