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16S rRNA sequencing gene datasets for CRC data

<p>Used datasets:&nbsp;</p> <table> <thead> <tr> <th scope="col"> <table> <thead> <tr> <th>Dataset</th> <th>16S rRNA Region</th> <th>Control (n)</th> <th>Adenoma (n)</th> <th>CRC (n)</th> <th>Available metadata</th> </tr> </thead> <tbody> <tr> <td><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4823848/">Baxter</a></td> <td>V4</td> <td>171</td> <td>198</td> <td>120</td> <td>Gender, age, weight, height, BMI, country, race</td> </tr> <tr> <td><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221363/">Zackular</a></td> <td>V4</td> <td>30</td> <td>30</td> <td>30</td> <td>Gender, age, weight, height, BMI, country, race, FOBT, medication</td> </tr> <tr> <td><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299606/">Zeller</a></td> <td>V4</td> <td>50</td> <td>38</td> <td>41</td> <td>Gender, age, BMI, country, FOBT</td> </tr> <tr> <td><strong>TOTAL</strong></td> <td>V4</td> <td>251</td> <td>266</td> <td>191</td> <td><em>All of the above</em></td> </tr> </tbody> </table> </th> </tr> </thead> <tbody> <tr> <td>&nbsp;</td> </tr> </tbody> </table> <p>Data processing &amp; sharing</p> <p>All datasets were processed using&nbsp;<a href="https://docs.qiime2.org/2021.11/">qiime2</a>&nbsp;pipeline with&nbsp;<a href="https://benjjneb.github.io/dada2/">DADA2</a>&nbsp;for Sequence quality control and feature table construction and&nbsp;<a href="https://www.arb-silva.de/">SILVA</a>&nbsp;database for taxonomic assignment, and then a <em>phyloseq </em>object was constructed.</p> <ul> <li>Abundance table at genus level is in file <em>genus.csv</em> (Sample counts with NO filtering).</li> <li>Clean metadata is in <em>metadata.csv</em> file (Countries: CA - Canada. USA - United States of America. FRA - France.)</li> <li>Phyloseq object is in file <em>physeq.RDS</em> (Saved as an RDS object in R)</li> </ul> <p>More information is&nbsp;<a href="https://hackmd.io/nbsLqCLlSNSRFc5RBX9c5Q?view">here</a>.&nbsp;</p> <p>&nbsp;</p>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
20
Reuse readiness
8
Engagement
4

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