Open MelodyJIN-Y opened 1 week ago
Hi @MelodyJIN-Y
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: jazzPanda
Type: Package
Title: Finding spatially relevant marker genes in image based spatial transcriptomics data
Version: 0.99.0
Date: 2024-07-25
Authors@R:
c(person(given = "Melody",
family = "Jin",
role = c("aut", "cre"),
email = "jin.m@wehi.edu.au",
comment=c(ORCID="0000-0002-2222-0958"))
)
LazyData: FALSE
Depends: R (>= 4.4.0)
Imports: spatstat.geom, dplyr, glmnet, caret, foreach, stats, magrittr, doParallel, BiocParallel
VignetteBuilder: knitr
Suggests:
BiocStyle,
knitr,
rmarkdown,
spatstat,
Seurat,
statmod,
corrplot,
ggplot2,
ggraph,
ggrepel,
gridExtra,
reshape2,
igraph,
jsonlite,
vdiffr,
patchwork,
ggpubr,
tidyr,
data.table,
testthat (>= 3.0.0)
Description: This package contains the function to find marker genes for image-based spatial transcriptomics data. There are functions to create spatial vectors from the cell and transcript coordiantes, which are passed as inputs to find marker genes. Marker genes are detected for every cluster by two approaches. The first approach is by permtuation testing, which is implmented in parallel for finding marker genes for one sample study. The other approach is to build a linear model for every gene. This approach can account for multiple samples and backgound noise.
License: GPL-3 + file LICENSE
URL: https://github.com/phipsonlab/jazzPanda, https://bhuvad.github.io/jazzPanda/
BugReports: https://github.com/phipsonlab/jazzPanda/issues
biocViews: Spatial, GeneExpression, DifferentialExpression, StatisticalMethod, Transcriptomics
RoxygenNote: 7.3.2
Encoding: UTF-8
Config/testthat/edition: 3
Packages are generally expected to use standard Bioconductor class objects. Please expand to use standard class objects like SpatialExperiment or SingleCellExperiment. For What Its Worth you might also check out the Experiment Data Package TENxXeniumData that already provides Xenium data in such a standard class object.
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.