bioc-issue-bot
commented
3 years ago Hi @tghosh30
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: cytoKernel
Type: Package
Title: Differential expression using kernel-based score test
Version: 0.99.0
Date: 2021-09-27
Authors@R:
c(person("Tusharkanti", "Ghosh",
email = "tusharkantighosh30@gmail.com",
role = c("aut", "cre")),
person("Victor", "Lui",
role = c("aut")),
person("Pratyaydipta", "Rudra",
role = c("aut")),
person("Souvik", "Seal",
role = c("aut")),
person("Thao", "Vu",
role = c("aut")),
person("Elena", "Hsieh",
role = c("aut")),
person("Debashis", "Ghosh",
role = c("aut", "cph")))
Imports: Rcpp, SummarizedExperiment, utils,
methods, ComplexHeatmap, circlize,
ashr, data.table, BiocParallel, dplyr,
stats, magrittr, rlang, S4Vectors
LinkingTo: Rcpp
Depends: R (>= 4.1)
Suggests:
knitr,
rmarkdown,
BiocStyle,
testthat
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-3
Description: cytoKernel implements a kernel-based score test to
identify differentially expressed features
in high-dimensional biological experiments. This
approach can be applied across many different
high-dimensional biological data including gene
expression data and dimensionally reduced
cytometry-based marker expression data.
In this R package,
we implement functions that compute the
feature-wise p values and their corresponding
adjusted p values. Additionally, it also computes
the feature-wise shrunk effect sizes and
their corresponding shrunken effect size.
Further, it calculates the percent of
differentially expressed features and plots
user-friendly heatmap of the top differentially
expressed features on the rows and samples on the
columns.
biocViews: ImmunoOncology, Proteomics, SingleCell, Software,
OneChannel, FlowCytometry, DifferentialExpression,
GeneExpression, Clustering
BugReports: https://github.com/Ghoshlab/cytoKernel/issues
RoxygenNote: 7.1.2
vjcitn
tghosh30
lshep
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