SCHIMEK, Michael G., Eva BUDINSKÁ, Karl G. KUGLER, Vendula ŠVENDOVÁ, Jie DING and Shili LIN. TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists. STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY. BERLIN: WALTER DE GRUYTER GMBH, 2015, vol. 14, No 3, p. 311-316. ISSN 2194-6302. Available from: https://dx.doi.org/10.1515/sagmb-2014-0093.
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Basic information
Original name TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists
Authors SCHIMEK, Michael G. (40 Austria), Eva BUDINSKÁ (703 Slovakia, guarantor, belonging to the institution), Karl G. KUGLER (276 Germany), Vendula ŠVENDOVÁ (203 Czech Republic), Jie DING (840 United States of America) and Shili LIN (840 United States of America).
Edition STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY, BERLIN, WALTER DE GRUYTER GMBH, 2015, 2194-6302.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10600 1.6 Biological sciences
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 1.265
RIV identification code RIV/00216224:14110/15:00083345
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.1515/sagmb-2014-0093
UT WoS 000355417300008
Keywords in English 62G99; 65K10; 68N01; 65C60; 62F07
Tags EL OK
Tags International impact, Reviewed
Changed by Changed by: Soňa Böhmová, učo 232884. Changed: 9/7/2015 14:21.
Abstract
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.
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