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 |
Documentation:
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