Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics
Abstract Spatial transcriptomics has revolutionized the study of gene expression within tissues, while preserving spatial context. However, annotating spatial spots’ biological identity remains a challenge. To tackle this, we introduce Pianno, a Bayesian framework automating structural semantics ann...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-04-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-47152-4 |
| _version_ | 1797219708456402944 |
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| author | Yuqiu Zhou Wei He Weizhen Hou Ying Zhu |
| author_facet | Yuqiu Zhou Wei He Weizhen Hou Ying Zhu |
| author_sort | Yuqiu Zhou |
| collection | DOAJ |
| description | Abstract Spatial transcriptomics has revolutionized the study of gene expression within tissues, while preserving spatial context. However, annotating spatial spots’ biological identity remains a challenge. To tackle this, we introduce Pianno, a Bayesian framework automating structural semantics annotation based on marker genes. Comprehensive evaluations underscore Pianno’s remarkable prowess in precisely annotating a wide array of spatial semantics, ranging from diverse anatomical structures to intricate tumor microenvironments, as well as in estimating cell type distributions, across data generated from various spatial transcriptomics platforms. Furthermore, Pianno, in conjunction with clustering approaches, uncovers a region- and species-specific excitatory neuron subtype in the deep layer 3 of the human neocortex, shedding light on cellular evolution in the human neocortex. Overall, Pianno equips researchers with a robust and efficient tool for annotating diverse biological structures, offering new perspectives on spatial transcriptomics data. |
| first_indexed | 2024-04-24T12:37:56Z |
| format | Article |
| id | doaj.art-0500bb5d77894d16b5012192c8a80574 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-24T12:37:56Z |
| publishDate | 2024-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-0500bb5d77894d16b5012192c8a805742024-04-07T11:23:44ZengNature PortfolioNature Communications2041-17232024-04-0115111510.1038/s41467-024-47152-4Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomicsYuqiu Zhou0Wei He1Weizhen Hou2Ying Zhu3State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan UniversityState Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan UniversityState Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan UniversityState Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, Institutes of Brain Science and Department of Neurosurgery, Huashan Hospital, Fudan UniversityAbstract Spatial transcriptomics has revolutionized the study of gene expression within tissues, while preserving spatial context. However, annotating spatial spots’ biological identity remains a challenge. To tackle this, we introduce Pianno, a Bayesian framework automating structural semantics annotation based on marker genes. Comprehensive evaluations underscore Pianno’s remarkable prowess in precisely annotating a wide array of spatial semantics, ranging from diverse anatomical structures to intricate tumor microenvironments, as well as in estimating cell type distributions, across data generated from various spatial transcriptomics platforms. Furthermore, Pianno, in conjunction with clustering approaches, uncovers a region- and species-specific excitatory neuron subtype in the deep layer 3 of the human neocortex, shedding light on cellular evolution in the human neocortex. Overall, Pianno equips researchers with a robust and efficient tool for annotating diverse biological structures, offering new perspectives on spatial transcriptomics data.https://doi.org/10.1038/s41467-024-47152-4 |
| spellingShingle | Yuqiu Zhou Wei He Weizhen Hou Ying Zhu Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics Nature Communications |
| title | Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics |
| title_full | Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics |
| title_fullStr | Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics |
| title_full_unstemmed | Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics |
| title_short | Pianno: a probabilistic framework automating semantic annotation for spatial transcriptomics |
| title_sort | pianno a probabilistic framework automating semantic annotation for spatial transcriptomics |
| url | https://doi.org/10.1038/s41467-024-47152-4 |
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