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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-09-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-25557-9 |
| Summary: | 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 innovation moving forward. |
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| ISSN: | 2041-1723 |