방사선의학 웹진

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Abstract
Spatial transcriptomics is a cutting-edge technique that combines gene expression with spatial information, allowing researchers to study molecular patterns within tissue architecture. Here, we present IAMSAM, a user-friendly web-based tool for analyzing spatial transcriptomics data focusing on morphological features. IAMSAM accurately segments tissue images using the Segment Anything Model, allowing for the semi-automatic selection of regions of interest based on morphological signatures. Furthermore, IAMSAM provides downstream analysis, such as identifying differentially expressed genes, enrichment analysis, and cell type prediction within the selected regions. With its simple interface, IAMSAM empowers researchers to explore and interpret heterogeneous tissues in a streamlined manner.

Affiliations

Dongjoo Lee # 1, Jeongbin Park # 1, Seungho Cook 1, Seongjin Yoo 1, Daeseung Lee 1, Hongyoon Choi 2 3 4
1Portrai, Inc, 78-18, Dongsulla-Gil, Jongno-Gu, Seoul, 03136, Republic of Korea.
2Portrai, Inc, 78-18, Dongsulla-Gil, Jongno-Gu, Seoul, 03136, Republic of Korea. chy100@snu.ac.kr.
3Department of Nuclear Medicine, Seoul National University Hospital, 03080, Seoul, Republic of Korea. chy100@snu.ac.kr.
4Department of Nuclear Medicine, Seoul National University College of Medicine, 03080, Seoul, Republic of Korea. chy100@snu.ac.kr.
#Contributed equally.