Yajima, Masanao

MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data

Finak, G., McDavid, A., Yajima, M., Deng, J., Gersuk, V., Shalek, A. K., Slichter, C. K., Miller, H. W., McElrath, M. J., Prlic, M., et al. (2015) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 3,159

Why We (Usually) Don't Have to Worry About Multiple Comparisons

Gelman, A., Hill, J., & Yajima, M. (2012) · Journal of Research on Educational Effectiveness

Statistical Methods and Bayesian InferenceStatistical Methods in Clinical Trials

Cited by 1,274

Decontamination of ambient RNA in single-cell RNA-seq with DecontX

Yang, S., Corbett, S. E., Koga, Y., Wang, Z., Johnson, W. E., Yajima, M., & Campbell, J. D. (2020) · Genome Biology

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 635

Transient rapamycin treatment can increase lifespan and healthspan in middle-aged mice

Bitto, A., Ito, T. K., Pineda, V. V., LeTexier, N. J., Huang, H. Z., Sutlief, E., Tung, H., Vizzini, N., Chen, B., Smith, K., et al. (2016) · eLife

Genetics, Aging, and Longevity in Model OrganismsAutophagy in Disease and Therapy

Cited by 474

Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Hong, R., Koga, Y., Bandyadka, S., Leshchyk, A., Wang, Y., Akavoor, V., Cao, X., Sarfraz, I., Wang, Z., Alabdullatif, S., et al. (2022) · Nature Communications

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 82