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Detecting periodic patterns in unevenly spaced gene expression time series using Lomb–Scargle periodograms

Earl F. Glynn, Jie Chen, Arcady R. Mushegian
2005 Computer applications in the biosciences : CABIOS  
Our approach should be applicable for detection and quantification of periodic patterns in any unevenly spaced gene expression time-series data.  ...  Methods: The Lomb-Scargle periodogram approach is used to search time series of gene expression to quantify the periodic behavior of every gene represented on the DNA array.  ...  In this paper, we propose to use the Lomb-Scargle periodogram to search for periodic patterns in unevenly spaced time series that represent gene expression profiles.  ... 
doi:10.1093/bioinformatics/bti789 pmid:16303799 fatcat:cydidewta5ezliz6zjk67dw5i4

A New Spectrum Estimation Method in Unevenly Sampling Space

Jun Xian, Shuan-hu Wu, Alan Liew, David Smith, Hong Yan
2006 2006 International Conference on Machine Learning and Cybernetics  
Spectrum estimation is a popular method for identifying periodically expressed genes in microarray time series analysis.  ...  The test on simulated noisy signal and typical periodically expressed gene data shows our algorithm is accurate compared with Lomb-Scargle algorithm.  ...  Ruf is one of the first to treat evenly sampled gene expression time series with missing values as unevenly sampled data for spectral analysis using the Lomb-Scargle periodogram [6] .  ... 
doi:10.1109/icmlc.2006.259011 fatcat:3ikwibgf3rfmrcpwbs5znmtf6u

Spectral estimation in unevenly sampled space of periodically expressed microarray time series data

Alan Liew, Jun Xian, Shuanhu Wu, David Smith, Hong Yan
2007 BMC Bioinformatics  
Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically expressed.  ...  Most methods used in the literature operate on evenly sampled time series and are not suitable for unevenly sampled time series.  ...  Glynn et al. [15] also used the Lomb-Scargle periodogram to detect periodic patterns in unevenly spaced gene expression time series.  ... 
doi:10.1186/1471-2105-8-137 pmid:17451610 pmcid:PMC1867827 fatcat:grqbju4o4bgljczz3achssou2a

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

Wentao Zhao, Kwadwo Agyepong, Erchin Serpedin, Edward R. Dougherty
2008 EURASIP Journal on Bioinformatics and Systems Biology  
Time series microarray measurements of gene expressions have been exploited to discover genes involved in cell cycles.  ...  periodically expressed genes.  ...  Given N time-series observations (t l , y l ), l = 0, . . . , N − 1, where t stands for the time tag and y denotes the sampled expression of a specific gene, the normalized Lomb-Scargle periodogram for  ... 
doi:10.1155/2008/769293 pmid:18584052 pmcid:PMC3171399 fatcat:ihc3yjceu5etvfa6t4kneyw3ey

On detection of periodicity in C-reactive protein (CRP) levels

Mohsen Dorraki, Anahita Fouladzadeh, Stephen J. Salamon, Andrew Allison, Brendon J. Coventry, Derek Abbott
2018 Scientific Reports  
The search for patterns (periodic or otherwise) in the CRP time-series is of interest for providing a cue for the optimal times at which cancer therapies are best administered.  ...  The analysis we provide may be used for establishing periodicity in any short time-series signal that is observed without a priori information.  ...  Moreover, the combination of a Scargle test statistic and a multiple hypothesis testing procedure is suggested to detect significant periodic gene expression patterns 40 .  ... 
doi:10.1038/s41598-018-30469-8 pmid:30097610 pmcid:PMC6086826 fatcat:e6qs75zgp5ar3oxzw4vblczqfu

Page 822 of Genetics Vol. 180, Issue 2 [page]

2008 Genetics  
GLYNN et al. (2006) proposed a Lomb-Scargle periodogram approach based on the fast Fourier transform to model unevenly spaced gene-expression time series and then characterize periodic patterns of gene  ...  This multivariate normal mixture model is employed to detect different patterns in gene-expression profiles. Assume that n genes are measured at multiple time points.  ... 

Identifying Genes Involved in Cyclic Processes by Combining Gene Expression Analysis and Prior Knowledge

Wentao Zhao, Erchin Serpedin, Edward R Dougherty
2009 EURASIP Journal on Bioinformatics and Systems Biology  
Based on time series gene expressions, cyclic genes can be recognized via spectral analysis and statistical periodicity detection tests.  ...  The power of a scheme is practically measured by comparing the detected periodically expressed genes with experimentally verified genes participating in a cyclic process.  ...  Given m time-series observations (t l , x l ), l = 0, . . . , m − 1, where t stands for the time tag, and x denotes the sampled expression of a specific gene, the normalized Lomb-Scargle periodogram at  ... 
doi:10.1155/2009/683463 pmid:19390635 pmcid:PMC3171438 fatcat:qeqto4vh5je3flequm4n5s5kwe

Spectral Preprocessing for Clustering Time-Series Gene Expressions

Wentao Zhao, Erchin Serpedin, Edward R. Dougherty
2009 EURASIP Journal on Bioinformatics and Systems Biology  
This paper proposes a novel clustering preprocessing strategy which combines clustering with spectral estimation techniques so that the time information present in time series gene expressions is fully  ...  The proposed technique is especially helpful in grouping genes participating in time-regulated processes.  ...  Methods This section explains how to apply the Lomb-Scargle periodogram to time-series gene expressions.  ... 
doi:10.1155/2009/713248 pmid:19381338 pmcid:PMC3171439 fatcat:6gqhsmxy4ff65iwww4cspafwv4

