Document Detail


Comparison of methods for identifying periodically varying genes.
MedLine Citation:
PMID:  23207998     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Several methods have been reported for identifying periodically varying genes from gene expression datasets. We compare the performance of five existing methods and a combination of G-statistic and autocovariance (called GVAR) using simulated sine-function-based and cell-cycle-based datasets. Based on this analysis we recommend appropriate methods for different experimental situations (length of the time series, sampling interval and noise level). No single method performs the best under all tested conditions. None of the evaluated methods perform well at high noise levels for short time series data. At lower noise levels, GVAR performed the best.
Authors:
Vinaya Vijayan; Prachi Deshpande; Chetan Gadgil; Mugdha Gadgil
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  International journal of bioinformatics research and applications     Volume:  9     ISSN:  1744-5485     ISO Abbreviation:  Int J Bioinform Res Appl     Publication Date:  2013  
Date Detail:
Created Date:  2012-12-04     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101253758     Medline TA:  Int J Bioinform Res Appl     Country:  Switzerland    
Other Details:
Languages:  eng     Pagination:  53-70     Citation Subset:  IM    
Affiliation:
Chemical Engineering and Process Development, National Chemical Laboratory, CSIR, Pune 411008, India.
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