From 4bcbf7c83d0b0633be3dbed172bad728595a252d Mon Sep 17 00:00:00 2001
From: Damien Farrell <farrell.damien@gmail.com>
Date: Mon, 28 Sep 2020 15:29:59 +0100
Subject: [PATCH] minor

---
 epitopepredict/base.py      |    4 +-
 epitopepredict/plotting.py  |    4 +-
 examples/basics.ipynb       | 1012 +++++++++++++++--------------------
 examples/mtb_sa_sette.ipynb |  405 ++++----------
 examples/sarscov2.ipynb     |  132 +++--
 5 files changed, 654 insertions(+), 903 deletions(-)

diff --git a/epitopepredict/base.py b/epitopepredict/base.py
index 0938545..8baeec1 100644
--- a/epitopepredict/base.py
+++ b/epitopepredict/base.py
@@ -679,8 +679,8 @@ def promiscuous_binders(self, binders=None, name=None, cutoff=.95,
             binders: can provide a precalculated list of binders
             name: specific protein, optional
             value: to pass to get_binders
-            cutoff_method: 'default', 'score' or 'rank'
-            cutoff: percentile cutoff for get_binders
+            cutoff_method: 'rank', 'score' or 'global'
+            cutoff: cutoff for get_binders (rank, score or percentile)
             n: min number of alleles
             unique_core: removes peptides with duplicate cores and picks the most
             limit: limit the number of peptides per protein, default None
diff --git a/epitopepredict/plotting.py b/epitopepredict/plotting.py
index d792d67..8dc3798 100644
--- a/epitopepredict/plotting.py
+++ b/epitopepredict/plotting.py
@@ -421,7 +421,7 @@ def bokeh_plot_sequence(preds, name=None, n=2, cutoff=.95, cutoff_method='defaul
     """
     callback = CustomJS(
         args=dict(x_range=p.x_range,rect=previewrect,text=seqtext,width=p.plot_width), code=jscode)
-    slider = RangeSlider (start=0, end=N, value=(0,L), step=10, callback_policy="throttle")
+    slider = RangeSlider (start=0, end=N, value=(0,L), step=10)#, callback_policy="throttle")
     slider.js_on_change('value_throttled', callback)
 
     #callback for plot drag
@@ -659,7 +659,7 @@ def plot_tracks(preds, name, n=1, cutoff=.95, cutoff_method='default', regions=N
             h = round(h*.1+2)
             figsize = (w,h)
         #plt.clf()
-        fig = plt.figure(figsize=figsize)
+        fig = plt.figure(figsize=figsize,facecolor='white')
         ax = fig.add_subplot(111)
 
     p = len(preds)
diff --git a/examples/basics.ipynb b/examples/basics.ipynb
index 75e1892..9419ffd 100644
--- a/examples/basics.ipynb
+++ b/examples/basics.ipynb
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -55,7 +55,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -95,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -115,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -140,14 +140,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['YRFESPEYD', 'PIQHEQDEW', 'FIFHMECYF', 'CDGDKSNPV', 'YAQRPYPNC']\n"
+      "['QISLMKHMK', 'WLKTYNFMC', 'QARFEQSYP', 'VKKWMGSLS', 'MDAIFPEQN']\n"
      ]
     }
    ],
@@ -171,19 +171,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "     peptide  pos  log50k   score  name       allele  rank\n",
-      "0  NTEKVALQY  270  0.8211    6.93  temp  HLA-A*01:01   1.0\n",
-      "1  YMAKFSALY  603  0.7968    9.01  temp  HLA-A*01:01   2.0\n",
-      "2  TTCMYQTRY   58  0.7505   14.87  temp  HLA-A*01:01   3.0\n",
-      "3  YLEYCDMPY  538  0.7310   18.37  temp  HLA-A*01:01   4.0\n",
-      "4  WTEFTVIQF  631  0.4376  439.24  temp  HLA-A*01:01   5.0\n"
+      "     peptide  pos  log50k  score  name       allele  rank\n",
+      "0  RTEDAHMNY  132  0.7236  19.90  temp  HLA-A*01:01   1.0\n",
+      "1  MADDEIIDY  597  0.6797  31.99  temp  HLA-A*01:01   2.0\n",
+      "2  NTSKSEQVY   38  0.6093  68.53  temp  HLA-A*01:01   3.0\n",
+      "3  AVEYMHLQY  986  0.5991  76.53  temp  HLA-A*01:01   4.0\n",
+      "4  LMESQDAHY  176  0.5987  76.86  temp  HLA-A*01:01   5.0\n"
      ]
     }
    ],
@@ -200,7 +200,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -373,7 +373,7 @@
        "[132 rows x 7 columns]"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -394,7 +394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -567,7 +567,7 @@
        "10     675      5  "
       ]
      },
-     "execution_count": 17,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -580,7 +580,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -599,7 +599,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -696,7 +696,7 @@
        "222  HLA-A*01:01  0.3067  Rv1886c  SSDPAWERN  223   5.0  1810.49"
       ]
      },
-     "execution_count": 44,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -714,19 +714,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pb1 = P1.promiscuous_binders(n=2, cutoff=5, cutoff_method='rank')\n",
+    "pb1[:5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## run other predictors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/home/damien/gitprojects/epitopepredict/epitopepredict/base.py:695: SettingWithCopyWarning: \n",
-      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
-      "Try using .loc[row_indexer,col_indexer] = value instead\n",
-      "\n",
-      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
-      "  binders['core'] = binders.peptide\n"
+      "predictions done for 3 sequences in 6 alleles\n"
      ]
     },
     {
@@ -750,107 +762,322 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
+       "      <th>%Rank_BA</th>\n",
+       "      <th>%Rank_EL</th>\n",
+       "      <th>BindLevel</th>\n",
+       "      <th>Gl</th>\n",
+       "      <th>Gp</th>\n",
+       "      <th>Icore</th>\n",
+       "      <th>Identity</th>\n",
+       "      <th>Il</th>\n",
+       "      <th>Ip</th>\n",
+       "      <th>Of</th>\n",
+       "      <th>Score_BA</th>\n",
+       "      <th>Score_EL</th>\n",
+       "      <th>allele</th>\n",
+       "      <th>core</th>\n",
+       "      <th>ic50</th>\n",
+       "      <th>name</th>\n",
        "      <th>peptide</th>\n",
        "      <th>pos</th>\n",
-       "      <th>name</th>\n",
-       "      <th>alleles</th>\n",
-       "      <th>core</th>\n",
+       "      <th>rank</th>\n",
        "      <th>score</th>\n",
-       "      <th>mean</th>\n",
-       "      <th>median_rank</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>70</th>\n",
-       "      <td>VTSIHSLLD</td>\n",
-       "      <td>22</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>3</td>\n",
-       "      <td>VTSIHSLLD</td>\n",
-       "      <td>3347.32</td>\n",
-       "      <td>5387.370</td>\n",
-       "      <td>3.0</td>\n",
+       "      <th>114</th>\n",
+       "      <td>0.064</td>\n",
+       "      <td>0.248</td>\n",
+       "      <td>&lt;=</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>QSSFYSDWY</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.608571</td>\n",
+       "      <td>0.550058</td>\n",
+       "      <td>HLA-A*01:01</td>\n",
+       "      <td>QSSFYSDWY</td>\n",
+       "      <td>69.07</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>QSSFYSDWY</td>\n",
+       "      <td>115</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>69.07</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>HTAGVDLAK</td>\n",
-       "      <td>70</td>\n",
-       "      <td>Rv3615c</td>\n",
-       "      <td>2</td>\n",
-       "      <td>HTAGVDLAK</td>\n",
-       "      <td>100.19</td>\n",
-       "      <td>4114.370</td>\n",
-       "      <td>1.5</td>\n",
+       "      <th>93</th>\n",
+       "      <td>0.090</td>\n",
