Intracellular spatial transcriptomic analysis toolkit (InSTAnT)
Author:
Funder
U.S. Department of Health & Human Services | National Institutes of Health
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41467-024-49457-w.pdf
Reference94 articles.
1. Rao, A., Barkley, D., França, G. S. & Yanai, I. Exploring tissue architecture using spatial transcriptomics. Nature 596, 211–220 (2021).
2. Marx, V. Method of the Year: spatially resolved transcriptomics. Nat. methods 18, 9–14 (2021).
3. Svensson, V., Teichmann, S. A. & Stegle, O. SpatialDE: identification of spatially variable genes. Nat. methods 15, 343–346 (2018).
4. Zhu, J., Sun, S. & Zhou, X. SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies. Genome Biol. 22, 1–25 (2021).
5. Chidester, B., Zhou, T., Alam, S. & Ma, J. SpiceMix enables integrative single-cell spatial modeling of cell identity. Nat. Genet. 55, 78–88 (2023).
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