We benchmarked BioTuring Cell Type Prediction against Seurat v4 on several datasets. Below are some highlights, full benchmarks will come shortly with our manuscript.
Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing
Chunhong Zheng, Liangtao Zheng, Jae-Kwang Yoo, Huahu Guo, Yuanyuan Zhang, Xinyi Guo, Boxi Kang, Ruozhen Hu, Julie Y. Huang, Qiming Zhang, Zhouzerui Liu, Minghui Dong, Xueda Hu, Wenjun Ouyang, Jirun Peng, Zemin Zhang
BioTuring accurately detected more subtypes including: Exhausted CD4+ T cell, Exhausted CD8+ T cell, NKT-like CD8+ cell. Seurat v4 mislabels effector memory CD8+ T cell with cytotoxic CD4+ T cell and NK cell.
BioTuring and Seurat v4 yielded nearly identical results on naive CD4+ T cell, central memory CD4+ T cell (CD4 TCM), effector memory CD4+ T cell (CD4 TEM), regulatory CD4+ T cell (CD4 Treg), naive CD8+ T cell, mucosal associated invariant CD8+ T cell (CD8 MAIT).
Landscape and dynamics of single immune cells in hepatocellular carcinoma
Zhang Q, He Y, Luo N, Patel SJ, Han Y, Gao R, Modak M, Carotta S, Haslinger C, Kind D, Peet GW, Zhong G, Lu S, Zhu W, Mao Y, Xiao M, Bergmann M, Hu X, Kerkar SP, Vogt AB, Pflanz S, Liu K, Peng J, Ren X, Zhang Z
In this dataset, Serat v4 misidentified most cell types: macrophages were incorrectly identified as CD14 monocytes, mast cells were mislabeled as erythrocytes. BioTuring correctly identified all these cell types as its model was built from much larger training data with more cell types.
