Murray, Evan

Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

Rodriques, S. G., Stickels, R. R., Goeva, A., Martin, C. A., Murray, E., Vanderburg, C. R., Welch, J., Chen, L. M., Chen, F., & Macosko, E. Z. (2019) · Science

Single-cell and spatial transcriptomicsGene expression and cancer classification

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Robust decomposition of cell type mixtures in spatial transcriptomics

Cable, D. M., Murray, E., Zou, L. S., Goeva, A., Macosko, E. Z., Chen, F., & Irizarry, R. A. (2022) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,487

Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2

Stickels, R. R., Murray, E., Kumar, P., Li, J., Marshall, J. L., Di Bella, D. J., Arlotta, P., Macosko, E. Z., & Chen, F. (2021) · Nature Biotechnology

Single-cell and spatial transcriptomicsRNA Research and Splicing

Cited by 1,295

Spatial genomics enables multi-modal study of clonal heterogeneity in tissues

Zhao, T., Chiang, Z. D., Morriss, J. W., LaFave, L. M., Murray, E. M., Del Priore, I., Meli, K., Lareau, C. A., Nadaf, N. M., Li, J., et al. (2022) · Nature

Single-cell and spatial transcriptomicsCancer Genomics and Diagnostics

Cited by 268