Fix typos, drop GCT

broadinstitute · Mar 20, 2021 · 4a0de4f · 4a0de4f
1 parent 907d031
commit 4a0de4f
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Showing 4 changed files with 1 addition and 114 deletions.
diff --git a/consensus/2016_04_01_a549_48hr_batch1/2016_04_01_a549_48hr_batch1_consensus_modz.gct b/consensus/2016_04_01_a549_48hr_batch1/2016_04_01_a549_48hr_batch1_consensus_modz.gct
diff --git a/consensus/README.md b/consensus/README.md
@@ -48,7 +48,7 @@ The pipeline can be reproduced by executing the following:
 # Make sure conda environment is activated
 conda activate lincs
 
-# Reproduce thepipeline for producing bulk signatures
+# Reproduce the pipeline for producing bulk signatures
 ipython scripts/nbconverted/build-consensus-signatures.py
 ```
 

diff --git a/consensus/build-consensus-signatures.ipynb b/consensus/build-consensus-signatures.ipynb
@@ -102,7 +102,6 @@
     "from pycytominer.aggregate import aggregate\n",
     "from pycytominer.consensus import modz_base\n",
     "from pycytominer.feature_select import feature_select\n",
-    "\n",
     "from pycytominer.cyto_utils import infer_cp_features"
    ]
   },
@@ -635,83 +634,6 @@
     "            index=False,\n",
     "        )"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Save whole plate MODZ consensus signature as GCT\n",
-    "\n",
-    "Whole-plate-normalized + MODZ aggregated consensus profiles will be made available on clue.io/morphology as a GCT file."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Now Writing: Consensus Operation: modz; Norm Strategy: whole_plate\n",
-      "File: 2016_04_01_a549_48hr_batch1/2016_04_01_a549_48hr_batch1_consensus_modz.gct\n",
-      "(8340, 1790)\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "\n",
-       "            setTimeout(function() {\n",
-       "                var nbb_cell_id = 11;\n",
-       "                var nbb_unformatted_code = \"import pycytominer.write_gct\\n\\noperation = \\\"modz\\\"\\nnorm_strat = \\\"whole_plate\\\"\\nfile_suffix = \\\".gct\\\"\\nconsensus_file = f\\\"{batch}_consensus_{operation}{file_suffix}\\\"\\nconsensus_file = pathlib.Path(batch, consensus_file)\\n\\nconsensus_df = all_consensus_dfs[norm_strat][operation][\\\"no_feat_select\\\"]\\n\\nprint(\\n    f\\\"Now Writing: Consensus Operation: {operation}; Norm Strategy: {norm_strat}\\\\nFile: {consensus_file}\\\"\\n)\\nprint(consensus_df.shape)\\n\\npycytominer.write_gct(consensus_df, consensus_file)\";\n",
-       "                var nbb_formatted_code = \"import pycytominer.write_gct\\n\\noperation = \\\"modz\\\"\\nnorm_strat = \\\"whole_plate\\\"\\nfile_suffix = \\\".gct\\\"\\nconsensus_file = f\\\"{batch}_consensus_{operation}{file_suffix}\\\"\\nconsensus_file = pathlib.Path(batch, consensus_file)\\n\\nconsensus_df = all_consensus_dfs[norm_strat][operation][\\\"no_feat_select\\\"]\\n\\nprint(\\n    f\\\"Now Writing: Consensus Operation: {operation}; Norm Strategy: {norm_strat}\\\\nFile: {consensus_file}\\\"\\n)\\nprint(consensus_df.shape)\\n\\npycytominer.write_gct(consensus_df, consensus_file)\";\n",
-       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
-       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
-       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
-       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
-       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
-       "                        }\n",
-       "                        break;\n",
-       "                    }\n",
-       "                }\n",
-       "            }, 500);\n",
-       "            "
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import pycytominer.write_gct\n",
-    "\n",
-    "operation = \"modz\"\n",
-    "norm_strat = \"whole_plate\"\n",
-    "file_suffix = \".gct\"\n",
-    "consensus_file = f\"{batch}_consensus_{operation}{file_suffix}\"\n",
-    "consensus_file = pathlib.Path(batch, consensus_file)\n",
-    "\n",
-    "consensus_df = all_consensus_dfs[norm_strat][operation][\"no_feat_select\"]\n",
-    "\n",
-    "print(\n",
-    "    f\"Now Writing: Consensus Operation: {operation}; Norm Strategy: {norm_strat}\\nFile: {consensus_file}\"\n",
-    ")\n",
-    "print(consensus_df.shape)\n",
-    "\n",
-    "pycytominer.write_gct(consensus_df, consensus_file)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

diff --git a/consensus/scripts/nbconverted/build-consensus-signatures.py b/consensus/scripts/nbconverted/build-consensus-signatures.py
@@ -36,7 +36,6 @@
 from pycytominer.aggregate import aggregate
 from pycytominer.consensus import modz_base
 from pycytominer.feature_select import feature_select
-
 from pycytominer.cyto_utils import infer_cp_features
 
 
@@ -270,34 +269,3 @@ def consensus_apply(df, operation, cp_features, replicate_cols):
             index=False,
         )
 
-
-# ## Save whole plate MODZ consensus signature as GCT
-# 
-# Whole-plate-normalized + MODZ aggregated consensus profiles will be made available on clue.io/morphology as a GCT file.
-
-# In[11]:
-
-
-import pycytominer.write_gct
-
-operation = "modz"
-norm_strat = "whole_plate"
-file_suffix = ".gct"
-consensus_file = f"{batch}_consensus_{operation}{file_suffix}"
-consensus_file = pathlib.Path(batch, consensus_file)
-
-consensus_df = all_consensus_dfs[norm_strat][operation]["no_feat_select"]
-
-print(
-    f"Now Writing: Consensus Operation: {operation}; Norm Strategy: {norm_strat}\nFile: {consensus_file}"
-)
-print(consensus_df.shape)
-
-pycytominer.write_gct(consensus_df, consensus_file)
-
-
-# In[ ]:
-
-
-
-