Introduction | Installation | Data preparation | Abundance data | Lipid characteristic table | Group information table | Constructing SummarizedExperiment object | Initiate LipidTrend workflow | One-dimensional analysis | Analyze lipid region | Result visualization | Two-dimensional analysis | Helper Functions – enhancing result viewing | View Results | Interpreting the Result Table | Session info
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:
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✨
DESCRIPTION |NEWS
card.svg |card.png
LipidTrend/json (API)
| # 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
Last updated from:c37d222e0f. Checks:1 NOTE, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 184 | ||
| linux-devel-x86_64 | OK | 331 | ||
| source / vignettes | OK | 260 | ||
| linux-release-x86_64 | OK | 520 | ||
| macos-release-arm64 | OK | 186 | ||
| macos-oldrel-arm64 | OK | 181 | ||
| windows-devel | OK | 222 | ||
| windows-release | OK | 257 | ||
| windows-oldrel | OK | 267 | ||
| wasm-release | OK | 131 |
Exports:analyzeLipidRegioneven_chain_resultodd_chain_resultplotRegion1DplotRegion2Dresultshow
Dependencies:abindBiobaseBiocGenericsclicpp11DelayedArraydplyrfarvergenericsGenomicRangesggnewscaleggplot2gluegtableIRangesisobandlabelinglatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmatrixTestspillarpkgconfigR6RColorBrewerrlangS4ArraysS4VectorsS7scalesSeqinfoSparseArraySummarizedExperimenttibbletidyselectutf8vctrsviridisLitewithrXVector
