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The Diels–Alder reaction brings together a diene and a dienophile to form a six-membered ring. Both components have unique characteristics that influence the rate of the reaction.
Characteristics of the diene
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Cycloadditions are one of the most valuable and effective synthesis routes to form cyclic compounds. These are concerted pericyclic reactions between two unsaturated compounds resulting in a cyclic product with two new σ bonds formed at the expense of π bonds. The [4 + 2] cycloaddition, known as the Diels–Alder reaction, is the most common. The other example is a [2 + 2] cycloaddition.
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Comparison of open-source software for producing directed acyclic graphs.

Amy J Pitts1, Charlotte R Fowler1

  • 1Department of Biostatistics, Columbia University.

Journal of Causal Inference
|February 16, 2024
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Summary
This summary is machine-generated.

Researchers can choose the best software for drawing directed acyclic graphs (DAGs) based on their needs. This study compares five common DAGs software packages, highlighting their features and usability for various research applications.

Keywords:
62D2068R1092B1597KxxDAGittyDirected acyclic graphs (DAGs)TikZdagRggdagigraph

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Area of Science:

  • Computer Science
  • Biostatistics
  • Epidemiology

Background:

  • Directed acyclic graphs (DAGs) are crucial for causal inference and research design.
  • Numerous software packages exist to aid researchers in creating DAGs.
  • Evaluating these tools is essential for efficient and accurate research visualization.

Purpose of the Study:

  • To compare the functionality, usability, and visualization capabilities of five popular DAGs software packages: Ti*k*Z, DAGitty, ggdag, dagR, and igraph.
  • To provide practical recommendations for selecting the most appropriate software based on specific research requirements.
  • To assess the performance of each software in generating both simple and complex DAG structures.

Main Methods:

  • A comparative analysis of five selected DAGs software packages.
  • Description of each software's background, analytical features, visualization options, and user-friendliness.
  • Generation of two DAGs (simple confounding and complex structure with confounders/mediator) in each software for direct comparison.

Main Results:

  • Detailed assessment of Ti*k*Z, DAGitty, ggdag, dagR, and igraph based on predefined criteria.
  • Identification of strengths and weaknesses of each software for different types of DAG generation tasks.
  • Empirical comparison of software performance using standardized DAG examples.

Conclusions:

  • The choice of DAGs software depends on the complexity of the graph and the user's technical expertise.
  • Ti*k*Z, DAGitty, ggdag, dagR, and igraph offer distinct advantages for specific research needs in causal inference.
  • This comparison aids researchers in selecting the optimal tool for visualizing causal relationships effectively.