Data and code from: Identification of a key target for elimination of nitrous oxide, a major greenhouse gas

<p>Note: Data files will be made available upon manuscript publication</p> <p>This dataset contains all code and data needed to reproduce the analyses in the manuscript:</p> <p>IDENTIFICATION OF A KEY TARGET FOR ELIMINATION OF NITROUS OXIDE, A MAJOR GREENHOUSE GAS.<br> Blake A. Oakley (1), Trevor Mitchell (2), Quentin D. Read (3), Garrett Hibbs (1), Scott E. Gold (2), Anthony E. Glenn (2)</p> <ol> <li>Department of Plant Pathology, University of Georgia, Athens, GA, USA.</li> <li>Toxicology and Mycotoxin Research Unit, U.S. National Poultry Research Center, United States Department of Agriculture-Agricultural Research Service, Athens, GA, USA</li> <li>Southeast Area, United States Department of Agriculture-Agricultural Research Service, Raleigh, NC, USA</li> </ol> <p><em>citation will be updated upon acceptance of manuscript</em></p> <h3>Brief description of study aims</h3> <p>Denitrification is a chemical process that releases nitrous oxide (N2O), a potent greenhouse gas. The NOR1 gene is part of the denitrification pathway in <em>Fusarium</em>. Three experiments were conducted for this study. (1) The N2O comparative experiment compares denitrification rates, as measured by N2O production, of a variety of <em>Fusarium</em> spp. strains with and without the NOR1 gene. (2) The N2O substrate experiment compares denitrification rates of selected strains on different growth media (substrates). For parts 1 and 2, linear models are fit comparing N2O production between strains and/or substrates. (3) The Bioscreen growth assay tests whether there is a pleiotropic effect of the NOR1 gene. In this portion of the analysis, growth curves are fit to assess differences in growth rate and carrying capacity between selected strains with and without the NOR1 gene.</p> <h3>Code</h3> <p>All code is included in a .zip archive generated from a private git repository on 2022-10-13 and archived as part of this dataset.</p> <p>The code is contained in R scripts and RMarkdown notebooks. There are two components to the analysis: the denitrification analysis (comprising parts 1 and 2 described above) and the Bioscreen growth analysis (part 3). The scripts for each are listed and described below.</p> <h4>Analysis of results of denitrification experiments (parts 1 and 2)</h4> <ul> <li><code>NOR1_denitrification_analysis.Rmd</code>: The R code to analyze the experimental data comparing nitrous oxide emissions is all contained in a single RMarkdown notebook. This script analyzes the results from the comparative study and the substrate study.</li> <li><code>n2o_subgroup_figures.R</code>: R script to create additional figures using the output from the RMarkdown notebook</li> </ul> <h4>Analysis of results of Bioscreen growth assay (part 3)</h4> <ul> <li><code>bioscreen_analysis.Rmd</code>: This RMarkdown notebook contains all R code needed to analyze the results of the Bioscreen assay comparing growth of the different strains. It could be run as is. However, the model-fitting portion was run on a high-performance computing cluster with the following scripts: <ul> <li><code>bioscreen_fit_simpler.R</code>: R script containing only the model-fitting portion of the Bioscreen analysis, fit using the Stan modeling language interfaced with R through the <strong>brms</strong> and <strong>cmdstanr</strong> packages.</li> <li><code>job_bssimple.sh</code>: Job submission shell script used to submit the model-fitting R job to be run on USDA SciNet high-performance computing cluster.</li> </ul></li> </ul> <p>Additional scripts developed as part of the analysis but that are not required to reproduce the analyses in the manuscript are in the <code>deprecated/</code> folder.</p> <p>Also note the files <code>nor1-denitrification.Rproj</code> (RStudio project file) and <code>gtstyle.css</code> (stylesheet for formatting the tables in the notebooks) are included.</p> <h3>Data</h3> <p>Data required to run the analysis scripts are archived in this dataset, other than <code>strain_lookup.csv</code>, a lookup table of strain abbreviations and full names included in the code repository for convenience. They should be placed in a folder or symbolic link called <code>project</code> within the unzipped code repository directory.</p> <ul> <li><code>N2O_data_2022-08-03/N2O_Comparative_Study_Trial_(n)_(date range).xlsx</code>: These are the data from the N2O comparative study, where <code>n</code> is the trial number from 1-3 and <code>date range</code> is the begin and end date of the trial.</li> <li><code>N2O_data_2022-08-03/Nitrogen_Substrate_Study_Trial_(n)_(date range).xlsx</code>: These are the data from the N2O substrate study, where <code>n</code> is the trial number from 1-3 and <code>date range</code> is the begin and end date of the trial.</li> <li><code>Outliers_NOR1_2022/Bioscreen_NOR1_Fungal_Growth_Assay_(substrate)_(oxygen level)_Outliers_BAO_(date).xlsx</code>: These are the raw Bioscreen data files in MS Excel format. The format of each file name includes the substrate (minimal medium with nitrite or nitrate and lysine), oxygen level (hypoxia or normoxia), and date of the run. This repository includes code to process these files, but the processed data are also included on Ag Data Commons, so it is not necessary to run the data processing portion of the code.</li> <li><code>clean_data/bioscreen_clean_data.csv</code>: This is an intermediate output file in CSV format generated by <code>bioscreen_analysis.Rmd</code>. It includes all the data from the Bioscreen assays in a clean analysis-ready format.</li> </ul><p></p>

[
  "005:18"
]

[
  "005:040"
]