diff --git a/interactomes/PCNet.05_2018.oi2 b/interactomes/PCNet.05_2018.oi2
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+version https://git-lfs.github.com/spec/v1
+oid sha256:18bba1b9612ffde9b729deac04216a666da50c8ac4571e7726cd6bb9ca406d41
+size 44161527
diff --git a/interactomes/PreProcess_PCNet_For_OmicsIntegrator.ipynb b/interactomes/PreProcess_PCNet_For_OmicsIntegrator.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# PreProcessing PCNet for OmicsIntegrator\n",
+    "\n",
+    "All Fraenkel-lab interactomes have been pre-processed to have 3 columns: 2 interactors and a scalar confidence\n",
+    "However, OmicsIntegrator requires that edges have a cost, not a confidence. This notebook sets costs on the edges and augments those interactomes for use in OmicsIntegrator."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>protein1</th>\n",
+       "      <th>protein2</th>\n",
+       "      <th>confidence</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>A2M</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ABCC6</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ACOT12</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ADH1A</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ADH4</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  protein1 protein2  confidence\n",
+       "0     A1BG      A2M         NaN\n",
+       "1     A1BG    ABCC6         NaN\n",
+       "2     A1BG   ACOT12         NaN\n",
+       "3     A1BG    ADH1A         NaN\n",
+       "4     A1BG     ADH4         NaN"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pcnet =  pd.read_pickle(\"../../interactomes/PCNet/PCNet.05_2018.cleaned.namespace-mapped.full.pickle\")\n",
+    "pcnet.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### PCNet is relatively unique in that we don't have confidences for the edges. We'll need to set them arbitrarily"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>protein1</th>\n",
+       "      <th>protein2</th>\n",
+       "      <th>cost</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>A2M</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ABCC6</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ACOT12</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ADH1A</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>A1BG</td>\n",
+       "      <td>ADH4</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  protein1 protein2  cost\n",
+       "0     A1BG      A2M   1.0\n",
+       "1     A1BG    ABCC6   1.0\n",
+       "2     A1BG   ACOT12   1.0\n",
+       "3     A1BG    ADH1A   1.0\n",
+       "4     A1BG     ADH4   1.0"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pcnet['cost'] = 1.0\n",
+    "del pcnet['confidence']\n",
+    "\n",
+    "pcnet.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pcnet.to_csv('PCNet.05_2018.oi2', sep='\\t', index=False)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}