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The DESCRIPTION file for this package is:
Package: SVP
Title: Predicting cell states and their variability in single-cell or spatial omics data
Version: 0.99.0
Authors@R: c(
person("Shuangbin", "Xu", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3513-5362")),
person("Guangchuang", "Yu", email = "[email protected]", role = c("aut", "ctb"), comment = c(ORCID = "0000-0002-6485-8781")))
Description: SVP uses the distance between cells and cells, features and features, cells and
features in the space of MCA to build nearest neighbor graph, then uses random walk with
restart algorithm to calculate the activity score of gene sets (such as cell marker genes,
kegg pathway, go ontology, gene modules, transcription factor or miRNA target sets, reactome
pathway, ...), which is then further weighted using the hypergeometric test results from
the original expression matrix. To detect the spatially or single cell variable gene sets or
(other features) and the spatial colocalization between the features accurately, SVP provides
some global and local spatial autocorrelation method to identify the spatial variable features.
SVP is developed based on SingleCellExperiment class, which can be interoperable with the
existing computing ecosystem.
Depends:
R (>= 4.3.0)
Imports:
Rcpp,
RcppParallel,
methods,
cli,
dplyr,
rlang,
S4Vectors,
SummarizedExperiment,
SingleCellExperiment,
SpatialExperiment,
BiocGenerics,
BiocParallel,
fastmatch,
pracma,
stats,
withr,
Matrix,
DelayedMatrixStats,
deldir,
utils,
BiocNeighbors,
ggplot2,
ggstar,
ggtree,
ggfun
Suggests:
rmarkdown,
prettydoc,
broman,
RSpectra,
BiasedUrn,
knitr,
ks,
igraph,
testthat (>= 3.0.0),
scuttle,
magrittr,
DropletUtils,
tibble,
tidyr,
harmony,
aplot,
scales,
ggsc,
scran
License: GPL-3
BugReports: https://github.com/YuLab-SMU/SVP/issues
URL: https://github.com/YuLab-SMU/SVP
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
biocViews: SingleCell, Software, Spatial, Transcriptomics, GeneTarget,
GeneExpression, GeneSetEnrichment, Transcription, GO, KEGG
SystemRequirements: GNU make
ByteCompile: true
VignetteBuilder: knitr
LinkingTo:
Rcpp,
RcppArmadillo (>= 14.0),
RcppParallel,
RcppEigen,
dqrng
Config/testthat/edition: 3
LazyData: false
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Bioconductor may retain use of package name.
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Passing these checks does not result in automatic acceptance. The
package will then undergo a formal review and recommendations for
acceptance regarding other Bioconductor standards will be addressed.
My package addresses statistical or bioinformatic issues related
to the analysis and comprehension of high throughput genomic data.
I am committed to the long-term maintenance of my package. This
includes monitoring the support site for issues that users may
have, subscribing to the bioc-devel mailing list to stay aware
of developments in the Bioconductor community, responding promptly
to requests for updates from the Core team in response to changes in
R or underlying software.
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agree to abide by it.
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months, for bug fixes.
(optionally via GitHub).
For questions/help about the submission process, including questions about
the output of the automatic reports generated by the SPB (Single Package
Builder), please use the #package-submission channel of our Community Slack.
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The text was updated successfully, but these errors were encountered: