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Hotfix Adding Cell Line Analysis (greenelab#83)
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* add biopython to conda env

* update path to ras_genes.csv

* remove old path to classifiers archive

* add CCLE predictions to analysis
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gwaybio authored Sep 28, 2018
1 parent eb61159 commit e103e74
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Showing 4 changed files with 15 additions and 3 deletions.
2 changes: 2 additions & 0 deletions environment.yml
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@@ -1,5 +1,6 @@
name: pancancer-classifier
channels:
- conda-forge
- bioconda
dependencies:
- conda-forge::python=3.6.5
Expand All @@ -25,3 +26,4 @@ dependencies:
- conda-forge::r-ggrepel 0.8.0
- conda-forge::r-cowplot=0.9.3
- conda-forge::r-hmisc=4.0_3
- bioconda::biopython=1.70
10 changes: 10 additions & 0 deletions ras_analysis.sh
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Expand Up @@ -182,7 +182,17 @@ python scripts/pancancer_classifier.py --genes 'KRAS,HRAS,NRAS' \
###############
# Step 8. Plot additional Ras, NF1, and BRAF results
###############
# Plot Ras pathway heatmaps
python scripts/ras_count_heatmaps.py

# Visualize CCLE predictions
jupyter nbconvert --to=script \
--FilesWriter.build_directory=scripts \
--ExecutePreprocessor.kernel_name=python3 \
--ExecutePreprocessor.timeout=100000 \
--execute scripts/ras_cell_line_predictions.ipynb

# Plot summary figures
Rscript --vanilla scripts/viz/ras_summary_figures.R
Rscript --vanilla scripts/viz/ras_ccle_pharmacology.R
Rscript --vanilla scripts/viz/ras_benchmarking_figures.R
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4 changes: 2 additions & 2 deletions scripts/ras_cell_line_predictions.ipynb
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Expand Up @@ -2437,7 +2437,7 @@
],
"source": [
"# Load TCGA PanCanAtlas Core Ras Pathway genes\n",
"ras_genes_file = os.path.join('..', 'classifiers', 'RAS', 'ras_genes.csv')\n",
"ras_genes_file = os.path.join('..', 'data', 'ras_genes.csv')\n",
"ras_core_df = pd.read_table(ras_genes_file)\n",
"ras_core_df.head()"
]
Expand Down Expand Up @@ -3622,7 +3622,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.5"
"version": "3.6.5"
}
},
"nbformat": 4,
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2 changes: 1 addition & 1 deletion scripts/viz/ras_summary_figures.R
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Expand Up @@ -23,7 +23,7 @@ source(file.path("scripts", "util", "pancancer_util.R"))

set.seed(123)

results_folder <- file.path("classifiers_archive", "RAS")
results_folder <- file.path("classifiers", "RAS")
results <- parse_summary(file.path(results_folder, "classifier_summary.txt"))

dir.create("figures")
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