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Merge pull request #26 from genotoul-bioinfo/dev
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Minor adjustments in documentation and tutorial
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JeanMainguy authored Sep 6, 2024
2 parents 277d433 + 82a0d4b commit f95e2ac
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7 changes: 4 additions & 3 deletions README.md
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Expand Up @@ -148,9 +148,10 @@ In both formats, the `--contigs` argument should specify a FASTA file containing
Binette results are stored in the `results` directory. You can specify a different directory using the `--outdir` option.
In this directory you will find:
- `final_bins_quality_reports.tsv`: This is a TSV (tab-separated values) file containing quality information about the final selected bins.
- `final_bins/`: This directory stores all the selected bins in fasta format.
- `temporary_files/`: This directory contains intermediate files. If you choose to use the `--resume` option, Binette will utilize files in this directory to prevent the recomputation of time-consuming steps.
- **`final_bins_quality_reports.tsv`**: This is a TSV (tab-separated values) file containing quality information about the final selected bins.
- **`final_bins/`**: This directory stores all the selected bins in fasta format.
- **`input_bins_quality_reports/`**: A directory storing quality reports for the input bin sets, with files following the same structure as `final_bins_quality_reports.tsv`.
- **`temporary_files/`**: This directory contains intermediate files. If you choose to use the `--resume` option, Binette will utilize files in this directory to prevent the recomputation of time-consuming steps.
The `final_bins_quality_reports.tsv` file contains the following columns:
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9 changes: 6 additions & 3 deletions docs/tutorial/analyse_binette_result.ipynb
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Expand Up @@ -7,7 +7,9 @@
"source": [
"## Analyse Binette results\n",
"\n",
"Let's visualize the results from Binette and compare them to the initial bin sets used as input. "
"Let's visualize the results from Binette and compare them to the initial bin sets used as input. \n",
"\n",
"To explore these results interactively, you can open the Jupyter notebook via Binder by following this link: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/genotoul-bioinfo/Binette/binder_tutorial_env?urlpath=git-pull%3Frepo%3Dhttps%253A%252F%252Fgithub.com%252Fgenotoul-bioinfo%252FBinette%26urlpath%3Dtree%252FBinette%252Fdocs%252Ftutorial%252Fanalyse_binette_result.ipynb%26branch%3Dmain)"
]
},
{
Expand All @@ -31,7 +33,8 @@
"from pathlib import Path\n",
"import plotly.express as px\n",
"\n",
"# This is needed to properly display Plotly graphs in the documentation\n",
"# The following two lines are needed to properly display Plotly graphs in the documentation\n",
"# However you may need to remove these lines and restart the kernel to visualise the graph in another context\n",
"import plotly.io as pio\n",
"pio.renderers.default = \"sphinx_gallery\""
]
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.19"
"version": "3.8.12"
}
},
"nbformat": 4,
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2 changes: 1 addition & 1 deletion docs/tutorial/get_dataset.md
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Expand Up @@ -24,7 +24,7 @@ Once the tool is installed, you can download the "Kickstart" dataset with the fo

```{code-block} bash
# Select the header of the table
head -n7 coal-metagenomics.tsv > coal-metagenomics_Kickstart_only.tsv
head -n8 coal-metagenomics.tsv > coal-metagenomics_Kickstart_only.tsv
# Append the relevant line for the Kickstart dataset
grep SRR5058924 coal-metagenomics.tsv >> coal-metagenomics_Kickstart_only.tsv
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