+       "      <td>0.173</td>\n",
+       "      <td>&lt;=</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NTPAFEWYY</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.567313</td>\n",
+       "      <td>0.661575</td>\n",
+       "      <td>HLA-A*01:01</td>\n",
+       "      <td>NTPAFEWYY</td>\n",
+       "      <td>107.94</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>NTPAFEWYY</td>\n",
+       "      <td>94</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>107.94</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>59</th>\n",
+       "      <th>169</th>\n",
+       "      <td>0.095</td>\n",
+       "      <td>0.201</td>\n",
+       "      <td>&lt;=</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "      <td>SSAMILAAY</td>\n",
-       "      <td>170</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.562260</td>\n",
+       "      <td>0.624424</td>\n",
+       "      <td>HLA-A*01:01</td>\n",
+       "      <td>SSAMILAAY</td>\n",
+       "      <td>114.01</td>\n",
        "      <td>Rv1886c</td>\n",
-       "      <td>2</td>\n",
        "      <td>SSAMILAAY</td>\n",
-       "      <td>26.88</td>\n",
-       "      <td>1057.660</td>\n",
-       "      <td>2.5</td>\n",
+       "      <td>170</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>114.01</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>61</th>\n",
-       "      <td>SVAITHGPY</td>\n",
-       "      <td>39</td>\n",
-       "      <td>Rv3615c</td>\n",
-       "      <td>2</td>\n",
-       "      <td>SVAITHGPY</td>\n",
-       "      <td>1713.29</td>\n",
-       "      <td>2833.760</td>\n",
-       "      <td>2.5</td>\n",
+       "      <th>118</th>\n",
+       "      <td>0.624</td>\n",
+       "      <td>1.533</td>\n",
+       "      <td>&lt;=</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>YSDWYSPAC</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.321390</td>\n",
+       "      <td>0.076134</td>\n",
+       "      <td>HLA-A*01:01</td>\n",
+       "      <td>YSDWYSPAC</td>\n",
+       "      <td>1544.43</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>YSDWYSPAC</td>\n",
+       "      <td>119</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1544.43</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>AIQGNVTSI</td>\n",
-       "      <td>17</td>\n",
+       "      <th>205</th>\n",
+       "      <td>0.943</td>\n",
+       "      <td>1.204</td>\n",
+       "      <td>&lt;=</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>LAMGDAGGY</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.268694</td>\n",
+       "      <td>0.111025</td>\n",
+       "      <td>HLA-A*01:01</td>\n",
+       "      <td>LAMGDAGGY</td>\n",
+       "      <td>2731.40</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>LAMGDAGGY</td>\n",
+       "      <td>206</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>2731.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>78.734</td>\n",
+       "      <td>43.500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>GVQQKWDAT</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.015567</td>\n",
+       "      <td>0.000028</td>\n",
+       "      <td>HLA-B*44:03</td>\n",
+       "      <td>GVQQKWDAT</td>\n",
+       "      <td>42249.46</td>\n",
        "      <td>Rv3875</td>\n",
-       "      <td>2</td>\n",
-       "      <td>AIQGNVTSI</td>\n",
-       "      <td>1410.10</td>\n",
-       "      <td>3128.155</td>\n",
-       "      <td>3.0</td>\n",
+       "      <td>GVQQKWDAT</td>\n",
+       "      <td>53</td>\n",
+       "      <td>83.0</td>\n",
+       "      <td>42249.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>88.447</td>\n",
+       "      <td>80.000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>GSEAYQGVQ</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.012250</td>\n",
+       "      <td>0.000003</td>\n",
+       "      <td>HLA-B*44:03</td>\n",
+       "      <td>GSEAYQGVQ</td>\n",
+       "      <td>43793.29</td>\n",
+       "      <td>Rv3875</td>\n",
+       "      <td>GSEAYQGVQ</td>\n",
+       "      <td>47</td>\n",
+       "      <td>84.0</td>\n",
+       "      <td>43793.29</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>90.081</td>\n",
+       "      <td>37.333</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>LDEGKQSLT</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.011645</td>\n",
+       "      <td>0.000042</td>\n",
+       "      <td>HLA-B*44:03</td>\n",
+       "      <td>LDEGKQSLT</td>\n",
+       "      <td>44080.89</td>\n",
+       "      <td>Rv3875</td>\n",
+       "      <td>LDEGKQSLT</td>\n",
+       "      <td>29</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>44080.89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>93.171</td>\n",
+       "      <td>70.000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>GGSGSEAYQ</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.010310</td>\n",
+       "      <td>0.000006</td>\n",
+       "      <td>HLA-B*44:03</td>\n",
+       "      <td>GGSGSEAYQ</td>\n",
+       "      <td>44722.25</td>\n",
+       "      <td>Rv3875</td>\n",
+       "      <td>GGSGSEAYQ</td>\n",
+       "      <td>44</td>\n",
+       "      <td>86.0</td>\n",
+       "      <td>44722.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>95.332</td>\n",
+       "      <td>70.000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>HSLLDEGKQ</td>\n",
+       "      <td>PEPLIST</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.008888</td>\n",
+       "      <td>0.000006</td>\n",
+       "      <td>HLA-B*44:03</td>\n",
+       "      <td>HSLLDEGKQ</td>\n",
+       "      <td>45415.65</td>\n",
+       "      <td>Rv3875</td>\n",
+       "      <td>HSLLDEGKQ</td>\n",
+       "      <td>26</td>\n",
+       "      <td>87.0</td>\n",
+       "      <td>45415.65</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
+       "<p>2994 rows × 20 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "      peptide  pos     name  alleles       core    score      mean  median_rank\n",
-       "70  VTSIHSLLD   22   Rv3875        3  VTSIHSLLD  3347.32  5387.370          3.0\n",
-       "24  HTAGVDLAK   70  Rv3615c        2  HTAGVDLAK   100.19  4114.370          1.5\n",
-       "59  SSAMILAAY  170  Rv1886c        2  SSAMILAAY    26.88  1057.660          2.5\n",
-       "61  SVAITHGPY   39  Rv3615c        2  SVAITHGPY  1713.29  2833.760          2.5\n",
-       "4   AIQGNVTSI   17   Rv3875        2  AIQGNVTSI  1410.10  3128.155          3.0"
+       "     %Rank_BA  %Rank_EL BindLevel  Gl  Gp      Icore Identity  Il  Ip  Of  Score_BA  Score_EL  \\\n",
+       "114     0.064     0.248        <=   0   0  QSSFYSDWY  PEPLIST   0   0   0  0.608571  0.550058   \n",
+       "93      0.090     0.173        <=   0   0  NTPAFEWYY  PEPLIST   0   0   0  0.567313  0.661575   \n",
+       "169     0.095     0.201        <=   0   0  SSAMILAAY  PEPLIST   0   0   0  0.562260  0.624424   \n",
+       "118     0.624     1.533        <=   0   0  YSDWYSPAC  PEPLIST   0   0   0  0.321390  0.076134   \n",
+       "205     0.943     1.204        <=   0   0  LAMGDAGGY  PEPLIST   0   0   0  0.268694  0.111025   \n",
+       "..        ...       ...       ...  ..  ..        ...      ...  ..  ..  ..       ...       ...   \n",
+       "52     78.734    43.500       NaN   0   0  GVQQKWDAT  PEPLIST   0   0   0  0.015567  0.000028   \n",
+       "46     88.447    80.000       NaN   0   0  GSEAYQGVQ  PEPLIST   0   0   0  0.012250  0.000003   \n",
