bioc-issue-bot
commented
2 months ago Hi @shazanfar
Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.
The DESCRIPTION file for this package is:
Package: SpatialFeatures
Title: Entropy-based subcellular and supercellular features for molecule-resolved spatial omics datasets
Version: 0.99.0
Authors@R: c(
person("Shila", "Ghazanfar", email = "shazanfar@gmail.com",
role = c("aut", "cre", "ctb"),comment = c(ORCID = "0000-0001-7861-6997")),
person("Guan", "Gui", role = "ctb")
)
Description: This package uses molecule-level information to extract new
cell-level features as an alternative to simply calculating gene counts. By
using four categories, sub-sector, super-sector, super-sector and
super-concentric segmentations of cells, SpatialFeatures then uses entropy
as a metric to arrive at a cell-by-gene level feature. Overall, this means
that we can extract more nuanced information from molecule-resolved spatial
gene expression for further downstream analysis with SingleCellExperiment.
License: GPL-2
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends: R (>= 4.4.0),
MoleculeExperiment,
SingleCellExperiment,
dplyr,
purrr,
parallel
Imports:
terra,
rlang
Suggests:
knitr,
ggplot2,
BiocStyle
VignetteBuilder: knitr
biocViews: Spatial, GeneExpression
URL: https://sydneybiox.github.io/SpatialFeatures/
BugReports: https://github.com/sydneybiox/SpatialFeatures/issues
HelenaLC
vjcitn
shazanfar
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