This main Jupyter notebook in this repository (Mackerel 16S Data Analysis.ipynb)
performs a simple re-analysis of mackerel and environmental sample 16S data
(Qiita study ID 11721,
and described in
Minich et al. 2019) in
QIIME 2,
Songbird,
and Qurro. This is for the Qurro
manuscript (now available in NAR Genomics and Bioinformatics here).
There are some other notebooks and files in this repository that were used in the process of preparing the manuscript, also. Here I'll try to explain some of these.
We recommend using nbviewer to view the notebooks in this repository:
-
Here's a link to the main notebook mentioned at the start of the case study section.
-
Here's a link to the notebook that produces Figs. 1(d) and 2(d), as mentioned in the figure captions.
-
Here's a link to the sample dropout analysis notebook mentioned in section 3 of the supplementary information.
This folder contains the input data for this analysis notebook (note that SILVA database files are not included; as the notebook describes, you'll have to download those yourself if you want to rerun this analysis). This input data should match the data on Qiita for this study, at least as of November 10, 2019.
This folder contains most of the output from the main notebook
(Mackerel 16S Data Analysis.ipynb).
As you can see from this repository's .gitignore file, files in his directory
with names matching the pattern silva*.qza are not included; this is because
most of these files are pretty large, and GitHub yelled at me when I tried to
commit them to this repository (so I had to
do this
and remove these files from the repository + repository history).
You can view all of the QIIME 2 artifact/visualization files here in
q2view by providing a URL of the format
https://raw.githubusercontent.com/knightlab-analyses/qurro-mackerel-analysis/master/output/songbird-regression-summary.qzv,
where you can replace songbird-regression-summary.qzv with whatever the QZA/QZV file you want to view is named.
Here are some links that'll take you straight to q2view:
- Imported feature table summary
- Imported and filtered feature table summary
- Songbird diagnostic plots
- Output Qurro plot (uses a development version of Qurro)
Please see the README in this folder describing the Qurro paper's figures. The script mentioned in the implementation section (for editing Vega-Lite specifications to make text bigger, etc.) is available in this folder as biggify.py.
Hey, it's not that long!