Comments (5)
Here is the additional information:
I installed Qiime2 using the command: conda install -c qiime2 qiime2
For Dokdo installation, I followed the instructions in the 'Getting Started' section:
$ git clone https://github.com/sbslee/dokdo
$ cd dokdo
$ pip install .
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Thanks for providing all the details. QIIME 2 requires many tools and plugins to run, and I don't think the command $ conda install -c qiime2 qiime2
installs all the required packages. Please follow their installation guide and reinstall QIIME 2 in the proper way. Please let me know if the problem still persists.
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Hello, @sbslee
I hope this message finds you well. I wanted to express my gratitude for your assistance. I encountered an unexpected conflict issue on my server, which prevented me from downloading files using wget. So I try to install qiime2 using the command:$ conda install -c qiime2 qiime2
.
As a solution, I followed your advice and installed Qiime2 with offical guide. It turns out that the issue with Dokdo not functioning correctly was related to the installation method. Now Dokdo runs smoothly without any issues. I appreciate your support in providing such a valuable visualization tool.
And I have another question. Is there a way to use the pretty_taxa feature when creating a bar plot with taxa_abundance_plot? I'd like to display only genus and species names by using level=[6,7]. If this feature is not currently supported in Dokdo, I'll try alternative methods and sharing the results.
Additionally, I have a question regarding the read_quality plot. I noticed that the tutorial demonstrates creating a boxplot-like graph, but I'm curious if it's possible to generate a histogram for Demultiplexed sequence counts summary. If this functionality is not currently available, I'm also willing to experiment with different approaches and share the outcomes.
Thank you once again for your assistance.
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As for the dokdo.taxa_abundance_bar_plot
method, you can do the following:
import dokdo
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set()
qzv_file = '/Users/sbslee/Desktop/dokdo/data/moving-pictures-tutorial/taxa-bar-plots.qzv'
dokdo.taxa_abundance_bar_plot(
qzv_file,
figsize=(10, 7),
level=7,
count=8,
legend_short=True,
pname_kws={'levels': [6, 7]}
)
plt.tight_layout()
As for your second question, I think the dokdo.denoising_stats_plot
method could be what you are looking for. Please see the method's documentation page.
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Closed due to inactivity. Please feel free to re-open it if necessary.
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Related Issues (20)
- `alpha_rarefaction_plot` apparently ignores 'N/A' values when plotting
- alpha and beta diversity without qiime file HOT 7
- correlation analysis HOT 11
- Plot options for `beta_2d/3d_plot` and `taxa_abundance_box_plot` methods HOT 13
- Implementing differential abundance analysis HOT 2
- dokdo `beta_parallel_plot` issue HOT 1
- taxa_abundance_bar_plot issue HOT 1
- Add the rank abundance curve plot
- exclude "others" from relative abundance and plot HOT 3
- ModuleNotFoundError: No module named 'skbio' HOT 8
- ImportError: libhdf5_cpp.so.200: cannot open shared object file: No such file or directory HOT 2
- Select samples for PCoA HOT 3
- Add taxon name in the pcoa biplot HOT 1
- Overlapping legends on clustermap HOT 3
- How to plot many species on a bar graph HOT 8
- [taxa_abundance_bar_plot] Customizing bar colors with using 'Seaborn palette' or 'Matplotlib colormap' HOT 2
- [taxa_abundance_box_plot] Deletion of notation of species not observed in samples HOT 2
- ImportError: cannot import name 'diversity_lib' HOT 2
- KeyError: "['merged'] not in index", after running "dokdo.denoising_stats_plot" HOT 2
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