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Related Concept Videos

Introduction to Test of Independence01:21

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In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
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The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
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While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.
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Related Experiment Video

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Direct Pressure Monitoring Accurately Predicts Pulmonary Vein Occlusion During Cryoballoon Ablation
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PrimerROC: accurate condition-independent dimer prediction using ROC analysis.

Andrew D Johnston1,2, Jennifer Lu1,2, Ke-Lin Ru1,2

  • 1Centre for Personalized NanoMedicine, The University of Queensland, St Lucia, 4072, QLD, Australia.

Scientific Reports
|January 20, 2019
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Summary

PrimerROC, a novel tool, accurately predicts primer-dimer formation in PCR using Receiver Operating Characteristic (ROC) curves. This assay-independent method outperforms existing software, achieving over 92% predictive accuracy for reliable primer design.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Accurate prediction of primer-dimer formation is crucial for PCR success.
  • Existing primer-dimer prediction tools lack standardized efficacy testing and comparison.
  • Measuring the predictive power of Gibbs free energy (ΔG) calculations for dimer formation is challenging.

Purpose of the Study:

  • To develop and validate a novel tool for assessing primer-dimer prediction accuracy.
  • To establish a reliable method for determining primer-dimer free thresholds.
  • To compare the performance of existing primer-dimer prediction software.

Main Methods:

  • Development of PrimerROC, an online tool utilizing Receiver Operating Characteristic (ROC) curves for accuracy assessment.
  • Integration of PrimerROC with PrimerDimer software to determine ΔG-based dimer-free thresholds.
  • Evaluation of seven public primer analysis tools using a dataset of over 300 primer pairs.

Main Results:

  • PrimerROC provides an assay and condition-independent prediction tool.
  • The PrimerROC/PrimerDimer software achieved predictive accuracies greater than 92%.
  • The method successfully designed multiplex PCR assays with up to 126 primers without amplification artifacts.

Conclusions:

  • PrimerROC offers a robust and accurate method for evaluating primer-dimer prediction software.
  • The developed software significantly outperforms existing tools in predicting dimer formation.
  • This approach enables reliable primer design for complex applications like multiplex PCR.