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Package: TCMDATA
Title: Traditional Chinese Medicine Data Analysis and Visualization
Version: 1.0.0
Authors@R: c(
person(given = "Nan", family = "He", email = "nanh302311@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0009-0008-6932-3867")),
person(given = "Guangchuang", family = "Yu", email = "guangchuangyu@gmail.com", role = c("aut", "ths"), comment = c(ORCID = "0000-0002-6485-8781")),
person(given = "Shuangbin", family = "Xu", email = "xshuangbin@163.com", role = "ctb", comment = c(ORCID = "0000-0003-3513-5362"))
)
Description: A comprehensive R package for Traditional Chinese Medicine (TCM)
network pharmacology research. Enables bidirectional queries of herb,
compound, and target databases; PubChem-based molecule annotation and
similarity search; pharmacological network construction with topological
analysis; herb-based enrichment analysis compatible with GO/KEGG; PPI
network analysis with 15+ centrality metrics and robustness evaluation;
machine learning-based biomarker screening (LASSO, Elastic Net, Random
Forest, SVM-RFE, XGBoost); LLM-powered result interpretation; and
publication-ready visualizations including Sankey diagrams, docking
heatmaps, and lollipop plots.
Depends:
R (>= 4.5.0)
Imports:
aplot,
clusterProfiler,
dplyr,
enrichplot,
ggfun,
ggplot2,
ggrepel,
ggtangle,
ggtree,
grDevices,
igraph,
jsonlite,
methods,
purrr,
rlang,
scales,
stats,
tibble,
tidyr,
utils,
yulab.utils
Suggests:
aplotExtra,
Matrix,
paletteer,
RColorBrewer,
aisdk (>= 1.5.0),
aisdk.providers (>= 0.1.0),
Boruta,
caret,
circlize,
ComplexHeatmap,
dotenv,
glmnet,
httr,
kernlab,
pROC,
randomForest,
xgboost,
xml2,
rcdk,
webchem,
knitr,
rmarkdown,
testthat (>= 3.0.0),
WGCNA,
ggalluvial,
ggvenn,
ggthemes,
AnnotationDbi,
org.Hs.eg.db,
shiny,
visNetwork
Remotes:
YuLab-SMU/aplotExtra,
YuLab-SMU/aisdk,
YuLab-SMU/aisdk.providers
License: Artistic-2.0
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
LazyData: true
LazyDataCompression: xz
Config/testthat/edition: 3