IntLIM 2.0：识别依赖于离散或连续表型测量的多组学关系。
IntLIM 2.0: identifying multi-omic relationships dependent on discrete or continuous phenotypic measurements.
作者信息
Eicher Tara, Spencer Kyle D, Siddiqui Jalal K, Machiraju Raghu, Mathé Ewy A
机构信息
Division of Preclinical Innovation, National Center for Advancing Translational Sciences, NIH, Rockville, MD 20892, USA.
Department of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.
出版信息
Bioinform Adv. 2023 Feb 1;3(1):vbad009. doi: 10.1093/bioadv/vbad009. eCollection 2023.
MOTIVATION
IntLIM uncovers phenotype-dependent linear associations between two types of analytes (e.g. genes and metabolites) in a multi-omic dataset, which may reflect chemically or biologically relevant relationships.
RESULTS
The new IntLIM R package includes newly added support for generalized data types, covariate correction, continuous phenotypic measurements, model validation and unit testing. IntLIM analysis uncovered biologically relevant gene-metabolite associations in two separate datasets, and the run time is improved over baseline R functions by multiple orders of magnitude.
AVAILABILITY AND IMPLEMENTATION
IntLIM is available as an R package with a detailed vignette (https://github.com/ncats/IntLIM) and as an R Shiny app (see Supplementary Figs S1-S6) (https://intlim.ncats.io/).
SUPPLEMENTARY INFORMATION
Supplementary data are available at online.
动机
IntLIM在多组学数据集中揭示了两种类型分析物（如基因和代谢物）之间依赖表型的线性关联，这可能反映了化学或生物学上的相关关系。
结果
新的IntLIM R包包括对广义数据类型、协变量校正、连续表型测量、模型验证和单元测试的新支持。IntLIM分析在两个独立的数据集中发现了生物学上相关的基因-代谢物关联，并且运行时间比基线R函数提高了多个数量级。
可用性和实现方式
IntLIM作为一个带有详细 vignette 的R包（https://github.com/ncats/IntLIM）以及一个R Shiny应用程序（见补充图S1 - S6）（https://intlim.ncats.io/）提供。
补充信息
补充数据可在网上获取。
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