From spots to cells: Cell segmentation in spatial transcriptomics with BOMS.
Imaging-based Spatial Transcriptomics methods enable the study of gene expression and regulation in complex tissues at subcellular resolution. However, inaccurate cell segmentation procedures lead to misassignment of mRNAs to individual cells which can introduce errors in downstream analysis. Curren...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0311458 |
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| _version_ | 1849335456990232576 |
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| author | Ocima Kamboj Jeongbin Park Oliver Stegle Fred A Hamprecht |
| author_facet | Ocima Kamboj Jeongbin Park Oliver Stegle Fred A Hamprecht |
| author_sort | Ocima Kamboj |
| collection | DOAJ |
| description | Imaging-based Spatial Transcriptomics methods enable the study of gene expression and regulation in complex tissues at subcellular resolution. However, inaccurate cell segmentation procedures lead to misassignment of mRNAs to individual cells which can introduce errors in downstream analysis. Current methods estimate cell boundaries using auxiliary DAPI/Poly(A) stains. These stains can be difficult to segment, thus requiring manual tuning of the method, and not all mRNA molecules may be assigned to the correct cells. We describe a new method, based on mean shift, that segments the cells based on the spatial locations and the gene labels of the mRNA spots without requiring any auxiliary images. We evaluate the performance of BOMS across various publicly available datasets and demonstrate that it achieves comparable results to the best existing method while being simple to implement and significantly faster in execution. Open-source code is available at https://github.com/sciai-lab/boms. |
| format | Article |
| id | doaj-art-f1bf13a73abb46c4b080d853fdea0a0a |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-f1bf13a73abb46c4b080d853fdea0a0a2025-08-20T03:45:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01206e031145810.1371/journal.pone.0311458From spots to cells: Cell segmentation in spatial transcriptomics with BOMS.Ocima KambojJeongbin ParkOliver StegleFred A HamprechtImaging-based Spatial Transcriptomics methods enable the study of gene expression and regulation in complex tissues at subcellular resolution. However, inaccurate cell segmentation procedures lead to misassignment of mRNAs to individual cells which can introduce errors in downstream analysis. Current methods estimate cell boundaries using auxiliary DAPI/Poly(A) stains. These stains can be difficult to segment, thus requiring manual tuning of the method, and not all mRNA molecules may be assigned to the correct cells. We describe a new method, based on mean shift, that segments the cells based on the spatial locations and the gene labels of the mRNA spots without requiring any auxiliary images. We evaluate the performance of BOMS across various publicly available datasets and demonstrate that it achieves comparable results to the best existing method while being simple to implement and significantly faster in execution. Open-source code is available at https://github.com/sciai-lab/boms.https://doi.org/10.1371/journal.pone.0311458 |
| spellingShingle | Ocima Kamboj Jeongbin Park Oliver Stegle Fred A Hamprecht From spots to cells: Cell segmentation in spatial transcriptomics with BOMS. PLoS ONE |
| title | From spots to cells: Cell segmentation in spatial transcriptomics with BOMS. |
| title_full | From spots to cells: Cell segmentation in spatial transcriptomics with BOMS. |
| title_fullStr | From spots to cells: Cell segmentation in spatial transcriptomics with BOMS. |
| title_full_unstemmed | From spots to cells: Cell segmentation in spatial transcriptomics with BOMS. |
| title_short | From spots to cells: Cell segmentation in spatial transcriptomics with BOMS. |
| title_sort | from spots to cells cell segmentation in spatial transcriptomics with boms |
| url | https://doi.org/10.1371/journal.pone.0311458 |
| work_keys_str_mv | AT ocimakamboj fromspotstocellscellsegmentationinspatialtranscriptomicswithboms AT jeongbinpark fromspotstocellscellsegmentationinspatialtranscriptomicswithboms AT oliverstegle fromspotstocellscellsegmentationinspatialtranscriptomicswithboms AT fredahamprecht fromspotstocellscellsegmentationinspatialtranscriptomicswithboms |