Package: scINSIGHT 0.1.5

Kun Qian

scINSIGHT: Interpretation of Heterogeneous Single-Cell Gene Expression Data

We develop a novel matrix factorization tool named 'scINSIGHT' to jointly analyze multiple single-cell gene expression samples from biologically heterogeneous sources, such as different disease phases, treatment groups, or developmental stages. Given multiple gene expression samples from different biological conditions, 'scINSIGHT' simultaneously identifies common and condition-specific gene modules and quantify their expression levels in each sample in a lower-dimensional space. With the factorized results, the inferred expression levels and memberships of common gene modules can be used to cluster cells and detect cell identities, and the condition-specific gene modules can help compare functional differences in transcriptomes from distinct conditions. Please also see Qian K, Fu SW, Li HW, Li WV (2022) <doi:10.1186/s13059-022-02649-3>.

Authors:Kun Qian [aut, ctb, cre], Wei Vivian Li [aut, ctb]

scINSIGHT_0.1.5.tar.gz
scINSIGHT_0.1.5.tar.gz(r-4.7-arm64)scINSIGHT_0.1.5.tar.gz(r-4.7-x86_64)scINSIGHT_0.1.5.tar.gz(r-4.6-arm64)scINSIGHT_0.1.5.tar.gz(r-4.6-x86_64)
scINSIGHT_0.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
scINSIGHT/json (API)

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

Bug tracker:https://github.com/vivianstats/scinsight/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

1.74 score 11 scripts 229 downloads 2 exports 16 dependencies

Last updated from:5c0adb9bb9. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK144
linux-devel-x86_64OK130
source / vignettesOK172
linux-release-arm64OK181
linux-release-x86_64OK133
wasm-releaseOK125

Exports:create_scINSIGHTrun_scINSIGHT

Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixpkgconfigRANNRcppRcppArmadillorlangstringistringrvctrs