Reference : RepExplore: Addressing technical replicate variance in proteomics and metabolomics da...
Scientific journals : Article
Life sciences : Biotechnology
Life sciences : Multidisciplinary, general & others
Human health sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/20114
RepExplore: Addressing technical replicate variance in proteomics and metabolomics data analysis
English
Glaab, Enrico mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Schneider, Reinhard mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
2015
Bioinformatics
31
13
2235
Yes
International
[en] technical replicates ; proteomics ; metabolomics ; differential analysis ; PCA ; visualization ; statistical analysis ; web-application ; mass spectrometry
[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 ran- king tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) ; Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group)
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/20114
10.1093/bioinformatics/btv127
http://bioinformatics.oxfordjournals.org/content/31/13/2235.long

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