bioc-issue-bot
commented
2 months ago Hi @PratibhaPanwar
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: clustSIGNAL
Type: Package
Title: clustSIGNAL: a spatial clustering method
Version: 0.99.0
Authors@R: c(
person("Pratibha", "Panwar", email = "pratibhapanwar.4@gmail.com",
role = c("cre", "aut", "ctb"), comment = c(ORCID = "0000-0002-7437-7084")),
person("Boyi", "Guo", email = "boyi.guo.work@gmail.com", role = "aut"),
person("Haowen", "Zhao", email = "haowen.zhou19@gmail.com", role = "aut"),
person("Stephanie", "Hicks", email = "shicks19@jhu.edu", role = "aut"),
person("Shila", "Ghazanfar", email = "shazanfar@gmail.com",
role = c("aut", "ctb"), comment = c(ORCID = "0000-0001-7861-6997")))
Description: clustSIGNAL: clustering of Spatially Informed Gene expression with
Neighbourhood Adapted Learning. A tool for adaptively smoothing and clustering
gene expression data. clustSIGNAL uses entropy to measure heterogeneity of
cell neighbourhoods and performs a weighted, adaptive smoothing, where
homogeneous neighbourhoods are smoothed more and heterogeneous neighbourhoods
are smoothed less. This not only overcomes data sparsity but also incorporates
spatial context into the gene expression data. The resulting smoothed gene
expression data is used for clustering and could be used for other downstream
analyses.
License: GPL-2
Encoding: UTF-8
URL: https://sydneybiox.github.io/clustSIGNAL/
BugReports: https://github.com/sydneybiox/clustSIGNAL/issues
biocViews: Clustering, Software, GeneExpression, Spatial, Transcriptomics, SingleCell
RoxygenNote: 7.3.2
Depends: R (>= 4.4.0), SpatialExperiment
Imports: BiocParallel,
BiocNeighbors,
bluster,
scater,
harmony,
SingleCellExperiment,
SummarizedExperiment,
methods
Suggests: knitr,
BiocStyle,
aricode,
cluster,
distances,
dplyr,
ggplot2,
patchwork,
scattermore
VignetteBuilder: knitr
lshep
svalvaro
Update the following URL to point to the GitHub repository of the package you wish to submit to Bioconductor
Confirm the following by editing each check box to '[x]'
[x] I understand that by submitting my package to Bioconductor, the package source and all review commentary are visible to the general public.
[x] I have read the Bioconductor Package Submission instructions. My package is consistent with the Bioconductor Package Guidelines.
[x] I understand Bioconductor Package Naming Policy and acknowledge Bioconductor may retain use of package name.
[x] I understand that a minimum requirement for package acceptance is to pass R CMD check and R CMD BiocCheck with no ERROR or WARNINGS. 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.
[x] My package addresses statistical or bioinformatic issues related to the analysis and comprehension of high throughput genomic data.
[x] 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.
[x] I am familiar with the Bioconductor code of conduct and agree to abide by it.
I am familiar with the essential aspects of Bioconductor software management, including:
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. Follow the link on the home page of the Bioconductor website to sign up.