Package: LipidTrend 1.3.0

Wei-Chung Cheng

LipidTrend: LipidTrend: Analysis and Visualization of Lipid Feature Tendencies

"LipidTrend" is an R package that implements a permutation-based statistical test to identify significant differences in lipidomic features between groups. The test incorporates Gaussian kernel smoothing of region statistics to improve stability and accuracy, particularly when dealing with small sample sizes. This package also includes two plotting functions for visualizing significant tendencies in 1D and 2D feature data, respectively.

Authors:Wei-Chung Cheng [aut, cre, cph], Chia-Hsin Liu [aut, ctb], Pei-Chun Shen [aut, ctb], Wen-Jen Lin [aut, ctb], Hung-Ching Chang [aut, ctb], Meng-Hsin Tsai [aut, ctb]

LipidTrend_1.3.0.tar.gz
LipidTrend_1.3.0.zip(r-4.7)LipidTrend_1.3.0.zip(r-4.6)LipidTrend_1.3.0.zip(r-4.5)
LipidTrend_1.3.0.tgz(r-4.6-any)LipidTrend_1.3.0.tgz(r-4.5-any)
LipidTrend_1.3.0.tar.gz(r-4.7-any)LipidTrend_1.3.0.tar.gz(r-4.6-any)
LipidTrend_1.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
LipidTrend/json (API)
NEWS

# Install 'LipidTrend' in R:
install.packages('LipidTrend', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bioinfomics/lipidtrend/issues

Datasets:
  • abundance_2D - Example lipid abundance data for two-dimensional LipidTrend analysis
  • abundance_CL - Example lipid abundance data for one-dimensional LipidTrend analysis
  • char_table_2D - Example lipid characteristics table for two-dimensional LipidTrend analysis
  • char_table_CL - Example lipid characteristics table for one-dimensional LipidTrend analysis
  • group_info - Example group information table for LipidTrend analysis
  • lipid_se_2D - Example Dataset for two-dimensional data
  • lipid_se_CL - Example Dataset for one-dimensional data

On BioConductor:LipidTrend-1.3.0(bioc 3.24)LipidTrend-1.2.0(bioc 3.23)

softwarelipidomicsstatisticalmethoddifferentialexpressionvisualization

4.64 score 29 scripts 172 downloads 7 exports 43 dependencies

Last updated from:c37d222e0f. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE184
linux-devel-x86_64OK331
source / vignettesOK260
linux-release-x86_64OK520
macos-release-arm64OK186
macos-oldrel-arm64OK181
windows-develOK222
windows-releaseOK257
windows-oldrelOK267
wasm-releaseOK131

Exports:analyzeLipidRegioneven_chain_resultodd_chain_resultplotRegion1DplotRegion2Dresultshow

Dependencies:abindBiobaseBiocGenericsclicpp11DelayedArraydplyrfarvergenericsGenomicRangesggnewscaleggplot2gluegtableIRangesisobandlabelinglatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmatrixTestspillarpkgconfigR6RColorBrewerrlangS4ArraysS4VectorsS7scalesSeqinfoSparseArraySummarizedExperimenttibbletidyselectutf8vctrsviridisLitewithrXVector

Analyzing Lipid Feature Tendencies with LipidTrend

Rendered fromLipidTrend.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2025-08-20
Started: 2025-02-25