Data integration (or batch effect correction) is one of the most complex steps in single-cell data analysis pipelines for data coming from different batches. Many factors may affect the final results, including the methods, the technologies, the nature of the data, etc.
In this webinar, we are excited to invite Hassaan Maan (PhD Candidate at The University of Toronto and Vector Institute) to discuss his recent study discovering a factor that can significantly affect the single-cell data integration results: the imbalance between the datasets.
Explore more webinars from us: www.pythiabio.com/multi-omics...