+       "28     90.081    37.333       NaN   0   0  LDEGKQSLT  PEPLIST   0   0   0  0.011645  0.000042   \n",
+       "43     93.171    70.000       NaN   0   0  GGSGSEAYQ  PEPLIST   0   0   0  0.010310  0.000006   \n",
+       "25     95.332    70.000       NaN   0   0  HSLLDEGKQ  PEPLIST   0   0   0  0.008888  0.000006   \n",
+       "\n",
+       "          allele       core      ic50     name    peptide  pos  rank     score  \n",
+       "114  HLA-A*01:01  QSSFYSDWY     69.07  Rv1886c  QSSFYSDWY  115   1.0     69.07  \n",
+       "93   HLA-A*01:01  NTPAFEWYY    107.94  Rv1886c  NTPAFEWYY   94   2.0    107.94  \n",
+       "169  HLA-A*01:01  SSAMILAAY    114.01  Rv1886c  SSAMILAAY  170   3.0    114.01  \n",
+       "118  HLA-A*01:01  YSDWYSPAC   1544.43  Rv1886c  YSDWYSPAC  119   4.0   1544.43  \n",
+       "205  HLA-A*01:01  LAMGDAGGY   2731.40  Rv1886c  LAMGDAGGY  206   5.0   2731.40  \n",
+       "..           ...        ...       ...      ...        ...  ...   ...       ...  \n",
+       "52   HLA-B*44:03  GVQQKWDAT  42249.46   Rv3875  GVQQKWDAT   53  83.0  42249.46  \n",
+       "46   HLA-B*44:03  GSEAYQGVQ  43793.29   Rv3875  GSEAYQGVQ   47  84.0  43793.29  \n",
+       "28   HLA-B*44:03  LDEGKQSLT  44080.89   Rv3875  LDEGKQSLT   29  85.0  44080.89  \n",
+       "43   HLA-B*44:03  GGSGSEAYQ  44722.25   Rv3875  GGSGSEAYQ   44  86.0  44722.25  \n",
+       "25   HLA-B*44:03  HSLLDEGKQ  45415.65   Rv3875  HSLLDEGKQ   26  87.0  45415.65  \n",
+       "\n",
+       "[2994 rows x 20 columns]"
       ]
      },
-     "execution_count": 46,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "source": [
-    "pb1 = P1.promiscuous_binders(n=2, cutoff=5, cutoff_method='rank')\n",
-    "pb1[:5]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## run other predictors"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "reload(base)\n",
     "P2 = base.get_predictor('netmhcpan')\n",
@@ -859,7 +1086,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -867,6 +1094,12 @@
      "output_type": "stream",
      "text": [
       "name                      allele           top peptide        score\n",
+      "Rv1886c                   HLA-A*01:01      QSSFYSDWY          101.60968740437352 \n",
+      "Rv1886c                   HLA-A*02:01      LMIGTAAAV          16.43169597457016 \n",
+      "Rv1886c                   HLA-A*03:01      AMGDAGGYK          56.968563298042575 \n",
+      "Rv1886c                   HLA-A*24:02      IYAGSLSAL          41.91324793746497 \n",
+      "Rv1886c                   HLA-B*07:02      GPSLIGLAM          39.6257950091114 \n",
+      "Rv1886c                   HLA-B*44:03      WETFLTSEL          166.67921521067566 \n",
       "Rv3615c                   HLA-A*01:01      QFNDTLNVY          804.3360154563782 \n",
       "Rv3615c                   HLA-A*02:01      ALGSSLHTA          31.665793785308146 \n",
       "Rv3615c                   HLA-A*03:01      HTAGVDLAK          87.12363499233405 \n",
@@ -879,7 +1112,7 @@
       "Rv3875                    HLA-A*24:02      AYQGVQQKW          44.24060698145829 \n",
       "Rv3875                    HLA-B*07:02      KWDATATEL          133.10928532097978 \n",
       "Rv3875                    HLA-B*44:03      TEGNVTGMF          56.09849773391828 \n",
-      "predictions done for 2 sequences in 6 alleles\n"
+      "predictions done for 3 sequences in 6 alleles\n"
      ]
     },
     {
@@ -918,74 +1151,74 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>49</th>\n",
+       "      <th>114</th>\n",
        "      <td>HLA-A*01:01</td>\n",
-       "      <td>804.336015</td>\n",
-       "      <td>0.745250</td>\n",
-       "      <td>2.261060</td>\n",
-       "      <td>0.146280</td>\n",
-       "      <td>0.115985</td>\n",
-       "      <td>Rv3615c</td>\n",
-       "      <td>QFNDTLNVY</td>\n",
-       "      <td>50</td>\n",
+       "      <td>101.609687</td>\n",
+       "      <td>0.139250</td>\n",
+       "      <td>0.808750</td>\n",
+       "      <td>0.505567</td>\n",
+       "      <td>0.052885</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>QSSFYSDWY</td>\n",
+       "      <td>115</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>804.336015</td>\n",
+       "      <td>101.609687</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>50</th>\n",
+       "      <th>93</th>\n",
        "      <td>HLA-A*01:01</td>\n",
-       "      <td>899.918141</td>\n",
-       "      <td>0.800625</td>\n",
-       "      <td>1.832636</td>\n",
-       "      <td>0.200953</td>\n",
-       "      <td>0.255270</td>\n",
-       "      <td>Rv3615c</td>\n",
-       "      <td>FNDTLNVYL</td>\n",
-       "      <td>51</td>\n",
+       "      <td>175.248959</td>\n",
+       "      <td>0.246500</td>\n",
+       "      <td>0.685408</td>\n",
+       "      <td>0.565139</td>\n",
+       "      <td>0.270296</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>NTPAFEWYY</td>\n",
+       "      <td>94</td>\n",
        "      <td>2.0</td>\n",
-       "      <td>899.918141</td>\n",
+       "      <td>175.248959</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>38</th>\n",
+       "      <th>169</th>\n",
        "      <td>HLA-A*01:01</td>\n",
-       "      <td>1196.684045</td>\n",
-       "      <td>0.945000</td>\n",
-       "      <td>2.587527</td>\n",
-       "      <td>0.119575</td>\n",
-       "      <td>0.159381</td>\n",
-       "      <td>Rv3615c</td>\n",
-       "      <td>SVAITHGPY</td>\n",
-       "      <td>39</td>\n",
+       "      <td>230.323815</td>\n",
+       "      <td>0.310625</td>\n",
+       "      <td>0.761630</td>\n",
+       "      <td>0.527871</td>\n",
+       "      <td>0.302801</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>SSAMILAAY</td>\n",
+       "      <td>170</td>\n",
        "      <td>3.0</td>\n",
-       "      <td>1196.684045</td>\n",
+       "      <td>230.323815</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>86</th>\n",
+       "      <th>205</th>\n",
        "      <td>HLA-A*01:01</td>\n",
-       "      <td>1998.165524</td>\n",
-       "      <td>1.246125</td>\n",
-       "      <td>5.449429</td>\n",
-       "      <td>0.046052</td>\n",
-       "      <td>0.007781</td>\n",
-       "      <td>Rv3615c</td>\n",
-       "      <td>YSEADEAWR</td>\n",
-       "      <td>87</td>\n",
+       "      <td>631.349649</td>\n",
+       "      <td>0.644625</td>\n",
+       "      <td>2.202255</td>\n",
+       "      <td>0.152359</td>\n",
+       "      <td>0.063034</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>LAMGDAGGY</td>\n",
+       "      <td>206</td>\n",
        "      <td>4.0</td>\n",
-       "      <td>1998.165524</td>\n",
+       "      <td>631.349649</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>88</th>\n",
+       "      <th>92</th>\n",
        "      <td>HLA-A*01:01</td>\n",
-       "      <td>4983.969685</td>\n",
-       "      <td>2.072250</td>\n",
-       "      <td>4.047908</td>\n",
-       "      <td>0.065828</td>\n",
-       "      <td>0.365604</td>\n",
-       "      <td>Rv3615c</td>\n",
-       "      <td>EADEAWRKA</td>\n",
-       "      <td>89</td>\n",
+       "      <td>990.540634</td>\n",
+       "      <td>0.843250</td>\n",
+       "      <td>2.778451</td>\n",
+       "      <td>0.107109</td>\n",
+       "      <td>0.072385</td>\n",
+       "      <td>Rv1886c</td>\n",
+       "      <td>INTPAFEWY</td>\n",
+       "      <td>93</td>\n",
        "      <td>5.0</td>\n",
-       "      <td>4983.969685</td>\n",
