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) <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: 0.1.1
Depends: R (≥ 2.10)
Imports: Ckmeans.1d.dp, magrittr, rsvd, Seurat
Suggests: ggplot2, gridExtra, knitr, Matrix, rmarkdown, SeuratObject, usethis
Published: 2022-10-16
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


Reference manual: SPECK.pdf
Vignettes: SPECKVignette


Package source: SPECK_0.1.1.tar.gz
Windows binaries: r-devel: SPECK_0.1.1.zip, r-release: SPECK_0.1.1.zip, r-oldrel: SPECK_0.1.1.zip
macOS binaries: r-release (arm64): SPECK_0.1.1.tgz, r-oldrel (arm64): SPECK_0.1.1.tgz, r-release (x86_64): SPECK_0.1.1.tgz, r-oldrel (x86_64): SPECK_0.1.1.tgz
Old sources: SPECK archive

Reverse dependencies:

Reverse imports: STREAK


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