Emerging Clostridioides difficile ribotypes have divergent metabolic phenotypes
<p>Dataset of multi-well plate reader files related to the analysis of the growth of <em>C. difficile</em> isolates on differnet carbon substrates. </p> <p><strong>Data Collection. </strong>This<strong> </strong>dataset accompanies an <em>mSystems</em> article which is available at <a href="https://doi.org/10.1128/msystems.01075-24">https://doi.org/10.1128/msystems.01075-24</a>. The "Materials and Methods" section in this article fully describes the biological nature of these samples and how the samples were processed and analyzed. </p> <p><strong>Repository Content. </strong>The <em>amiga</em> folders contains both the raw data (see <em>data</em> and <em>mapping </em>sub-folders), intermediate outpus (see <em>dervied</em> sub-folders), and final outputs (see <em>figures</em> and <em>summary</em> sub-folders). Each <em>amiga </em>folder corresponds to a single working directory analyzed by the <a href="https://github.com/firasmidani/amiga"><em>AMiGA</em></a> software. For the <em>amiga-biolog</em> directory, the <em>notes</em> sub-folder also includes text files related to flagging plates and wells for quality issues.</p> <p><strong>Data Organization. </strong>Growth plate data are organized by the following experiments. </p> <ul> <li>biolog</li> <li>validation</li> <li>ribotype-255</li> <li>clade-5</li> <li>yeast-extract-biolog</li> <li>yeast-extract-validation</li> </ul> <p><strong>Data Analysis. </strong>Code used for manipulating and analyzing these samples is also publicly available on GitHub (<a href="https://github.com/firasmidani/cdiff-biolog-growth">https://github.com/firasmidani/cdiff-biolog-growth</a>) under the GNU GPL-3.0 license. The scripts in "analyze-code" can be used to analyze all data and the scripts in the "generate-figures" folder can be used to reproduce all figures included in the manuscript. See the GitHub repository for instructions on how to do so. </p> <p> </p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4