SPECK

Surface Protein abundance Estimation using CKmeans-based clustered thresholding ('SPECK') is an unsupervised learning-based method that performs receptor abundance estimation for single cell RNA-sequencing data based on reduced rank reconstruction (RRR) and a clustered thresholding mechanism. Seurat's normalization method is described in: Hao et al., (2021) doi:10.1016/j.cell.2021.04.048, Stuart et al., (2019) doi:10.1016/j.cell.2019.05.031, Butler et al., (2018) doi:10.1038/nbt.4096 and Satija et al., (2015) doi:10.1038/nbt.3192. Method for the RRR is further detailed in: Erichson et al., (2019) doi:10.18637/jss.v089.i11 and Halko et al., (2009) . Clustering method is outlined in: Song et al., (2020) doi:10.1093/bioinformatics/btaa613 and Wang et al., (2011) doi:10.32614/RJ-2011-015.