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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>.
Getting started
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Package details |
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| 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@nih.gov> |
| License | GPL-2 |
| Version | 2.0.2 |
| Package repository | View on CRAN |
| Installation |
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