diff --git a/nbs/25_pvalue/00-ccc_pvalue_dist-generate.ipynb b/nbs/25_pvalue/00-ccc_pvalue_dist-generate-data_matrix.ipynb similarity index 97% rename from nbs/25_pvalue/00-ccc_pvalue_dist-generate.ipynb rename to nbs/25_pvalue/00-ccc_pvalue_dist-generate-data_matrix.ipynb index a50cbd98..576c8537 100644 --- a/nbs/25_pvalue/00-ccc_pvalue_dist-generate.ipynb +++ b/nbs/25_pvalue/00-ccc_pvalue_dist-generate-data_matrix.ipynb @@ -31,7 +31,9 @@ "tags": [] }, "source": [ - "Generates a distribution of pvalues under the null hypothesis of no association." + "Generates a distribution of pvalues under the null hypothesis of no association.\n", + "\n", + "This notebook uses a data matrix as input for CCC and parallelizes computation across gene pairs." ] }, { @@ -370,7 +372,7 @@ }, "outputs": [], "source": [ - "output_file = OUTPUT_DIR / \"cm_values.npy\"\n", + "output_file = OUTPUT_DIR / \"data_matrix-cm_values.npy\"\n", "display(output_file)\n", "\n", "np.save(output_file, cm_values)" @@ -392,7 +394,9 @@ }, "outputs": [], "source": [ - "output_file = OUTPUT_DIR / \"cm_pvalues.npy\"\n", + "output_file = OUTPUT_DIR / \"data_matrix-cm_pvalues.npy\"\n", + "display(output_file)\n", + "\n", "np.save(output_file, cm_pvalues)" ] }, diff --git a/nbs/25_pvalue/py/00-ccc_pvalue_dist-generate.py b/nbs/25_pvalue/py/00-ccc_pvalue_dist-generate-data_matrix.py similarity index 86% rename from nbs/25_pvalue/py/00-ccc_pvalue_dist-generate.py rename to nbs/25_pvalue/py/00-ccc_pvalue_dist-generate-data_matrix.py index 5f138aec..0ca21ea5 100644 --- a/nbs/25_pvalue/py/00-ccc_pvalue_dist-generate.py +++ b/nbs/25_pvalue/py/00-ccc_pvalue_dist-generate-data_matrix.py @@ -18,6 +18,8 @@ # %% [markdown] tags=[] # Generates a distribution of pvalues under the null hypothesis of no association. +# +# This notebook uses a data matrix as input for CCC and parallelizes computation across gene pairs. # %% [markdown] tags=[] # # Modules loading @@ -80,13 +82,15 @@ # # Save # %% tags=[] -output_file = OUTPUT_DIR / "cm_values.npy" +output_file = OUTPUT_DIR / "data_matrix-cm_values.npy" display(output_file) np.save(output_file, cm_values) # %% tags=[] -output_file = OUTPUT_DIR / "cm_pvalues.npy" +output_file = OUTPUT_DIR / "data_matrix-cm_pvalues.npy" +display(output_file) + np.save(output_file, cm_pvalues) # %% tags=[]