Observability of Spectral Components beyond Nyquist Limit in Nonuniformly Sampled Signals

Jozef Púčik, Oldřich Ondráček, Elena Cocherová
2012 ISRN Signal Processing  
The derived relation is illustrated by Lomb-Scargle periodograms applied on simulated data.  ...  In this paper, we provide a theoretical analysis of the aliased components reduction in the nonparametric periodogram for two sampling schemes: the random sampling pattern and the sampling pattern generated  ...  sampled QRS maxima, (c) the Lomb-Scargle periodogram of unevenly sampled QRS maxima.  ... 
doi:10.5402/2012/643563 fatcat:3ws4uano6fd3xfygedunudaj5q

Network Theory Inspired Analysis of Time-Resolved Expression Data Reveals Key Players Guiding P. patens Stem Cell Development

Hauke Busch, Melanie Boerries, Jie Bao, Sebastian T. Hanke, Manuel Hiss, Theodhor Tiko, Stefan A. Rensing, Panayiotis V. Benos
2013 PLoS ONE  
Here we present a method that allows to determine such genes based on trajectory analysis of time-resolved transcriptome data.  ...  Transcription factors (TFs) often trigger developmental decisions, yet, their transcripts are often only moderately regulated and thus not easily detected by conventional statistics on expression data.  ...  The Lomb -Scargle periodogram approach can quantify the periodic behavior of the gene expression time series for every gene.  ... 
doi:10.1371/journal.pone.0060494 pmid:23637751 pmcid:PMC3630159 fatcat:xefjasriabgvrfo3ogicoyrro4

Spectral Analysis on Time-Course Expression Data: Detecting Periodic Genes Using a Real-Valued Iterative Adaptive Approach

Kwadwo S. Agyepong, Fang-Han Hsu, Edward R. Dougherty, Erchin Serpedin
2013 Advances in Bioinformatics  
Time-course expression profiles and methods for spectrum analysis have been applied for detecting transcriptional periodicities, which are valuable patterns to unravel genes associated with cell cycle  ...  The inferred spectrum is then analyzed using Fisher's hypothesis test. With a proper -value threshold, periodic genes can be detected.  ...  Acknowledgments The authors would like to thank the members in the Genomic Signal Processing Laboratory, Texas A&M University, for the helpful discussions and valuable feedback.  ... 
doi:10.1155/2013/171530 pmid:23533399 pmcid:PMC3600260 fatcat:ifsl6vjooffo5hl3sssab2xfca

MathIOmica: An Integrative Platform for Dynamic Omics

George I. Mias, Tahir Yusufaly, Raeuf Roushangar, Lavida R. K. Brooks, Vikas V. Singh, Christina Christou
2016 Scientific Reports  
The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics.  ...  We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science  ...  simulation and are provided by the user: (i) Classification based on a Lomb-Scargle periodogram, classifying data into classes for time-series showing the same dominant frequency in their spectra; Classification  ... 
doi:10.1038/srep37237 pmid:27883025 pmcid:PMC5121649 fatcat:rx5ul3obonhovjw3svx74bx3ba

MathIOmica: An Integrative Platform for Dynamic Omics [article]

George Mias, Tahir Yusufaly, Raeuf Roushangar, Lavida R.K. Brooks, Vikas Vikram Singh, Christina Christou
2016 bioRxiv   pre-print
The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics.  ...  We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science  ...  simulation and are provided by the user: (i) Classification based on a Lomb-Scargle periodogram, classifying data into classes for time-series showing the same dominant frequency in their spectra; Classification  ... 
doi:10.1101/074260 fatcat:slojm6onfrazrefed5t5ykevpa

The risks of using the chi-square periodogram to estimate the period of biological rhythms

Michael C. Tackenberg, Jacob J. Hughey, Ulrik R. Beierholm
2021 PLoS Computational Biology  
Nonetheless, even the greedy CSP tended to be less accurate on our simulated time-courses than an alternative method, namely the Lomb-Scargle periodogram.  ...  We traced the source of the bias to discontinuities in the periodogram that are related to the number of time-points the CSP uses to calculate the observed variance for a given test period.  ...  Acknowledgments We thank Allison Leich-Hilbun for input on the revised calculations for the chi-square periodogram.  ... 
doi:10.1371/journal.pcbi.1008567 pmid:33406069 fatcat:5bkmyqtsa5emvbb2yggp6a23r4

The risks of using the chi-square periodogram to estimate the period of biological rhythms [article]

Michael C Tackenberg, Jacob J Hughey
2020 bioRxiv   pre-print
Nonetheless, even the greedy CSP tended to be less accurate on our simulated time-courses than an alternative method, namely the Lomb-Scargle periodogram.  ...  The bias is caused by discontinuities in the periodogram that are related to the number of time-points the CSP uses to calculate the observed variance for a given test period.  ...  Acknowledgments We thank Allison Leich-Hilbun for input on the revised calculations for the chi-square periodogram.  ... 
doi:10.1101/2020.08.14.251512 fatcat:chbr4cujprc77dun3ov4te6wsu
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