Detecting Periodic Genes from Irregularly Sampled Gene Expressions: A Comparison Study

Time series microarray measurements of gene expressions have been exploited to discover genes involved in cell cycles. Due to experimental constraints, most microarray observations are obtained through irregular sampling. In this paper three popular spectral analysis schemes, namely, Lomb-Scargle, C...

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Detalles Bibliográficos
Autores principales: Zhao, Wentao, Agyepong, Kwadwo, Serpedin, Erchin, Dougherty, Edward R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2008
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171399/
https://www.ncbi.nlm.nih.gov/pubmed/18584052
http://dx.doi.org/10.1155/2008/769293
Descripción
Sumario:Time series microarray measurements of gene expressions have been exploited to discover genes involved in cell cycles. Due to experimental constraints, most microarray observations are obtained through irregular sampling. In this paper three popular spectral analysis schemes, namely, Lomb-Scargle, Capon and missing-data amplitude and phase estimation (MAPES), are compared in terms of their ability and efficiency to recover periodically expressed genes. Based on in silico experiments for microarray measurements of Saccharomyces cerevisiae, Lomb-Scargle is found to be the most efficacious scheme. 149 genes are then identified to be periodically expressed in the Drosophila melanogaster data set.

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