|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|469110||698288||2016||6 صفحه PDF||سفارش دهید||دانلود کنید|
• Integrative approaches for the study of biological systems have gained popularity..
• There is lack of integrative simulation techniques to assess “systems-biology” methods.
• InterSIM bridges this gap by simulating complex interrelated genomic data.
• InterSIM allows researchers to evaluate and test new integrative methods.
• The software tool InterSIM is implemented in R and is freely available from CRAN.
Background and objectiveIntegrative approaches for the study of biological systems have gained popularity in the realm of statistical genomics. For example, The Cancer Genome Atlas (TCGA) has applied integrative clustering methodologies to various cancer types to determine molecular subtypes within a given cancer histology. In order to adequately compare integrative or “systems-biology”-type methods, realistic and related datasets are needed to assess the methods. This involves simulating multiple types of ‘omic data with realistic correlation between features of the same type (e.g., gene expression for genes in a pathway) and across data types (e.g., “gene silencing” involving DNA methylation and gene expression).MethodsWe present the software application tool InterSIM for simulating multiple interrelated data types with realistic intra- and inter-relationships based on the DNA methylation, mRNA gene expression, and protein expression from the TCGA ovarian cancer study.ResultsThe resulting simulated datasets can be used to assess and compare the operating characteristics of newly developed integrative bioinformatics methods to existing methods. Application of InterSIM is presented with an example of heatmaps of the simulated datasets.ConclusionsInterSIM allows researchers to evaluate and test new integrative methods with realistically simulated interrelated genomic datasets. The software tool InterSIM is implemented in R and is freely available from CRAN.
Journal: Computer Methods and Programs in Biomedicine - Volume 128, May 2016, Pages 69–74