TY  - JOUR
AU  - Kamboj, Ocima
AU  - Park, Jeongbin
AU  - Stegle, Oliver
AU  - Hamprecht, Fred A
TI  - From spots to cells: Cell segmentation in spatial transcriptomics with BOMS.
JO  - PLOS ONE
VL  - 20
IS  - 6
SN  - 1932-6203
CY  - San Francisco, California, US
PB  - PLOS
M1  - DKFZ-2025-01213
SP  - e0311458 -
PY  - 2025
AB  - 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.
KW  - Transcriptome
KW  - Gene Expression Profiling: methods
KW  - RNA, Messenger: genetics
KW  - RNA, Messenger: metabolism
KW  - Humans
KW  - Software
KW  - Algorithms
KW  - Image Processing, Computer-Assisted: methods
KW  - RNA, Messenger (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:40504785
DO  - DOI:10.1371/journal.pone.0311458
UR  - https://inrepo02.dkfz.de/record/302015
ER  -