+       "      <td>990.540634</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -1073,53 +1306,53 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>1092 rows × 11 columns</p>\n",
+       "<p>2994 rows × 11 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "         allele  mhcflurry_affinity  mhcflurry_affinity_percentile  \\\n",
-       "49  HLA-A*01:01          804.336015                       0.745250   \n",
-       "50  HLA-A*01:01          899.918141                       0.800625   \n",
-       "38  HLA-A*01:01         1196.684045                       0.945000   \n",
-       "86  HLA-A*01:01         1998.165524                       1.246125   \n",
-       "88  HLA-A*01:01         4983.969685                       2.072250   \n",
-       "..          ...                 ...                            ...   \n",
-       "18  HLA-B*44:03        32259.021322                      40.329625   \n",
-       "52  HLA-B*44:03        32465.619160                      46.498875   \n",
-       "35  HLA-B*44:03        32688.080557                      46.498875   \n",
-       "37  HLA-B*44:03        32939.261826                      53.881750   \n",
-       "4   HLA-B*44:03        32984.599702                      53.881750   \n",
+       "          allele  mhcflurry_affinity  mhcflurry_affinity_percentile  \\\n",
+       "114  HLA-A*01:01          101.609687                       0.139250   \n",
+       "93   HLA-A*01:01          175.248959                       0.246500   \n",
+       "169  HLA-A*01:01          230.323815                       0.310625   \n",
+       "205  HLA-A*01:01          631.349649                       0.644625   \n",
+       "92   HLA-A*01:01          990.540634                       0.843250   \n",
+       "..           ...                 ...                            ...   \n",
+       "18   HLA-B*44:03        32259.021322                      40.329625   \n",
+       "52   HLA-B*44:03        32465.619160                      46.498875   \n",
+       "35   HLA-B*44:03        32688.080557                      46.498875   \n",
+       "37   HLA-B*44:03        32939.261826                      53.881750   \n",
+       "4    HLA-B*44:03        32984.599702                      53.881750   \n",
        "\n",
-       "    mhcflurry_presentation_percentile  mhcflurry_presentation_score  mhcflurry_processing_score  \\\n",
-       "49                           2.261060                      0.146280                    0.115985   \n",
-       "50                           1.832636                      0.200953                    0.255270   \n",
-       "38                           2.587527                      0.119575                    0.159381   \n",
-       "86                           5.449429                      0.046052                    0.007781   \n",
-       "88                           4.047908                      0.065828                    0.365604   \n",
-       "..                                ...                           ...                         ...   \n",
-       "18                          99.286603                      0.003155                    0.001343   \n",
-       "52                          99.286603                      0.003217                    0.008599   \n",
-       "35                          99.286603                      0.003116                    0.001443   \n",
-       "37                          99.286603                      0.003113                    0.003266   \n",
-       "4                           62.744674                      0.004964                    0.136014   \n",
+       "     mhcflurry_presentation_percentile  mhcflurry_presentation_score  mhcflurry_processing_score  \\\n",
+       "114                           0.808750                      0.505567                    0.052885   \n",
+       "93                            0.685408                      0.565139                    0.270296   \n",
+       "169                           0.761630                      0.527871                    0.302801   \n",
+       "205                           2.202255                      0.152359                    0.063034   \n",
+       "92                            2.778451                      0.107109                    0.072385   \n",
+       "..                                 ...                           ...                         ...   \n",
+       "18                           99.286603                      0.003155                    0.001343   \n",
+       "52                           99.286603                      0.003217                    0.008599   \n",
+       "35                           99.286603                      0.003116                    0.001443   \n",
+       "37                           99.286603                      0.003113                    0.003266   \n",
+       "4                            62.744674                      0.004964                    0.136014   \n",
        "\n",
-       "       name    peptide  pos  rank         score  \n",
-       "49  Rv3615c  QFNDTLNVY   50   1.0    804.336015  \n",
-       "50  Rv3615c  FNDTLNVYL   51   2.0    899.918141  \n",
-       "38  Rv3615c  SVAITHGPY   39   3.0   1196.684045  \n",
-       "86  Rv3615c  YSEADEAWR   87   4.0   1998.165524  \n",
-       "88  Rv3615c  EADEAWRKA   89   5.0   4983.969685  \n",
-       "..      ...        ...  ...   ...           ...  \n",
-       "18   Rv3875  QGNVTSIHS   19  83.0  32259.021322  \n",
-       "52   Rv3875  GVQQKWDAT   53  84.0  32465.619160  \n",
-       "35   Rv3875  LTKLAAAWG   36  85.0  32688.080557  \n",
-       "37   Rv3875  KLAAAWGGS   38  86.0  32939.261826  \n",
-       "4    Rv3875  QWNFAGIEA    5  87.0  32984.599702  \n",
+       "        name    peptide  pos  rank         score  \n",
+       "114  Rv1886c  QSSFYSDWY  115   1.0    101.609687  \n",
+       "93   Rv1886c  NTPAFEWYY   94   2.0    175.248959  \n",
+       "169  Rv1886c  SSAMILAAY  170   3.0    230.323815  \n",
+       "205  Rv1886c  LAMGDAGGY  206   4.0    631.349649  \n",
+       "92   Rv1886c  INTPAFEWY   93   5.0    990.540634  \n",
+       "..       ...        ...  ...   ...           ...  \n",
+       "18    Rv3875  QGNVTSIHS   19  83.0  32259.021322  \n",
+       "52    Rv3875  GVQQKWDAT   53  84.0  32465.619160  \n",
+       "35    Rv3875  LTKLAAAWG   36  85.0  32688.080557  \n",
+       "37    Rv3875  KLAAAWGGS   38  86.0  32939.261826  \n",
+       "4     Rv3875  QWNFAGIEA    5  87.0  32984.599702  \n",
        "\n",
-       "[1092 rows x 11 columns]"
+       "[2994 rows x 11 columns]"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1132,7 +1365,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1159,20 +1392,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/damien/gitprojects/epitopepredict/epitopepredict/base.py:695: SettingWithCopyWarning: \n",
+      "/home/damien/gitprojects/epitopepredict/epitopepredict/base.py:700: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
       "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
       "  binders['core'] = binders.peptide\n",
-      "/home/damien/gitprojects/epitopepredict/epitopepredict/base.py:695: SettingWithCopyWarning: \n",
+      "/home/damien/gitprojects/epitopepredict/epitopepredict/base.py:700: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
@@ -1182,7 +1415,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -1209,26 +1442,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Rv3615c', 'Rv3875']\n"
