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Related Concept Videos

Deconvolution01:20

Deconvolution

221
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
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Uncertainty: Overview00:59

Uncertainty: Overview

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

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The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
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Estimation of the Physical Quantities01:05

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On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
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Uncertainty: Confidence Intervals00:54

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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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Updated: Aug 16, 2025

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
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Uncertainty quantification of reference-based cellular deconvolution algorithms.

Dorothea Seiler Vellame1, Gemma Shireby1, Ailsa MacCalman1

  • 1University of Exeter Medical School, University of Exeter, Exeter EX2 5DW, UK.

Epigenetics
|December 20, 2022
PubMed
Summary
This summary is machine-generated.

A new metric, CETYGO score, assesses cellular composition accuracy in DNA methylation studies. It identifies inaccurate deconvolution, crucial for reliable epigenetic epidemiology research.

Keywords:
DNA methylationIllumina EPIC arraycellular heterogeneityepigenetic epidemiologyillumina 450K array

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Area of Science:

  • Epigenetics
  • Computational Biology
  • Epidemiology

Background:

  • Epigenetic epidemiology studies often use bulk tissues, risking confounding from cellular composition variations.
  • Current methods for estimating cellular composition from bulk tissue lack validation for unknown true proportions.

Purpose of the Study:

  • To develop and validate a novel metric, the CETYGO score, for assessing the accuracy of cellular composition estimates in DNA methylation data.
  • To characterize factors influencing the accuracy of cellular deconvolution in whole blood samples.

Main Methods:

  • Developed the CETYGO score to quantify the deviation between a sample's DNA methylation profile and its expected profile based on estimated cell proportions.
  • Validated the CETYGO score using reconstructed whole blood profiles to identify inaccurate deconvolutions.
  • Applied the CETYGO score to over 6,300 empirical whole blood profiles.

Main Results:

  • The CETYGO score effectively distinguishes inaccurate and incomplete cellular deconvolution results.
  • Accuracy of cellular composition estimation in whole blood is influenced by technical and biological factors.
  • Less accurate deconvolution estimates were observed for females, neonates, older individuals, and smokers when using a common reference panel.

Conclusions:

  • The CETYGO score provides a reliable method to assess the accuracy of cellular deconvolution in epigenetic studies.
  • This metric enhances the reliability of DNA methylation studies relying on statistical proxies for cellular heterogeneity.
  • The CETYGO score is available as an R package to facilitate its integration into existing research pipelines.