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Uncover a microbiota signature of upper respiratory tract in patients with SARS-CoV-2+

<p>This is the repository containing the code used to obtain the results shown in <a href="https://doi.org/10.1038/s41598-023-43040-x"><i><strong>Bellato M, Cappellato M, Longhin F, Del Vecchio C, Brancaccio G, Cattelan AM, Brun P, Salaris C, Castagliuolo I, Di Camillo B. "Uncover a microbiota signature of upper respiratory tract in patients with SARS-CoV-2+" Sci Rep 13, 16867 (2023)</strong></i></a>.</p><p>We characterized through 16S rDNA-seq the microbiota in the upper airways of 192 subjects with a positive nasopharyngeal swab for SARS-CoV-2 to identify a microbial signature predictive of disease progression. Patients were divided in groups based on the presence of symptoms, the level of pneumonia, and whether or not they needed oxygen therapy or intubation.&nbsp;</p><p>In the GitLab repository&nbsp;<a href="https://gitlab.com/sysbiobig/microbiomecovid/-/tree/v1.0">here</a>&nbsp;there are all the scripts used to perform the preprocessing step and the downstream analysis.&nbsp;The GitLab repository (version 1.0) contains also the Docker image&nbsp;<strong>microbiomecovid:1.0.0</strong>&nbsp;that can be used to reproduce the results shown in the paper (see the instruction <a href="https://gitlab.com/sysbiobig/microbiomecovid/-/tree/v1.0#reproduce-the-results-%EF%B8%8F">here</a>).</p><p>Here in Zenodo you can find the&nbsp;<strong>microbiomecovid_data.zip </strong>file containing two folders that need to be unzipped and&nbsp;put in the <i>microbiomecovid</i>&nbsp;local repository, downloaded from GitLab.</p><p>In particular, the <i><strong>original_data</strong></i> folder contains:</p><ul><li><i><strong>Raw_data</strong></i><strong>: </strong>a folder with two FASTQ files for each sample, i.e., forward (R1) and reverse (R2) reads.</li><li><strong>Metadata.xlsx: </strong>the table containing information on the - anonymized - subjects involved in the study.</li><li><strong>QC Report.pdf: </strong>The report provided by the sequencing center.</li></ul><p>Additionally, in the&nbsp;<i><strong>output</strong></i><strong> </strong>folder, the following items can be found:</p><ul><li><i><strong>Preprocessing</strong></i><strong>: </strong>a folder containing all the output file from step1 to step7, namely:<ul><li>create input data for QIIME2;</li><li>import data in QIIME2;</li><li>remove primers;</li><li>denoising and imputation;</li><li>taxonomy classification;</li><li>phylogenetic tree&nbsp;reconstruction;</li><li>collapse at specific taxonomic level and normalize data.</li></ul></li><li><i><strong>Analysis</strong></i><strong>:&nbsp; </strong>a folder containing all the output files form step8 to step10 namely:<ul><li>alpha and beta diversity results;</li><li><i><strong>DA_output</strong></i><strong>:</strong> a folder containing the differential abundance analysis performed for each taxonomic level and for each covariate;</li><li><i><strong>Network_output:</strong></i> a folder containing the sparCC and&nbsp;Cytoscape networks and results.</li></ul></li></ul><p>For more info about all the bioinformatic pipeline see the <a href="https://gitlab.com/sysbiobig/microbiomecovid/-/tree/v1.0#pipeline">GitLab repository</a><strong>.</strong></p><p>Remember to set the path as&nbsp;<i>ABSOLUTE_PATH_MICROBIOMECOVID.</i></p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

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

Stewardship
8
Harmonization
4
Access
8
Reuse readiness
8
Engagement
4

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Dataset details

Repository
zenodo
Published
March 8, 2023
License
Not reported
DOI
10.5281/zenodo.7299599

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