+      "['Rv1886c', 'Rv3615c', 'Rv3875']\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 720x288 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1238,389 +1469,16 @@
     "print (P2.get_names())\n",
     "ax = plotting.plot_tracks([P1,P2,P3],name='Rv3875',cutoff=5,cutoff_method='rank',n=2,legend=True)\n",
     "plt.tight_layout()\n",
-    "plt.savefig('comparison_rv3875.png',dpi=150)\n",
+    "plt.savefig('comparison_rv3875.png',dpi=300)\n",
     "#ax = plotting.plot_binder_map(P1,name='Rv0011c',cutoff=10)\n",
     "#plt.savefig('mhc_rv0011c_map.png',dpi=150)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "    <div class=\"bk-root\">\n",
-       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
-       "        <span id=\"2361\">Loading BokehJS ...</span>\n",
-       "    </div>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "\n",
-       "(function(root) {\n",
-       "  function now() {\n",
-       "    return new Date();\n",
-       "  }\n",
-       "\n",
-       "  var force = true;\n",
-       "\n",
-       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
-       "    root._bokeh_onload_callbacks = [];\n",
-       "    root._bokeh_is_loading = undefined;\n",
-       "  }\n",
-       "\n",
-       "  var JS_MIME_TYPE = 'application/javascript';\n",
-       "  var HTML_MIME_TYPE = 'text/html';\n",
-       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
-       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
-       "\n",
-       "  /**\n",
-       "   * Render data to the DOM node\n",
-       "   */\n",
-       "  function render(props, node) {\n",
-       "    var script = document.createElement(\"script\");\n",
-       "    node.appendChild(script);\n",
-       "  }\n",
-       "\n",
-       "  /**\n",
-       "   * Handle when an output is cleared or removed\n",
-       "   */\n",
-       "  function handleClearOutput(event, handle) {\n",
-       "    var cell = handle.cell;\n",
-       "\n",
-       "    var id = cell.output_area._bokeh_element_id;\n",
-       "    var server_id = cell.output_area._bokeh_server_id;\n",
-       "    // Clean up Bokeh references\n",
-       "    if (id != null && id in Bokeh.index) {\n",
-       "      Bokeh.index[id].model.document.clear();\n",
-       "      delete Bokeh.index[id];\n",
-       "    }\n",
-       "\n",
-       "    if (server_id !== undefined) {\n",
-       "      // Clean up Bokeh references\n",
-       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
-       "      cell.notebook.kernel.execute(cmd, {\n",
-       "        iopub: {\n",
-       "          output: function(msg) {\n",
-       "            var id = msg.content.text.trim();\n",
-       "            if (id in Bokeh.index) {\n",
-       "              Bokeh.index[id].model.document.clear();\n",
-       "              delete Bokeh.index[id];\n",
-       "            }\n",
-       "          }\n",
-       "        }\n",
-       "      });\n",
-       "      // Destroy server and session\n",
-       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
-       "      cell.notebook.kernel.execute(cmd);\n",
-       "    }\n",
-       "  }\n",
-       "\n",
-       "  /**\n",
-       "   * Handle when a new output is added\n",
-       "   */\n",
-       "  function handleAddOutput(event, handle) {\n",
-       "    var output_area = handle.output_area;\n",
-       "    var output = handle.output;\n",
-       "\n",
-       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
-       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
-       "      return\n",
-       "    }\n",
-       "\n",
-       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
-       "\n",
-       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
-       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
-       "      // store reference to embed id on output_area\n",
-       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
-       "    }\n",
-       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
-       "      var bk_div = document.createElement(\"div\");\n",
-       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
-       "      var script_attrs = bk_div.children[0].attributes;\n",
-       "      for (var i = 0; i < script_attrs.length; i++) {\n",
-       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
-       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
-       "      }\n",
-       "      // store reference to server id on output_area\n",
-       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
-       "    }\n",
-       "  }\n",
-       "\n",
-       "  function register_renderer(events, OutputArea) {\n",
-       "\n",
-       "    function append_mime(data, metadata, element) {\n",
-       "      // create a DOM node to render to\n",
-       "      var toinsert = this.create_output_subarea(\n",
-       "        metadata,\n",
-       "        CLASS_NAME,\n",
-       "        EXEC_MIME_TYPE\n",
-       "      );\n",
-       "      this.keyboard_manager.register_events(toinsert);\n",
-       "      // Render to node\n",
-       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
-       "      render(props, toinsert[toinsert.length - 1]);\n",
-       "      element.append(toinsert);\n",
-       "      return toinsert\n",
-       "    }\n",
-       "\n",
-       "    /* Handle when an output is cleared or removed */\n",
-       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
-       "    events.on('delete.Cell', handleClearOutput);\n",
-       "\n",
-       "    /* Handle when a new output is added */\n",
-       "    events.on('output_added.OutputArea', handleAddOutput);\n",
-       "\n",
-       "    /**\n",
-       "     * Register the mime type and append_mime function with output_area\n",
-       "     */\n",
-       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
-       "      /* Is output safe? */\n",
-       "      safe: true,\n",
-       "      /* Index of renderer in `output_area.display_order` */\n",
-       "      index: 0\n",
-       "    });\n",
-       "  }\n",
-       "\n",
-       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
-       "  if (root.Jupyter !== undefined) {\n",
-       "    var events = require('base/js/events');\n",
-       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
-       "\n",
-       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
-       "      register_renderer(events, OutputArea);\n",
-       "    }\n",
-       "  }\n",
-       "\n",
-       "  \n",
-       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
-       "    root._bokeh_timeout = Date.now() + 5000;\n",
-       "    root._bokeh_failed_load = false;\n",
-       "  }\n",
-       "\n",
-       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
-       "     \"<div style='background-color: #fdd'>\\n\"+\n",
-       "     \"<p>\\n\"+\n",
-       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
-       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
-       "     \"</p>\\n\"+\n",
-       "     \"<ul>\\n\"+\n",
-       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
-       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
-       "     \"</ul>\\n\"+\n",
-       "     \"<code>\\n\"+\n",
-       "     \"from bokeh.resources import INLINE\\n\"+\n",
-       "     \"output_notebook(resources=INLINE)\\n\"+\n",
-       "     \"</code>\\n\"+\n",
