Closed marvinquiet closed 4 years ago
Hi @marvinquiet
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: LRcell
Type: Package
Title: Differential cell type change analysis using Logistic/linear Regression
Version: 0.99.0
Date: 2020-08-08
Authors@R: person("Wenjing", "Ma",
email="wenjing.ma@emory.edu",
role=c("cre", "aut"),
comment = c(ORCID = "0000-0001-8757-651X"))
Maintainer: Wenjing Ma <wenjing.ma@emory.edu>
BugReports: https://github.com/marvinquiet/LRcell/issues
GitURL: https://github.com/marvinquiet/LRcell
Description: The goal of LRcell is to identify specific sub-cell types that drives the changes
observed in a bulk RNA-seq differential gene expression experiment. To achieve this,
LRcell utilizes sets of cell marker genes acquired from single-cell RNA-sequencing (scRNA-seq)
as indicators for various cell types in the tissue of interest. Next, for each cell type,
using its marker genes as indicators, we apply Logistic Regression on the complete
set of genes with differential expression p-values to calculate a cell-type significance p-value.
Finally, these p-values are compared to predict which one(s) are likely to be responsible
for the differential gene expression pattern observed in the bulk RNA-seq experiments.
LRcell is inspired by the LRpath[@sartor2009lrpath] algorithm developed by Sartor et al.,
originally designed for pathway/gene set enrichment analysis. LRcell contains three major
components: LRcell analysis, plot generation and marker gene selection.
All modules in this package are written in R. This package also provides marker
genes in the Prefrontal Cortex (pFC) human brain region and nine mouse brain
regions (Frontal Cortex, Cerebellum, Globus Pallidus, Hippocampus, Entopeduncular,
Posterior Cortex, Striatum, Substantia Nigra and Thalamus).
License: MIT + file LICENSE
Encoding: UTF-8
biocViews: SingleCell, GeneSetEnrichment, Sequencing, Regression, GeneExpression, DifferentialExpression
Depends:
R (>= 3.6)
Imports:
BiocParallel,
dplyr,
ggplot2,
ggrepel,
magrittr,
stats,
utils
RoxygenNote: 7.1.1
Suggests:
BiocStyle,
knitr,
rmarkdown,
roxygen2,
testthat
VignetteBuilder: knitr
Your repository contains files larger than 5Mb
files larger than 5Mb:
/marker_genes_lib/mouse/FCenriched_genes.RDS
/marker_genes_lib/mouse/GPenriched_genes.RDS
/marker_genes_lib/mouse/HCenriched_genes.RDS
/marker_genes_lib/mouse/PCenriched_genes.RDS
Please update these to conform with package guidelines; it may be necessary to update your vignette to use a representative sample of data, or to make these data resources available via AnnotationHub or ExperimentHub () (for example http://bioconductor.org/packages/devel/bioc/vignettes/AnnotationHub/inst/doc/CreateAnAnnotationPackage.html).
Please update your package, and run BiocCheck::BiocCheck(). When your package is ready for review, please post a comment here.
I'll close this issue now; post a comment here when it is ready to be reviewed.
Hi,
Thank you for your suggestion! I am using the /marker_genes_lib/ as an online data resource and when building the package, I included the following lines in .Rbuildignore
.
# ignore marker genes library
marker_genes_lib/
The LRcell package built through R CMD build LRcell/
could pass both R CMD BiocCheck
and R CMD check
.
Sincerely, Wenjing
remove the large files from the master branch of your git repository; your git repository is cloned to ours as part of the review / dissemination process, and files cannot be that large.
Got it, will do soon! Thank you! I will let you know when I finish.
Hi, sorry for the long wait. I just uploaded my external data as an ExperimentHub package named LRcellTypeMarkers, which could pass the R CMD check
and R CMD BiocCheck
. Do I need to re-submit a repo or can I just do it here?
The Github repo can be found here: https://github.com/marvinquiet/LRcellTypeMarkers.
Because I submitted my software package first, according to the documentation of Submitting Related Packages, should I wait until the review in progress
tag and then inform you of my original software package? Not sure what is the most appropriate thing I would do in my case. Any suggestions or help is appreciated.
@lshep can you walk us through the best steps? thanks!
Hi @mtmorgan and @lshep,
Thank you for your help!
I have checked both my packages and I think these two are both ready for the review process. Below please find the two packages.
Could you please let me know what I can do to trigger the review process?
Sincerely, Wenjing
@marvinquiet Very sorry for the delayed response. Could you please open a new issue for the process to continue. Remember to submit the experiment data hub package first. Wait for it be in "review in progress" instead of "awaiting moderation" and then you can submit the second software package under the same issue using AdditionalPackage: https://github.com/marvinquiet/LRcell
Cheers!
Got you! Thank you so much for your suggestions.
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