RT info:eu-repo/semantics/conferenceObject
T1 Evaluation of microarray normalization strategies to detect cyclic circadian genes.
A1 Larriba González, Yolanda
A1 Rueda Sabater, María Cristina
A1 Fernández Temprano, Miguel Alejandro
A1 Peddada, Shyamal
AB Microarrays are a widely used research tool in gene expression analysis. A large varietyof preprocessing methods for raw intensity measures is available to establish gene expression values. Normalization is the key stage in preprocessing methods, sinceit removes systematic variations in microarray data. Then, the subsequent analysesmay be highly dependent on normalization strategy employed. Our research focuseson detecting rhythmic signals in measured circadian gene expressions. We have observedthat rhythmicity detection depends not only upon the rhythmicity detectionalgorithm but also upon the normalization strategy employed. We analyze the effectsof well-known normalization strategies in literature within three different rhythmicitydetection algorithms; JTK, RAIN and our recently proposal ORI, a novel statisticalmethodology based on Order Restricted Inference. The results obtained are comparedusing artificial microarray data and publicly available circadian data bases.
YR 2016
FD 2016
LK http://uvadoc.uva.es/handle/10324/22937
UL http://uvadoc.uva.es/handle/10324/22937
LA spa
DS UVaDOC
RD 27-nov-2024