Schroeder, Amelia

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network

Hu, J., Li, X., Coleman, K., Schroeder, A., Ma, N., Irwin, D. J., Lee, E. B., Shinohara, R. T., & Li, M. (2021) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,113

Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology

Zhang, D., Schroeder, A., Yan, H., Yang, H., Hu, J., Lee, M. Y. Y., Cho, K. S., Susztak, K., Xu, G. X., Feldman, M. D., et al. (2024) · Nature Biotechnology

Single-cell and spatial transcriptomicsCell Image Analysis Techniques

Cited by 219

A multi-use deep learning method for CITE-seq and single-cell RNA-seq data integration with cell surface protein prediction and imputation

Lakkis, J., Schroeder, A., Su, K., Lee, M. Y. Y., Bashore, A. C., Reilly, M. P., & Li, M. (2022) · Nature Machine Intelligence

Single-cell and spatial transcriptomicsBioinformatics and Genomic Networks

Cited by 105

Resolving tissue complexity by multimodal spatial omics modeling with MISO

Coleman, K., Schroeder, A., Loth, M., Zhang, D., Park, J. H., Sung, J.-Y., Blank, N., Cowan, A. J., Qian, X., Chen, J., et al. (2025) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 87