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scROSHI
View on CRAN: Click
here
Download and install scROSHI package within the R console
Install from CRAN:
install.packages("scROSHI")
Install from Github:
library("remotes")
install_github("cran/scROSHI")
Install by package version:
library("remotes")
install_version("scROSHI", "1.0.0.0")
Attach the package and use:
library("scROSHI")
Maintained by
Lars Bosshard
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-10
Latest Update: 2023-01-10
Description:
Identifying cell types based on expression profiles is a pillar of single cell analysis. 'scROSHI' identifies cell types based on expression profiles of single cell analysis by utilizing previously obtained cell type specific gene sets. It takes into account the hierarchical nature of cell type relationship and does not require training or annotated data. A detailed description of the method can be found at: Prummer, Bertolini, Bosshard, Barkmann, Yates, Boeva, The Tumor Profiler Consortium, Stekhoven, and Singer (2022) .
How to cite:
Lars Bosshard (2023). scROSHI: Robust Supervised Hierarchical Identification of Single Cells. R package version 1.0.0.0, https://cran.r-project.org/web/packages/scROSHI. Accessed 01 May. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for scROSHI
Functions, R codes and Examples using
the scROSHI R package
Some associated functions: config . f_annot_ctgenes . f_my_correlation_test . f_my_wilcox_test . f_score_ctgenes_U . f_score_profile_cor . marker_list . scROSHI . test_sce_data .
Some associated R codes: config.R . data.R . f_annot_ctgenes.R . f_my_correlation_test.R . f_my_wilcox_test.R . f_score_ctgenes_U.R . f_score_profile_cor.R . marker.R . scROSHI-package.R . scROSHI.R . Full scROSHI package functions and examples
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