bioc-issue-bot
commented
2 years ago Hi @MarcElosua
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: SPOTlight
Version: 0.99.0
Type: Package
Title: `SPOTlight`: Spatial Transcriptomics Deconvolution
Description: `SPOTlight`provides a method to deconvolute spatial transcriptomics
spots using a seeded NMF approach along with visualization tools to assess
the results. Spatially resolved gene expression profiles are key to
understand tissue organization and function. However, novel spatial
transcriptomics (ST) profiling techniques lack single-cell resolution and
require a combination with single-cell RNA sequencing (scRNA-seq)
information to deconvolute the spatially indexed datasets. Leveraging the
strengths of both data types, we developed SPOTlight, a computational tool
that enables the integration of ST with scRNA-seq data to infer the location
of cell types and states within a complex tissue. SPOTlight is centered
around a seeded non-negative matrix factorization (NMF) regression,
initialized using cell-type marker genes and non-negative least squares
(NNLS) to subsequently deconvolute ST capture locations (spots).
Authors@R: c(
person("Marc", "Elosua-Bayes", email="elosua.marc@gmail.com", role=c("aut", "cre")),
person("Helena L.", "Crowell", email="helena@crowell.eu", role="aut"))
Depends: R (>= 4.1)
Imports:
ggplot2,
NMF,
Matrix,
matrixStats,
nnls,
SeuratObject,
SingleCellExperiment,
stats
Suggests:
BiocStyle,
ExperimentHub,
DelayedArray,
ggcorrplot,
grid,
igraph,
jpeg,
knitr,
methods,
png,
scater,
scatterpie,
scran,
Seurat,
SeuratData,
SpatialExperiment,
SummarizedExperiment,
TabulaMurisSenisData,
TENxVisiumData,
testthat
biocViews:
SingleCell,
Spatial,
StatisticalMethod
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.2
VignetteBuilder: knitr
URL: https://github.com/MarcElosua/SPOTlight
BugReports: https://github.com/MarcElosua/SPOTlight/issues
LiNk-NY
HelenaLC
MarcElosua
lshep
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.