IntLIM: Integration of Omics Data Using Linear Modeling

This workflow takes analyte levels from two different types of analytes (e.g. gene expression and metabolite abundance), meta-information on each analyte type, and sample outcome and metadata to identify analyte pairs that are significantly associated with a continuous or discrete outcome (e.g. drug response or tumor type). The following references describe the methods in this package: (1) Jalal K. Siddiqui, et al. (2018) <doi:10.1186/s12859-018-2085-6>, (2) Andrew Patt, et al. (2019) <doi:10.1007/978-1-4939-9027-6_23>.

Version: 2.0.2
Depends: R (≥ 3.2.0)
Imports: ComplexHeatmap, DT, ggplot2, graphics, grDevices, heatmaply, highcharter, htmltools, KernSmooth, margins, methods, MASS, RColorBrewer, reshape2, rmarkdown, shiny, shinydashboard, shinyFiles, shinyjs, stats, testthat, utils
Suggests: knitr
Published: 2022-08-22
Author: Jalal Siddiqui [aut], Shunchao Wang [aut], Rohith Vanam [aut], Elizabeth Baskin [aut], Tara Eicher [aut, cre], Kyle Spencer [aut], Ewy Mathe [aut]
Maintainer: Tara Eicher <tara.eicher at>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: IntLIM results


Reference manual: IntLIM.pdf
Vignettes: IntLIM: Integration through Linear Modeling


Package source: IntLIM_2.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): IntLIM_2.0.2.tgz, r-oldrel (arm64): IntLIM_2.0.2.tgz, r-release (x86_64): IntLIM_2.0.2.tgz, r-oldrel (x86_64): IntLIM_2.0.2.tgz


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