-       "     \"</div>\"}};\n",
-       "\n",
-       "  function display_loaded() {\n",
-       "    var el = document.getElementById(\"2361\");\n",
-       "    if (el != null) {\n",
-       "      el.textContent = \"BokehJS is loading...\";\n",
-       "    }\n",
-       "    if (root.Bokeh !== undefined) {\n",
-       "      if (el != null) {\n",
-       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
-       "      }\n",
-       "    } else if (Date.now() < root._bokeh_timeout) {\n",
-       "      setTimeout(display_loaded, 100)\n",
-       "    }\n",
-       "  }\n",
-       "\n",
-       "\n",
-       "  function run_callbacks() {\n",
-       "    try {\n",
-       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
-       "        if (callback != null)\n",
-       "          callback();\n",
-       "      });\n",
-       "    } finally {\n",
-       "      delete root._bokeh_onload_callbacks\n",
-       "    }\n",
-       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
-       "  }\n",
-       "\n",
-       "  function load_libs(css_urls, js_urls, callback) {\n",
-       "    if (css_urls == null) css_urls = [];\n",
-       "    if (js_urls == null) js_urls = [];\n",
-       "\n",
-       "    root._bokeh_onload_callbacks.push(callback);\n",
-       "    if (root._bokeh_is_loading > 0) {\n",
-       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
-       "      return null;\n",
-       "    }\n",
-       "    if (js_urls == null || js_urls.length === 0) {\n",
-       "      run_callbacks();\n",
-       "      return null;\n",
-       "    }\n",
-       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
-       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
-       "\n",
-       "    function on_load() {\n",
-       "      root._bokeh_is_loading--;\n",
-       "      if (root._bokeh_is_loading === 0) {\n",
-       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
-       "        run_callbacks()\n",
-       "      }\n",
-       "    }\n",
-       "\n",
-       "    function on_error() {\n",
-       "      console.error(\"failed to load \" + url);\n",
-       "    }\n",
-       "\n",
-       "    for (var i = 0; i < css_urls.length; i++) {\n",
-       "      var url = css_urls[i];\n",
-       "      const element = document.createElement(\"link\");\n",
-       "      element.onload = on_load;\n",
-       "      element.onerror = on_error;\n",
-       "      element.rel = \"stylesheet\";\n",
-       "      element.type = \"text/css\";\n",
-       "      element.href = url;\n",
-       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
-       "      document.body.appendChild(element);\n",
-       "    }\n",
-       "\n",
-       "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n",
-       "\n",
-       "    for (var i = 0; i < js_urls.length; i++) {\n",
-       "      var url = js_urls[i];\n",
-       "      var element = document.createElement('script');\n",
-       "      element.onload = on_load;\n",
-       "      element.onerror = on_error;\n",
-       "      element.async = false;\n",
-       "      element.src = url;\n",
-       "      if (url in hashes) {\n",
-       "        element.crossOrigin = \"anonymous\";\n",
-       "        element.integrity = \"sha384-\" + hashes[url];\n",
-       "      }\n",
-       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
-       "      document.head.appendChild(element);\n",
-       "    }\n",
-       "  };\n",
-       "\n",
-       "  function inject_raw_css(css) {\n",
-       "    const element = document.createElement(\"style\");\n",
-       "    element.appendChild(document.createTextNode(css));\n",
-       "    document.body.appendChild(element);\n",
-       "  }\n",
-       "\n",
-       "  \n",
-       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n",
-       "  var css_urls = [];\n",
-       "  \n",
-       "\n",
-       "  var inline_js = [\n",
-       "    function(Bokeh) {\n",
-       "      Bokeh.set_log_level(\"info\");\n",
-       "    },\n",
-       "    function(Bokeh) {\n",
-       "    \n",
-       "    \n",
-       "    }\n",
-       "  ];\n",
-       "\n",
-       "  function run_inline_js() {\n",
-       "    \n",
-       "    if (root.Bokeh !== undefined || force === true) {\n",
-       "      \n",
-       "    for (var i = 0; i < inline_js.length; i++) {\n",
-       "      inline_js[i].call(root, root.Bokeh);\n",
-       "    }\n",
-       "    if (force === true) {\n",
-       "        display_loaded();\n",
-       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
-       "      setTimeout(run_inline_js, 100);\n",
-       "    } else if (!root._bokeh_failed_load) {\n",
-       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
-       "      root._bokeh_failed_load = true;\n",
-       "    } else if (force !== true) {\n",
-       "      var cell = $(document.getElementById(\"2361\")).parents('.cell').data().cell;\n",
-       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
-       "    }\n",
-       "\n",
-       "  }\n",
-       "\n",
-       "  if (root._bokeh_is_loading === 0) {\n",
-       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
-       "    run_inline_js();\n",
-       "  } else {\n",
-       "    load_libs(css_urls, js_urls, function() {\n",
-       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
-       "      run_inline_js();\n",
-       "    });\n",
-       "  }\n",
-       "}(window));"
-      ],
-      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"2361\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"2361\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
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-     "metadata": {},
-     "output_type": "display_data"
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-       "(function(root) {\n",
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{\"db791cf9-acd6-4d2f-80ef-170cc133c73d\":{\"roots\":{\"references\":[{\"attributes\":{\"background_fill_alpha\":0.5,\"background_fill_color\":\"#fafaf4\",\"below\":[{\"id\":\"2373\"}],\"center\":[{\"id\":\"2376\"},{\"id\":\"2380\"},{\"id\":\"2405\"}],\"left\":[{\"id\":\"2377\"}],\"min_border\":10,\"plot_height\":330,\"plot_width\":800,\"renderers\":[{\"id\":\"2396\"}],\"sizing_mode\":\"fixed\",\"title\":{\"id\":\"2365\"},\"toolbar\":{\"id\":\"2386\"},\"x_range\":{\"id\":\"2362\"},\"x_scale\":{\"id\":\"2369\"},\"y_range\":{\"id\":\"2363\"},\"y_scale\":{\"id\":\"2371\"}},\"id\":\"2364\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"axis\":{\"id\":\"2373\"},\"minor_grid_line_alpha\":0.1,\"minor_grid_line_color\":\"gray\",\"ticker\":null},\"id\":\"2376\",\"type\":\"Grid\"},{\"attributes\":{\"index\":0,\"label\":{\"value\":\"basicmhc1\"},\"renderers\":[{\"id\":\"2396\"}]},\"id\":\"2406\",\"type\":\"LegendItem\"},{\"attributes\":{\"data\":{\"allele\":[\"HLA-A*01:01\",\"HLA-A*01:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-B*07:02\",\"HLA-B*07:02\",\"HLA-B*07:02\",\"HLA-B*44:03\",\"HLA-B*44:03\",\"HLA-B*44:03\",\"HLA-B*44:03\",\"HLA-A*01:01\",\"HLA-A*01:01\",\"HLA-A*01:01\",\"HLA-A*01:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*03:01\",\"HLA-A*03:01\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-B*07:02\",\"HLA-A*01:01\",\"HLA-A*01:01\",\"HLA-A*01:01\",\"HLA-A*01:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*02:01\",\"HLA-A*03:01\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-A*24:02\",\"HLA-B*07:02\",\"HLA-B*07