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) doi:10.48550/arXiv.0909.4061. 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.

Last 30 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.