PaperS7546
Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks
PAC-MAN combines adaptive partitioning and population-network matching to address shifts between cytometry samples. Tests use simulations and prior reference datasets. Validated panels, coherent samples and downstream validation are required. Benchmark ties and losses qualify broad superiority wording; internal clade labels and a thymus percentage conflict between prose and tables. Scientific funding and author credentials do not validate unrelated UAP claims.
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