TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists
| Autor: | Shili Lin, Michael G. Schimek, Vendula Svendova, Jie Ding, Karl G. Kugler, Eva Budinská |
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| Rok vydání: | 2015 |
| Předmět: |
Statistics and Probability
Models Statistical business.industry Computer science Gene Expression Profiling Computational Biology Genomics computer.software_genre Visualization Set (abstract data type) MicroRNAs Computational Mathematics Software 62g99 65k10 68n01 65c60 62f07 Genetics Statistical inference Data mining Differential (infinitesimal) business Raw data Molecular Biology License computer Graphical user interface |
| Zdroj: | Stat. Appl. Genet. Mol. Biol. 14, 311-316 (2015) |
| ISSN: | 1544-6115 2194-6302 |
| Popis: | High-throughput sequencing techniques are increasingly affordable and produce massive amounts of data. Together with other high-throughput technologies, such as microarrays, there are an enormous amount of resources in databases. The collection of these valuable data has been routine for more than a decade. Despite different technologies, many experiments share the same goal. For instance, the aims of RNA-seq studies often coincide with those of differential gene expression experiments based on microarrays. As such, it would be logical to utilize all available data. However, there is a lack of biostatistical tools for the integration of results obtained from different technologies. Although diverse technological platforms produce different raw data, one commonality for experiments with the same goal is that all the outcomes can be transformed into a platform-independent data format - rankings - for the same set of items. Here we present the R package TopKLists, which allows for statistical inference on the lengths of informative (top-k) partial lists, for stochastic aggregation of full or partial lists, and for graphical exploration of the input and consolidated output. A graphical user interface has also been implemented for providing access to the underlying algorithms. To illustrate the applicability and usefulness of the package, we integrated microRNA data of non-small cell lung cancer across different measurement techniques and draw conclusions. The package can be obtained from CRAN under a LGPL-3 license. |
| Databáze: | OpenAIRE |
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