:02\",\"HLA-B*44:03\"],\"color\":[\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#e41a1c\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#984ea3\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\",\"#ff7f00\"],\"peptide\":[\"ERLTRGLAY\",\"YSAVGPVDV\",\"LAYSAVGPV\",\"YSAVGPVDV\",\"AAQDVVANL\",\"VVANLPQAL\",\"YSAVGPVDV\",\"VVANLPQAL\",\"RSKHHLWIF\",\"ILAGGAVAF\",\"AGGAVAFSI\",\"LAYSAVGPV\",\"VVANLPQAL\",\"ILAGGAVAF\",\"ERLTRGLAY\",\"AAQDVVANL\",\"RSKHHLWIF\",\"AGGAVAFSI\",\"LAYSAVGPV\",\"RSTAAGLRR\",\"RSKHHLWIF\",\"ILAGGAVAF\",\"LAYSAVGPV\",\"IFAGIAAAI\",\"ILAGGAVAF\",\"RSTAAGLRR\",\"RYREGRLAR\",\"RYREGRLAR\",\"RSKHHLWIF\",\"IFAGIAAAI\",\"ILAGGAVAF\",\"LAYSAVGPV\",\"AVGPVDVTR\",\"AAQDVVANL\",\"RSKHHLWIF\",\"ILAGGAVAF\",\"GLLELGVGL\",\"AAQDVVANL\",\"VVANLPQAL\",\"ILAGGAVAF\",\"AVGPVDVTR\",\"GLLELGVGL\",\"AAQDVVANL\",\"VVANLPQAL\",\"QRRSKHHLW\",\"RSKHHLWIF\",\"ILAGGAVAF\",\"AAQDVVANL\",\"VVANLPQAL\",\"QRRSKHHLW\"],\"position\":[13,21,19,21,78,82,21,82,98,113,115,19,82,113,13,78,98,115,19,46,98,113,19,105,113,46,55,55,98,105,113,19,23,78,98,113,32,78,82,113,23,32,78,82,96,98,113,78,82,96],\"predictor\":[\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"basicmhc1\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"netmhcpan\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\",\"mhcflurry\"],\"score\":[14738.6,4062.65,1213.2,2141.07,1569.53,2028.31,6740.94,9499.0,8.98,2202.15,6625.25,3205.54,710.13,2978.16,13812.19,14175.55,11172.82,12804.71,22947.14,23160.42,17010.16,19558.24,1064.87,3376.82,1814.78,2553.65,8420.74,16169.21,719.11,822.8,3651.67,4113.82,14684.299462237856,13812.895693075747,9099.941264068006,12721.675858553886,28.414423836679394,428.50986843986124,665.6318629565172,1024.9540021558537,334.06805514409257,11930.927526131696,9208.092869684991,5541.5187672263355,10428.427578475717,496.8889058706845,377.6411072124089,863.697130278146,152.84382822506717,7801.966093162864],\"width\":[9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9],\"x\":[17.5,25.5,23.5,25.5,82.5,86.5,25.5,86.5,102.5,117.5,119.5,23.5,86.5,117.5,17.5,82.5,102.5,119.5,23.5,50.5,102.5,117.5,23.5,109.5,117.5,50.5,59.5,59.5,102.5,109.5,117.5,23.5,27.5,82.5,102.5,117.5,36.5,82.5,86.5,117.5,27.5,36.5,82.5,86.5,100.5,102.5,117.5,82.5,86.5,100.5],\"y\":[3.5,3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-       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "\n",
-       "  }\n",
-       "  if (root.Bokeh !== undefined) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (root.Bokeh !== undefined) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else {\n",
-       "        attempts++;\n",
-       "        if (attempts > 100) {\n",
-       "          clearInterval(timer);\n",
-       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
-       "        }\n",
-       "      }\n",
-       "    }, 10, root)\n",
-       "  }\n",
-       "})(window);"
-      ],
-      "application/vnd.bokehjs_exec.v0+json": ""
-     },
-     "metadata": {
-      "application/vnd.bokehjs_exec.v0+json": {
-       "id": "2364"
-      }
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "reload(plotting)\n",
     "from bokeh.io import show, output_notebook\n",
diff --git a/examples/mtb_sa_sette.ipynb b/examples/mtb_sa_sette.ipynb
index 27fc6a1..1ea1ae3 100644
--- a/examples/mtb_sa_sette.ipynb
+++ b/examples/mtb_sa_sette.ipynb
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 125,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -31,7 +31,7 @@
     "from IPython.display import display, HTML\n",
     "import seaborn as sns\n",
     "from importlib import reload\n",
-    "sns.set_style(\"ticks\", {'axes.facecolor': '#F7F7F7', 'axes.grid': False,\n",
+    "sns.set_style(\"ticks\", {'axes.facecolor': 'white', 'axes.grid': False,\n",
     "                        'legend.frameon':True, 'legend.fontsize':12})\n",
     "sns.set_context(\"notebook\", font_scale=1.4)"
    ]
@@ -45,17 +45,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 104,
    "metadata": {
     "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "75"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "#sette mtb epitopes\n",
     "sette = pd.read_csv('sette_SA_MTB_epitopes.csv')\n",
+    "sette.name.unique()\n",
+    "len(sette)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "proteins = sorted(sette.name.unique())\n",
     "mtb = sequtils.genbank_to_dataframe(base.mtb_genome,cds=True)\n",
     "mtb = mtb[mtb.locus_tag.isin(sette.name)]\n",
@@ -107,7 +128,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 83,
    "metadata": {
     "collapsed": false,
     "jupyter": {
@@ -121,6 +142,7 @@
      "text": [
       "predictions done for 29 sequences in 27 alleles\n",
       "results saved to /home/damien/gitprojects/epitopepredict/examples/mtbsa_tepitope\n",
+      "took 447.051 seconds\n",
       "predictions done for 29 sequences in 27 alleles\n",
       "results saved to /home/damien/gitprojects/epitopepredict/examples/mtbsa_netmhciipan\n"
      ]
@@ -128,44 +150,55 @@
    ],
    "source": [
     "Pt=ep.get_predictor('tepitope')\n",
-    "Pt.predict_sequences(mtb, alleles=drballeles,path='mtbsa_tepitope', overwrite=False, threads=10)\n",
+    "Pt.predict_sequences(mtb, alleles=drballeles,path='mtbsa_tepitope', length=15, overwrite=False, threads=10)\n",
     "Pt.load(path='mtbsa_tepitope')\n",
     "Pn=ep.get_predictor('netmhciipan')\n",
-    "Pn.predict_sequences(mtb, alleles=drballeles,path='mtbsa_netmhciipan', overwrite=False, threads=10)\n",
+    "Pn.predict_sequences(mtb, alleles=drballeles,path='mtbsa_netmhciipan', length=15, overwrite=False, threads=10)\n",
     "Pn.load(path='mtbsa_netmhciipan')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    }
-   },
+   "execution_count": 157,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['Rv0124', 'Rv0125', 'Rv0129c', 'Rv0256c', 'Rv0280', 'Rv0288', 'Rv1047', 'Rv1172c', 'Rv1195', 'Rv1196', 'Rv1705c', 'Rv1886c', 'Rv1908c', 'Rv1926c', 'Rv2031c', 'Rv2608', 'Rv2770c', 'Rv3024c', 'Rv3025c', 'Rv3136', 'Rv3330', 'Rv3615c', 'Rv3619c', 'Rv3620c', 'Rv3804c', 'Rv3873', 'Rv3874', 'Rv3875', 'Rv3876']\n"
+      "9299.0\n",
+      "9299\n",
+      "27\n",
+      "['HLA-DRB3*0202' 'HLA-DRB4*0101' 'HLA-DRB3*0101' 'HLA-DRB4*0103'\n",
+      " 'HLA-DRB1*0401' 'HLA-DRB1*0301' 'HLA-DRB5*0101' 'HLA-DRB1*0701'\n",
+      " 'HLA-DRB3*0301' 'HLA-DRB1*1301' 'HLA-DRB1*1503' 'HLA-DRB1*0302'\n",
+      " 'HLA-DRB1*1101' 'HLA-DRB1*1201' 'HLA-DRB1*0101' 'HLA-DRB1*0404'\n",
+      " 'HLA-DRB1*0405' 'HLA-DRB1*1501' 'HLA-DRB1*1502' 'HLA-DRB1*1202'\n",
+      " 'HLA-DRB1*1303' 'HLA-DRB1*1404' 'HLA-DRB1*1302' 'HLA-DRB1*0102'\n",
+      " 'HLA-DRB5*0102' 'HLA-DRB1*1114' 'HLA-DRB1*1102']\n"
      ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1008x720 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
     }
    ],
+   "source": [
+    "print (len(Pn.data)/27)\n",
+    "print (Pn.data.allele.value_counts()[0])\n",
+    "print (len(Pn.data.allele.unique()))\n",
+    "print (Pn.data.allele.unique())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    }
+   },
+   "outputs": [],
    "source": [
     "print (proteins)\n",
-    "ax = plotting.plot_tracks([Pn,Pt],name=proteins[-3],\n",
+    "ax = plotting.plot_tracks([Pn,Pt],name='Rv1196',\n",
     "                     n=5, cutoff=10, kind='tracks',                   \n",
     "                     legend=True, cutoff_method='rank',            \n",
     "                     figsize=(14,10))\n"
