Addressing Technical Replicate Variance in Omics Data Analysis

Glaab, Enrico; Schneider, Reinhard

Reference : Addressing Technical Replicate Variance in Omics Data Analysis


	Document type :	Scientific congresses, symposiums and conference proceedings : Poster
	Discipline(s) :	Life sciences : Biotechnology Human health sciences : Multidisciplinary, general & others
	To cite this reference:	http://hdl.handle.net/10993/20115

Title :	Addressing Technical Replicate Variance in Omics Data Analysis
Language :	English
Author, co-author :	Glaab, Enrico [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Schneider, Reinhard [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Publication date :	2014
Number of pages :	A0
Peer reviewed :	Yes
Audience :	International
Event name :	Benelux Bioinformatics Conference 2014
Event date :	from 08-12-2014 to 09-12-2014
Keywords :	[en] omics ; proteomics ; transcriptomics ; technical replicates ; statistical analysis ; microarray ; differential analysis ; visualization ; principal component analysis
Abstract :	[en] High-throughput omics datasets often contain technical replicates, included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses. We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ranking tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. The web-based software is freely available at http://www.repexplore.tk.
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/20115
Other URL :	http://www.repexplore.tk

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Open access	repexplore_poster.pdf		Publisher postprint	972.07 kB	View/Open

All documents in ORBi^lu are protected by a user license.

University of Luxembourg Library | Feedback | Legal notices