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Chunk #16 — Results — Robustness and benchmarking analysis

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Dictionary learning for integrative, multimodal and scalable single-cell analysis.
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but we also observed failure modes in this regime. We note that generating bridge datasets consisting of more than 50 cells per subpopulation is quite feasible for many multi-omic technologies, and that our findings represent guidelines to assist in experimental design when performing multi-omic experiments. Notably, we found that substantially altering the relative composition of cell types in the bridge dataset (while maintaining the minimum threshold) did not negatively affect performance, demonstrating that bridge integration can be successful even in cases where there are substantial compositional differences in the sample used to generate the multi-omic bridge (Supplementary Fig. 2a,b).