Removal of batch effects from longitudinal studies

Journal of Applied & Computational Mathematics

ISSN: 2168-9679

Open Access

Removal of batch effects from longitudinal studies

4th International Conference and Exhibition on Biometrics & Biostatistics

November 16-18, 2015 San Antonio, USA

Marco Giordan

Edmund Mach Foundation, Italy

Posters-Accepted Abstracts: J Appl Computat Math

Abstract :

Biological data are very often produced in different non-comparable batches. For data with repeated measurements and for longitudinal data, the correlated nature of the samples must also be considered in the procedure for the removal of the batch effects. Current literature on the removal of batch effects, however, is mainly concerned with the analysis of experiments having an independent sampling of the subjects. We have developed a procedure based on a linear mixed model to remove the batch effects from correlated data. Our procedure provides a filtered data set that can be used for further analyses.

Biography :

Marco Giordan has completed his PhD in Statistics in 2007 from Padua University and then worked as Biostatistician in different research institutes. Actually, he is a Researcher in the group of Biostatistics and Data Management at Edmund Mach Foundation, an institute promoting research in Agriculture.


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