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DESCRIPTION
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DESCRIPTION
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Package: dce
Type: Package
Title: Pathway Enrichment Based on Differential Causal Effects
Version: 1.3.5
Authors@R:
c(
person(
given = "Kim Philipp", family = "Jablonski",
role = c("aut", "cre"),
email = "kim.philipp.jablonski@gmail.com",
comment = c(ORCID = "0000-0002-4166-4343")
),
person(
given = "Martin", family = "Pirkl",
role = c("aut"),
email = "martinpirkl@yahoo.de"
)
)
Description: Compute differential causal effects (dce) on (biological) networks.
Given observational samples from a control experiment and non-control (e.g., cancer) for two genes A and B, we can compute differential causal effects with a (generalized) linear regression.
If the causal effect of gene A on gene B in the control samples is different from the causal effect in the non-control samples the dce will differ from zero.
We regularize the dce computation by the inclusion of prior network information from pathway databases such as KEGG.
URL: https://github.com/cbg-ethz/dce
BugReports: https://github.com/cbg-ethz/dce/issues
biocViews:
Software,
StatisticalMethod,
GraphAndNetwork,
Regression,
GeneExpression,
DifferentialExpression,
NetworkEnrichment,
Network,
KEGG
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends:
R (>= 4.1)
Suggests:
knitr,
rmarkdown,
testthat (>= 2.1.0),
BiocStyle,
formatR,
cowplot,
ggplotify,
dagitty,
lmtest,
sandwich,
devtools,
curatedTCGAData,
TCGAutils,
SummarizedExperiment,
RcppParallel,
docopt,
CARNIVAL
VignetteBuilder: knitr
RoxygenNote: 7.1.2
Imports:
stats,
methods,
assertthat,
graph,
pcalg,
purrr,
tidyverse,
Matrix,
ggraph,
tidygraph,
ggplot2,
rlang,
expm,
MASS,
edgeR,
epiNEM,
igraph,
metap,
mnem,
naturalsort,
ppcor,
glm2,
graphite,
reshape2,
dplyr,
magrittr,
glue,
Rgraphviz,
harmonicmeanp,
org.Hs.eg.db,
logger,
shadowtext