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@article{1305886,
author = {Schimek, Michael G. and Budinská, Eva and Kugler, Karl G. and Švendová, Vendula and Ding, Jie and Lin, Shili},
article_location = {BERLIN},
article_number = {3},
doi = {http://dx.doi.org/10.1515/sagmb-2014-0093},
keywords = {62G99; 65K10; 68N01; 65C60; 62F07},
language = {eng},
issn = {2194-6302},
journal = {STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY},
title = {TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists},
volume = {14},
year = {2015}
}
TY - JOUR
ID - 1305886
AU - Schimek, Michael G. - Budinská, Eva - Kugler, Karl G. - Švendová, Vendula - Ding, Jie - Lin, Shili
PY - 2015
TI - TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists
JF - STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY
VL - 14
IS - 3
SP - 311-316
EP - 311-316
PB - WALTER DE GRUYTER GMBH
SN - 21946302
KW - 62G99
KW - 65K10
KW - 68N01
KW - 65C60
KW - 62F07
N2 - 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.
ER -
SCHIMEK, Michael G., Eva BUDINSKÁ, Karl G. KUGLER, Vendula ŠVENDOVÁ, Jie DING a Shili LIN. TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists. \textit{STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY}. BERLIN: WALTER DE GRUYTER GMBH, 2015, roč.~14, č.~3, s.~311-316. ISSN~2194-6302. Dostupné z: https://dx.doi.org/10.1515/sagmb-2014-0093.
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