Package: scROSHI 1.0.0.0

scROSHI: Robust Supervised Hierarchical Identification of Single Cells

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) <doi:10.1101/2022.04.05.487176>.

Authors:Lars Bosshard [aut, cre], Michael Prummer [aut]

scROSHI_1.0.0.0.tar.gz
scROSHI_1.0.0.0.zip(r-4.7)scROSHI_1.0.0.0.zip(r-4.6)scROSHI_1.0.0.0.zip(r-4.5)
scROSHI_1.0.0.0.tgz(r-4.6-any)scROSHI_1.0.0.0.tgz(r-4.5-any)
scROSHI_1.0.0.0.tar.gz(r-4.7-any)scROSHI_1.0.0.0.tar.gz(r-4.6-any)
scROSHI_1.0.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
scROSHI/json (API)

# Install 'scROSHI' in R:
install.packages('scROSHI', repos = c('https://lbosshard.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 9 scripts 227 downloads 6 exports 31 dependencies

Last updated from:e2fed0e27e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK154
source / vignettesOK207
linux-release-x86_64OK155
macos-release-arm64OK144
macos-oldrel-arm64OK171
windows-develOK90
windows-releaseOK100
windows-oldrelOK85
wasm-releaseOK152

Exports:f_annot_ctgenesf_my_correlation_testf_my_wilcox_testf_score_ctgenes_Uf_score_profile_corscROSHI

Dependencies:abindBHBiobaseBiocGenericsDelayedArraydqrngFNNgenericsGenomicRangesIRangesirlbalatticelimmaMatrixMatrixGenericsmatrixStatsRcppRcppAnnoyRcppEigenRcppProgressRSpectraS4ArraysS4VectorsSeqinfoSingleCellExperimentsitmoSparseArraystatmodSummarizedExperimentuwotXVector