scholarly journals Example of Methylome Analysis with MethylIT using Cancer Datasets

2018 ◽  
Author(s):  
Robersy Sanchez ◽  
Sally Mackenzie
Keyword(s):  
Signal Detection ◽  
Background Noise ◽  
Thermal Fluctuations ◽  
Analysis Procedure ◽  
Methylation Analysis ◽  
Detection Problem ◽  
Gene Pathway ◽  
Genome Methylation ◽  
Regulatory Signal ◽  
Methylome Analysis

AbstractMethyl-IT, a novel methylome analysis procedure based on information thermodynamics and signal detection was recently released. Methylation analysis involves a signal detection problem, and the method was designed to discriminate methylation regulatory signal from background noise induced by thermal fluctuations. Methyl-IT enhances the resolution of genome methylation behavior to reveal network-associated responses, offering resolution of gene pathway influences not attainable with previous methods. Herein, an example of MethylIT application to the analysis of breast cancer methylomes is presented.

scholarly journals Enhancing resolution of natural methylome reprogramming behavior in plants

2018 ◽  
Author(s):  
Robersy Sanchez ◽  
Xiaodong Yang ◽  
Jose R Barreras ◽  
Hardik Kundariya ◽  
Sally A. Mackenzie
Keyword(s):  
Signal Detection ◽  
Thermal Fluctuation ◽  
Methylation Analysis ◽  
Dynamic Background ◽  
Discrimination Power ◽  
Stress Effects ◽  
Enhanced Resolution ◽  
Differentially Methylated Genes ◽  
Methylome Analysis ◽  
Hellinger Divergence

AbstractBackgroundNatural methylome reprogramming within chromatin involves changes in local energy landscapes that are subject to thermodynamic principles. Signal detection permits the discrimination of methylation signal from dynamic background noise that is induced by thermal fluctuation. Current genome-wide methylation analysis methods do not incorporate biophysical properties of DNA, and focus largely on DNA methylation density changes, which limits resolution of natural, more subtle methylome behavior in relation to gene activity.ResultsWe present here a novel methylome analysis procedure, Methyl-IT, based on information thermodynamics and signal detection. Methylation analysis involves a signal detection step, and the method was designed to discriminate methylation regulatory signal from background variation. Comparisons with commonly used programs and two publicly available methylome datasets, involving stages of seed development and drought stress effects, were implemented. Information divergence between methylation levels from different groups, measured in terms of Hellinger divergence, provides discrimination power between control and treatment samples. Differentially informative methylation positions (DIMPs) achieved higher sensitivity and accuracy than standard differentially methylated positions (DMPs) identified by other methods. Differentially methylated genes (DMG) that are based on DIMPs were significantly enriched in biologically meaningful networks.ConclusionsMethyl-IT analysis enhanced resolution of natural methylome reprogramming behavior to reveal network-associated responses, offering resolution of gene pathway influences not attainable with previous methods.

scholarly journals Space Lower Bounds for the Signal Detection Problem

2020 ◽  
Author(s):  
Faith Ellen ◽  
Rati Gelashvili ◽  
Philipp Woelfel ◽  
Leqi Zhu
Keyword(s):  
Signal Detection ◽  
Lower Bounds ◽  
Detection Problem

SIGNAL DETECTION ENHANCED BY COMODULATED NOISE

2006 ◽  
Vol 06 (04) ◽  
pp. L339-L347 ◽  
Author(s):  
MICHAEL BUSCHERMÖHLE ◽  
ULRIKE FEUDEL ◽  
GEORG M. KLUMP ◽  
MARK A. BEE ◽  
JAN A. FREUND
Keyword(s):  
Signal Detection ◽  
Auditory System ◽  
Background Noise ◽  
Frequency Resolution ◽  
General Phenomenon ◽  
Detection Scheme ◽  
Hearing Research ◽  
Limited Frequency ◽  
Detection Of Signals ◽  
Comodulated Noise

Signal detection in fluctuating background noise is a common problem in diverse fields of research and technology. It has been shown in hearing research that the detection of signals in noise that is correlated in amplitude across the frequency spectrum (comodulated) can be improved compared to uncorrelated background noise. We show that the mechanism leading to this effect is a general phenomenon which may be utilized in other areas where signal detection in comodulated noise needs to be done with a limited frequency resolution. Our model is based on neurophysiological experiments. The proposed signal detection scheme evaluates a fluctuating envelope, the statistics of which depend on the correlation structure across the spectrum of the noise. In our model, signal detection does not require a sophisticated neuronal network but can be accomplished through the encoding of the compressed stimulus envelope in the firing rate of neurons in the auditory system.

Vibrational risk assessment as a signal detection problem: Escape hatching of red‐eyed treefrog eggs

2007 ◽  
Vol 121 (5) ◽  
pp. 3080-3080
Author(s):  
Karen M. Warkentin ◽  
Michael S. Caldwell ◽  
J. Gregory McDaniel
Keyword(s):  
Risk Assessment ◽  
Signal Detection ◽  
Detection Problem

scholarly journals Hypothesis Testing for Signal Detection Problem and Large Deviations

2001 ◽  
Vol 162 ◽  
pp. 187-203 ◽  
Author(s):  
Taizo Chiyonobu
Keyword(s):  
Signal Detection ◽  
Continuous Time ◽  
Error Probability ◽  
Diffusion Processes ◽  
Large Deviation ◽  
Observation Time ◽  
Optimal Decision ◽  
Detection Problem ◽  
Stationary Diffusion ◽  
Decision Region

We consider a signal detection problem for the continuous-time stationary diffusion processes. The optimal decision region is given by Neyman-Pearson’s lemma. We establish certain large deviation estimates, and with the help of it we show that the error probability of the second kind of the signal detection tends to zero or one exponentially fast, depending on the fixed exponent of the decay of the error probability of the first kind, as the observation time goes to infinity.

scholarly journals Whole-genome methylation analysis of benign and malignant colorectal tumours.J Pathol2013; 229: 697-704

2013 ◽  
Vol 231 (4) ◽  
pp. 543-543
Author(s):  
Andrew D Beggs ◽  
Angela Jones ◽  
Mona El-Bahrawy ◽  
Muti Abuladfi ◽  
Shirley V Hodgson ◽  
...  
Keyword(s):  
Whole Genome ◽  
Methylation Analysis ◽  
Genome Methylation

scholarly journals Epigenetic Impact of Long-Term Shiftwork: Pilot Evidence From Circadian Genes and Whole-Genome Methylation Analysis

2011 ◽  
Vol 28 (10) ◽  
pp. 852-861 ◽  
Author(s):  
Yong Zhu ◽  
Richard G. Stevens ◽  
Aaron E. Hoffman ◽  
Anne Tjonneland ◽  
Ulla B. Vogel ◽  
...  
Keyword(s):  
Whole Genome ◽  
Methylation Analysis ◽  
Circadian Genes ◽  
Genome Methylation
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