13 papers · ranked by Valyu relevance
Fei Quan, Xin Liang, Mingjiang Cheng, Huan Yang + 12 more
'Shengyuan He' 'Shangqin Sun' 'Menglan Deng' 'Yanzhen He' 'Wei Liu' 'Shuai Wang' 'Shuxiang Zhao' 'Lantian Deng' 'Xiaobo Hou' 'Xinxin Zhang' 'Yun Xiao'] Background The advancement of single-cell sequencing has progressed our ability to solve biological questions. Cell type annotation is of vital importance to this…
Wenpin Hou, Zhicheng Ji
Here we demonstrate that the large language model GPT-4 can accurately annotate cell types using marker gene information in single-cell RNA sequencing analysis. When evaluated across hundreds of tissue and cell types, GPT-4 generates cell type annotations exhibiting strong concordance with manual annotations. This…
Jiawen Chen, Jianghao Zhang, Huaxiu Yao, Yun Li
Cell type annotation is a critical yet laborious step in single-cell RNA sequencing analysis. We present a trustworthy large language model (LLM)-agent, CellTypeAgent, which integrates LLMs with verification from relevant databases. CellTypeAgent achieves higher accuracy than existing methods while mitigating…
Hettiarachchige Wijewardena, Saloni Bhatia, Namrata Bhattacharya, Debarka Sengupta + 2 more
Accurate cell type identification is critical for interpreting single-cell transcriptomic data and understanding complex biological systems. In this review, we discuss how natural language processing and large language models can enhance the accuracy and scalability of cell type annotation. We also highlight how…
Tianhao Li, Zixuan Wang, Yuhang Liu, Sihan He + 2 more
'Yongqing Zhang'] Title: Abstract The rapid accumulation of single-cell RNA sequencing data has provided unprecedented computational resources for cell type annotation, significantly advancing our understanding of cellular heterogeneity. Leveraging gene expression profiles derived from transcriptomic data, researchers…
Qi Qi, Yanchi Su, Yi Fan, Zhuohan Yu + 3 more
The advent of single-cell RNA-seq has revolutionized the study of gene expression profiles with unparalleled resolution. Accurate identification of cell types from single-cell RNA-seq data is crucial to advance our understanding of disease progression and tumor microenvironments. Although various methods have been…
Sheng Wang, Angela Oliveira Pisco, Aaron McGeever, Maria Brbic + 5 more
Single cell technologies are rapidly generating large amounts of data that enables us to understand biological systems at single-cell resolution. However, joint analysis of datasets generated by independent labs remains challenging due to a lack of consistent terminology to describe cell types. Here, we present…
Dimitrios Kleftogiannis, Sonia Gavasso, Benedicte Sjo Tislevoll, Nisha van der Meer + 10 more
'Nisha van der Meer' 'Inga K.F. Motzfeldt' 'Monica Hellesøy' 'Stein-Erik Gullaksen' 'Emmanuel Griessinger' 'Oda Fagerholt' 'Andrea Lenartova' 'Yngvar Fløisand' 'Jan Jacob Schuringa' 'Bjørn Tore Gjertsen' 'Inge Jonassen'] Title: Summary Mass cytometry by time-of-flight (CyTOF) is an emerging technology allowing for…
Lin Yuan, Junjie Cao, Shengguo Sun, Siguo Wang + 3 more
A key challenge in single-cell RNA sequencing (scRNA-seq) data analysis is accurately and efficiently identifying the cell type of each cell. Cell type annotation for scRNA-seq data not only needs to overcome batch effects caused by various factors but also requires effective handling of large-scale scRNA-seq datasets.…
Aanchal Mongia, Fatema Tuz Zohora, Noah G. Burget, Yeqiao Zhou + 9 more
'Diane C. Saunders' 'Yue J. Wang' 'Marcela Brissova' 'Alvin C. Powers' 'Klaus H. Kaestner' 'Golnaz Vahedi' 'Ali Naji' 'Gregory W. Schwartz' 'Robert B. Faryabi'] Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image…
Shawn Zheng Kai Tan, Aleix Puig-Barbe, Damien Goutte-Gattat, Caroline Eastwood + 31 more
Single-cell omics technologies have transformed our understanding of cellular diversity by enabling high-resolution profiling of individual cells. However, the unprecedented scale and heterogeneity of these datasets demand robust frameworks for data integration and annotation. The Cell Ontology (CL) has emerged as a…
Euxhen Hasanaj, Jingtao Wang, Arjun Sarathi, Jun Ding + 1 more
'Ziv Bar-Joseph'] Cell type assignment is a major challenge for all types of high throughput single cell data. In many cases such assignment requires the repeated manual use of external and complementary data sources. To improve the ability to uniformly assign cell types across large consortia, platforms and…
Minxing Pang, Tarun Kanti Roy, Xiaodong Wu, Kai Tan
Cell segmentation and classification are critical tasks in spatial omics data analysis. Here we introduce CelloType, an end-to-end model designed for cell segmentation and classification for image-based spatial omics data. Unlike the traditional two-stage approach of segmentation followed by classification, CelloType…