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SPECK  

Receptor Abundance Estimation using Reduced Rank Reconstruction and Clustered Thresholding
View on CRAN: Click here


Download and install SPECK package within the R console
Install from CRAN:
install.packages("SPECK")

Install from Github:
library("remotes")
install_github("cran/SPECK")

Install by package version:
library("remotes")
install_version("SPECK", "1.0.0")



Attach the package and use:
library("SPECK")
Maintained by
Azka Javaid
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-13
Latest Update: 2023-11-17
Description:
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>.
How to cite:
Azka Javaid (2022). SPECK: Receptor Abundance Estimation using Reduced Rank Reconstruction and Clustered Thresholding. R package version 1.0.0, https://cran.r-project.org/web/packages/SPECK
Previous versions and publish date:
0.1.0 (2022-10-13 10:42), 0.1.1 (2022-10-16 09:32)
Other packages that cited SPECK R package
View SPECK citation profile
Other R packages that SPECK depends, imports, suggests or enhances
Functions, R codes and Examples using the SPECK R package
Some associated functions: SPECK-package . ckmeansThreshold . pbmc.rna.mat . pipe . randomizedRRR . speck . 
Some associated R codes: CkmeansThreshold.R . RandomizedRRR.R . SPECK-package.R . SPECK.R . data.R . utils-pipe.R .  Full SPECK package functions and examples
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