A hybrid machine learning and regression method for cell type deconvolution of spatial barcoding-based transcriptomic data
Yunqing Liu, Ningshan Li, Ji Qi, Gang Xu, Jiayi Zhao, Nating Wang, Xiayuan Huang, Wenhao Jiang, A. Justet, Taylor Sterling Adams, Robert Homer, Amei Amei, Iván O. Rosas, Naftali Kaminski, Zuoheng Wang, Xiting Yan
SDePER improves cell type deconvolution in spatial transcriptomic data by addressing platform effects, sparsity, and spatial correlation, achieving more accurate results than existing methods.
bioRxiv · Aug 24, 2023 · PreprintBioinformatics