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Making omics data visualization as effortless as watching the flames burn auburn on the mountain side 🧬🔥

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iSEEfier

R-CMD-check

The goal of iSEEfier is to provides a set of functionality to quickly and intuitively create, inspect, and combine initial configuration objects for the iSEE package.

These can be conveniently passed in a straightforward manner to the function call to launch iSEE() with the specified configuration, tailored to individual visualisation objectives.

This package currently works seamlessly with the sets of panels provided by the iSEE and iSEEu packages, but can be extended to accommodate the usage of any custom panel (e.g. from iSEEde, iSEEpathways, or any panel developed independently by the user).

iSEEfier can be found on Bioconductor (https://www.bioconductor.org/packages/iSEEfier).

Installation

You can install the development version of iSEEfier from GitHub with:

library("remotes")
remotes::install_github("NajlaAbassi/iSEEfier", 
                        dependencies = TRUE, build_vignettes = TRUE)

Example

This is a basic example which shows you how to use iSEEfier on a demo dataset (the one included in the scRNAseq package).

library(iSEEfier)
library(iSEE)

sce <- scRNAseq::RichardTCellData()
sce <- scuttle::logNormCounts(sce)
sce <- scater::runPCA(sce)
sce <- scater::runTSNE(sce)

gene_list <- c("ENSMUSG00000026581", "ENSMUSG00000005087", "ENSMUSG00000015437")
cluster <- "stimulus"
group <- "single cell quality"

initial <- iSEEinit(sce = sce, features = gene_list, clusters = cluster, groups = group)

iSEE(sce, initial = initial)

Usage overview

You can find the rendered version of the documentation of iSEEfier at the project website https://NajlaAbassi.github.io/iSEEfier, created with pkgdown.

Development

If you encounter a bug, have usage questions, or want to share ideas and functionality to make this package better, feel free to file an issue.

Code of Conduct

Please note that the iSEEfier project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

MIT

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Making omics data visualization as effortless as watching the flames burn auburn on the mountain side 🧬🔥

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