Time-series alignment by non-negative multiple generalized canonical correlation analysis
Open access
Datum
2007Typ
- Conference Paper
ETH Bibliographie
yes
Altmetrics
Abstract
Background
Quantitative analysis of differential protein expressions requires to align temporal elution measurements from liquid chromatography coupled to mass spectrometry (LC/MS). We propose multiple Canonical Correlation Analysis (mCCA) as a method to align the non-linearly distorted time scales of repeated LC/MS experiments in a robust way.
Results
Multiple canonical correlation analysis is able to map several time series to a consensus time scale. The alignment function is learned in a supervised fashion. We compare our approach with previously published methods for aligning mass spectrometry data on a large proteomics dataset. The proposed method significantly increases the number of proteins that are identified as being differentially expressed in different biological samples.
Conclusion
Jointly aligning multiple liquid chromatography/mass spectrometry samples by mCCA substantially increases the detection rate of potential bio-markers which significantly improves the interpretability of LC/MS data. Mehr anzeigen
Persistenter Link
https://doi.org/10.3929/ethz-b-000008245Publikationsstatus
publishedExterne Links
Zeitschrift / Serie
BMC BioinformaticsBand
Seiten / Artikelnummer
Verlag
BioMed CentralKonferenz
Thema
False discovery rate; Canonical correlation analysis; Ridge regression; Thin plate spline; Differential protein expressionOrganisationseinheit
03659 - Buhmann, Joachim M. (emeritus) / Buhmann, Joachim M. (emeritus)
ETH Bibliographie
yes
Altmetrics