SPECK: Receptor Abundance Estimation using Reduced Rank Reconstruction
and Clustered Thresholding
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>.
| Version: | 1.0.1 | 
| Depends: | R (≥ 3.5) | 
| Imports: | Ckmeans.1d.dp, magrittr, Matrix (≥ 1.6.1.1), rsvd, Seurat | 
| Suggests: | ggplot2, gridExtra, knitr, rmarkdown, SeuratObject, usethis | 
| Published: | 2025-10-05 | 
| DOI: | 10.32614/CRAN.package.SPECK | 
| Author: | H. Robert Frost [aut],
  Azka Javaid [aut, cre] | 
| Maintainer: | Azka Javaid  <azka.javaid.gr at dartmouth.edu> | 
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] | 
| NeedsCompilation: | no | 
| CRAN checks: | SPECK results | 
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