Computational challenges and opportunities in spatially resolved transcriptomic data analysis

Spatially resolved transcriptomic data demand new computational analysis methods to derive biological insights. Here, we comment on these associated computational challenges as well as highlight the opportunities for standardized benchmarking metrics and data-sharing infrastructure in spurring innov...

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Veröffentlicht in:	Nature communications Jg. 12; H. 1; S. 5283 - 5
Hauptverfasser:	Atta, Lyla, Fan, Jean
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 06.09.2021 Nature Publishing Group Nature Portfolio
Schlagworte:	14/32 45/91 631/114 631/61/212/2019 Animals Benchmarking Cell Communication - genetics Cell cycle Cells, Cultured Comment Computer applications Data analysis Demand analysis Gene expression Gene Expression Profiling - statistics & numerical data Humanities and Social Sciences Humans Ligands Mathematical Computing Morphology multidisciplinary Open source software Science Science (multidisciplinary) Single-Cell Analysis - methods Single-Cell Analysis - statistics & numerical data Transcriptome
ISSN:	2041-1723, 2041-1723
Online-Zugang:	Volltext
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