Package: scCAN 1.0.5

scCAN: Single-Cell Clustering using Autoencoder and Network Fusion

A single-cell Clustering method using 'Autoencoder' and Network fusion ('scCAN') Bang Tran (2022) <doi:10.1038/s41598-022-14218-6> for segregating the cells from the high-dimensional 'scRNA-Seq' data. The software automatically determines the optimal number of clusters and then partitions the cells in a way such that the results are robust to noise and dropouts. 'scCAN' is fast and it supports Windows, Linux, and Mac OS.

Authors:Bang Tran [aut, cre], Duc Tran [aut], Hung Nguyen [aut], Tin Nguyen [fnd]

scCAN_1.0.5.tar.gz


scCAN_1.0.5.tar.gz(r-4.5-noble)scCAN_1.0.5.tar.gz(r-4.4-noble)
scCAN_1.0.5.tgz(r-4.4-emscripten)scCAN_1.0.5.tgz(r-4.3-emscripten)
scCAN.pdf |scCAN.html
scCAN/json (API)

# Install 'scCAN' in R:
install.packages('scCAN', repos = c('https://strancsus.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.

2.70 score 520 downloads 5 exports 52 dependencies

Last updated 10 months agofrom:cc0ee4fc5d. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 16 2025
R-4.5-linuxOKMar 16 2025
R-4.4-linuxOKMar 16 2025

Exports:adjustedRandIndexcalculate_celltype_probcurate_markersget_cluster_markersscCAN

Dependencies:BHbitbit64callrcliclustercodetoolscolorspacecorocpp11descdoParalleldqrngfarverFNNforeachglueigraphirlbaiteratorsjsonlitelabelinglatticelifecyclemagrittrMatrixmatrixStatsmunsellpkgconfigprocessxpspurrrR6RColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppParallelRcppProgressRhpcBLASctlrlangRSpectrasafetensorsscalesscDHAsitmotorchuwotvctrsviridisLitewithr

 

Rendered fromExample.Rmdusingknitr::rmarkdownon Mar 16 2025.

Last update: 2024-06-14
Started: 2021-07-12

Readme and manuals

Help Manual

Help pageTopics
adjustedRandIndexadjustedRandIndex
calculate_celltype_probcalculate_celltype_prob
curate_markerscurate_markers
find_markersfind_markers
find_specific_markerfind_specific_marker
get_cluster_markersget_cluster_markers
scCANscCAN
SCESCE