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DenoIST

This is the released version of DenoIST; for the devel version, see DenoIST.

All versions 3.24 (devel), 3.23 (release)

DenoIST: Denoising Image-based Spatial Transcriptomics data


Bioconductor version: Release (3.23)

DenoIST identifies and removes contamination in Image-based Spatial Transcriptomics data, using a transposed poisson mixture model with local neighbourhood offsets to infer genes that are likely to be due to neighbourhood contamination rather than endogenous expression.

Author: Aaron Kwok [aut, cre] ORCID iD ORCID: 0000-0001-7831-4198 , Heejung Shim [aut], Davis McCarthy [aut]

Maintainer: Aaron Kwok <akwok at svi.edu.au>

Citation (from within R, enter citation("DenoIST")):

Aaron Kwok, Heejung Shim, Davis McCarthy. DenoIST: DenoIST: Denoising Image-based Spatial Transcriptomics data. doi:10.18129/B9.bioc.DenoIST, R package version 1.0.0, https://bioconductor.org/packages/DenoIST.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("DenoIST")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("DenoIST")
denoist_spe HTML R Script
Reference ManualPDF
NEWSText
LICENSEText

Details

biocViews GeneExpression, Preprocessing, SingleCell, Software, Spatial, Transcriptomics
Version1.0.0
In Bioconductor sinceBioC 3.23 (R-4.6) (< 6 months)
License MIT + file LICENSE
Depends R (>= 3.5.0)
Imports flexmix, hexbin, pbapply, sparseMatrixStats, SpatialExperiment, stats, SummarizedExperiment, parallel, Matrix, dbscan, methods
System Requirements
URLhttps://github.com/aaronkwc/DenoIST
Bug Reportshttps://github.com/aaronkwc/DenoIST/issues
See More
Suggests BiocStyle, knitr, rmarkdown, testthat, ggplot2, patchwork
Linking To
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Depends On Me
Imports Me
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Links To Me
Build Report Build Report, r-universe

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package DenoIST_1.0.0.tar.gz
Windows Binary (x86_64) DenoIST_1.0.0.zip
macOS Binary (big-sur-x86_64) DenoIST_1.0.0.tgz
macOS Binary (sonoma-arm64) DenoIST_1.0.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/DenoIST
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/DenoIST
Package Short Url https://bioconductor.org/packages/DenoIST/
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