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Detecting periodic patterns in unevenly spaced gene expression time series using Lomb–Scargle periodograms
2005
Computer applications in the biosciences : CABIOS
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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
2006
2006 International Conference on Machine Learning and Cybernetics
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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
2007
BMC Bioinformatics
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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
2008
EURASIP Journal on Bioinformatics and Systems Biology
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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
2018
Scientific Reports
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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
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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
2009
EURASIP Journal on Bioinformatics and Systems Biology
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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
2009
EURASIP Journal on Bioinformatics and Systems Biology
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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
2012
ISRN Signal Processing
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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
2013
PLoS ONE
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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
2013
Advances in Bioinformatics
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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
2016
Scientific Reports
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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]
2016
bioRxiv
pre-print
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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
2021
PLoS Computational Biology
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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]
2020
bioRxiv
pre-print
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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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