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STREAK (version 1.0.0)

Receptor Abundance Estimation using Feature Selection and Gene Set Scoring

Description

Performs receptor abundance estimation for single cell RNA-sequencing data using a supervised feature selection mechanism and a thresholded gene set scoring procedure. Seurat's normalization method is described in: Hao et al., (2021) , Stuart et al., (2019) , Butler et al., (2018) and Satija et al., (2015) . Method for reduced rank reconstruction and rank-k selection is detailed in: Javaid et al., (2022) . Gene set scoring procedure is described in: Frost et al., (2020) . Clustering method is outlined in: Song et al., (2020) and Wang et al., (2011) .

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Version

Install

install.packages('STREAK')

Monthly Downloads

187

Version

1.0.0

License

GPL (>= 2)

Maintainer

Azka Javaid

Last Published

November 17th, 2023

Functions in STREAK (1.0.0)

STREAK-package

STREAK: Receptor Abundance Estimation using Feature Selection and Gene Set Scoring
receptorAbundanceEstimation

Receptor abundance estimation for single cell RNA-sequencing (scRNA-seq) data using gene set scoring and thresholding.
receptorGeneSetConstruction

Gene sets weights membership matrix construction for receptor abundance estimation.
target.malt.rna.mat

Single cell RNA-sequencing (scRNA-seq) target subset of the 10X Genomics MALT counts.
train.malt.adt.mat

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) training subset of the 10X Genomics MALT counts.
train.malt.rna.mat

Single cell RNA-sequencing (scRNA-seq) training subset of the 10X Genomics MALT counts.