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DESCRIPTION
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Package: POMA
Title: Tools for Omics Data Analysis
Version: 1.17.6
Authors@R:
c(person(given = "Pol",
family = "Castellano-Escuder",
role = c("aut", "cre"),
email = "[email protected]",
comment = c(ORCID = "0000-0001-6466-877X"))
)
Description:
The POMA package offers a comprehensive toolkit designed for omics data analysis,
streamlining the process from initial visualization to final statistical analysis.
Its primary goal is to simplify and unify the various steps involved in omics data
processing, making it more accessible and manageable within a single, intuitive R package.
Emphasizing on reproducibility and user-friendliness, POMA leverages the standardized
SummarizedExperiment class from Bioconductor, ensuring seamless integration and compatibility
with a wide array of Bioconductor tools. This approach guarantees maximum flexibility and
replicability, making POMA an essential asset for researchers handling omics datasets.
See https://github.com/pcastellanoescuder/POMAShiny. Paper: Castellano-Escuder
et al. (2021) <doi:10.1371/journal.pcbi.1009148> for more details.
License: GPL-3
Encoding: UTF-8
LazyData: true
biocViews:
BatchEffect,
Classification,
Clustering,
DecisionTree,
DimensionReduction,
MultidimensionalScaling,
Normalization,
Preprocessing,
PrincipalComponent,
Regression,
RNASeq,
Software,
StatisticalMethod,
Visualization
Imports:
broom,
caret,
ComplexHeatmap,
dbscan,
dplyr,
DESeq2,
fgsea,
FSA,
ggcorrplot,
ggplot2,
ggrepel,
glmnet,
grid,
impute,
janitor,
limma,
lme4,
magrittr,
MASS,
mixOmics,
multcomp,
msigdbr,
purrr,
randomForest,
RankProd (>= 3.14),
rlang,
SummarizedExperiment,
sva,
tibble,
tidyr,
utils,
uwot,
vegan
Suggests:
BiocStyle,
covr,
ggraph,
ggtext,
knitr,
patchwork,
plotly,
tidyverse,
testthat (>= 2.3.2)
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends: R (>= 4.0)
VignetteBuilder: knitr
URL: https://github.com/pcastellanoescuder/POMA
BugReports: https://github.com/pcastellanoescuder/POMA/issues