@@ -180,12 +213,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 84,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 288x288 with 1 Axes>"
       ]
@@ -209,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 85,
    "metadata": {
     "collapsed": false,
     "jupyter": {
@@ -219,7 +252,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 288x288 with 1 Axes>"
       ]
@@ -235,134 +268,67 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    }
-   },
-   "outputs": [],
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "#compare to exp results?\n",
-    "reload(analysis)\n",
-    "P=Pt\n",
-    "labels=['netmhciipan','tepitope']\n",
-    "res=[]\n",
-    "for P in [Pn, Pt]:\n",
-    "    #binders by median rank    \n",
-    "    rb = P.promiscuous_binders(cutoff_method='rank',cutoff=30,n=5)\n",
-    "    #all binders by promiscuity, just use low perc to get all\n",
-    "    pball = P.promiscuous_binders(n=1, cutoff=0.4).sort_values(['alleles','median_rank'],ascending=False)\n",
-    "    #reload(analysis)\n",
-    "    a = analysis.prediction_coverage(exp, pball, key='sequence', perc=50)\n",
-    "    print (a)\n",
-    "    b = analysis.prediction_coverage(exp, rb, key='sequence', perc=50)\n",
-    "    res.append({'all':a,'ranked':b})\n",
-    "    \n",
-    "x = pd.DataFrame(res,index=['netmhciipan','tepitope'])\n",
-    "print (x)\n",
-    "x.plot(kind='barh')\n"
+    "## find percentage coverage at given cutoff levels"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 207,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "29\n",
-      "    cutoff  len1  len2  lenb  netMHCIIpan  tepitope      both\n",
-      "0        2    67    53   118     0.233333  0.166667  0.316667\n",
-      "1        5   160   131   265     0.483333  0.433333  0.600000\n",
-      "2        8   228   189   381     0.533333  0.533333  0.700000\n",
-      "3       11   309   250   505     0.633333  0.650000  0.766667\n",
-      "4       14   375   314   623     0.700000  0.700000  0.783333\n",
-      "5       17   444   380   745     0.700000  0.716667  0.800000\n",
-      "6       20   510   442   855     0.716667  0.733333  0.833333\n",
-      "7       23   589   497   970     0.766667  0.733333  0.850000\n",
-      "8       26   662   569  1095     0.800000  0.750000  0.850000\n",
-      "9       29   737   630  1207     0.866667  0.833333  0.900000\n",
-      "10      32   795   678  1303     0.833333  0.833333  0.900000\n",
-      "11      35   856   722  1389     0.850000  0.833333  0.900000\n",
-      "12      38   921   778  1497     0.866667  0.833333  0.900000\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import difflib\n",
     "\n",
-    "def get_hits(n):\n",
-    "    cutoffs = range(2,40,3)\n",
+    "def get_hits(P,n,m,cutoffs):\n",
+    "\n",
     "    res = []\n",
+    "    print (cutoffs)\n",
     "    for c in cutoffs:\n",
-    "        rbn = Pn.promiscuous_binders(cutoff_method='rank',cutoff=c,n=n)\n",
-    "        rbt = Pt.promiscuous_binders(cutoff_method='rank',cutoff=c,n=n)\n",
-    "        rboth = pd.concat([rbn,rbt]).drop_duplicates(['peptide','name'])\n",
-    "        #print (rbt[:15])\n",
+    "        rb = P.promiscuous_binders(cutoff_method=m,cutoff=c,n=n,limit=30)\n",
     "        #print (len(rbn),len(rbt),len(rboth))\n",
     "        df=exp#[exp.name==name].copy()\n",
     "        def find_matches(x, p):\n",
     "            return len(difflib.get_close_matches(x.sequence, p, n=10, cutoff=.6))\n",
     "\n",
-    "        df.loc[:,'hits1'] = df.apply(lambda x: find_matches(x, rbn.peptide),1)        \n",
-    "        f1 = len(df[df.hits1>0])/len(df)\n",
-    "        df.loc[:,'hits2'] = df.apply(lambda x: find_matches(x, rbt.peptide),1)\n",
-    "        f2 = len(df[df.hits2>0])/len(df)\n",
+    "        df.loc[:,'hits'] = df.apply(lambda x: find_matches(x, rb.peptide),1)        \n",
+    "        f = len(df[df.hits>0])/len(df)*100\n",
     "        #print (df[:10])\n",
-    "        b = (len(df[(df.hits1>0) | (df.hits2>0)]))/len(df)\n",
-    "        res.append({'cutoff':c,'len1':len(rbn),'len2':len(rbt),'lenb':len(rboth),\n",
-    "                    'netMHCIIpan':f1, 'tepitope':f2, 'both':b})\n",
+    "        res.append({'cutoff':c,'binders':len(rb),m:f})\n",
     "    res = pd.DataFrame(res)\n",
     "    return res\n",
     "\n",
     "print (len(proteins))\n",
     "n=5\n",
-    "res = get_hits(n)\n",
-    "print (res)\n",
-    "ax=res.plot(x='len1',y='netMHCIIpan',lw=2)\n",
-    "res.plot(x='len2',y='tepitope',lw=2,ax=ax)\n",
-    "res.plot(x='lenb',y='both',lw=2,ax=ax)\n",
-    "plt.xlabel('predicted binders')\n",
-    "plt.tight_layout()\n",
-    "plt.savefig('mtb_sette_hits.png',dpi=150)"
+    "res = get_hits(Pn,n,'rank',cuts['rank'])\n",
+    "ax=res.plot(x='binders',y=['rank'],lw=2)\n",
+    "plt.tight_layout()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 205,
+   "execution_count": 175,
    "metadata": {},
    "outputs": [
     {
-     "ename": "IndexError",
-     "evalue": "index 9 is out of bounds for axis 0 with size 9",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-205-06ac4c5079b7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mn\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m15\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_hits\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m     \u001b[0mres\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'cutoff'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlw\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m     \u001b[0mi\u001b[0m\u001b[0;34m+=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mIndexError\u001b[0m: index 9 is out of bounds for axis 0 with size 9"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "range(2, 40, 3)\n",
+      "range(50, 1000, 100)\n",
+      "[0.99 0.98 0.97 0.96 0.95 0.94 0.93 0.92 0.91 0.9  0.89 0.88 0.87]\n",
+      "range(2, 40, 3)\n",
+      "[5.  4.6 4.2 3.8 3.4 3.  2.6 2.2 1.8 1.4 1.  0.6 0.2]\n",
+      "[0.99 0.98 0.97 0.96 0.95 0.94 0.93 0.92 0.91 0.9  0.89 0.88 0.87]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 864x720 with 9 Axes>"
+       "<Figure size 1008x360 with 2 Axes>"
       ]
      },
      "metadata": {},
@@ -370,177 +336,42 @@
     }
    ],
    "source": [
-    "fig,axs=plt.subplots(3,3,figsize=(12,10))\n",
+    "cuts = {'rank':range(2,40,3),'global':np.arange(.99,.86,-.01),'score':range(50,1000,100)}\n",
+    "\n",
+    "fig,axs=plt.subplots(1,2,figsize=(14,5),facecolor='white')\n",
     "axs=axs.flat\n",
     "i=0\n",
-    "for n in range(5,15):\n",
-    "    res = get_hits(n)    \n",
-    "    res.plot(x='len1',y='netMHCIIpan',lw=2,ax=axs[i])\n",
-    "    res.plot(x='len2',y='tepitope',lw=2,ax=axs[i])\n",
-    "    i+=1"
+    "['rank','global','score']\n",
+    "for P in [Pn,Pt]:    \n",
+    "    res1 = get_hits(P,5,'rank',cuts['rank'])\n",
+    "    if P.name=='tepitope':\n",
+    "        scuts = np.arange(5,0,-.4)\n",
+    "    else:\n",
+    "        scuts=cuts['score']    \n",
+    "    res2 = get_hits(P,5,'score',scuts)\n",
+    "    res3 = get_hits(P,5,'global',cuts['global'])\n",
+    "    \n",
+    "    res1.plot(x='binders',y='rank',lw=2,ax=axs[i])\n",
+    "    res2.plot(x='binders',y='score',lw=2,ax=axs[i])\n",
+    "    res3.plot(x='binders',y='global',lw=2,ax=axs[i])    \n",
+    "    axs[i].set_xlabel('no. predicted binders')\n",
+    "    axs[i].set_ylabel('% coverage')    \n",
+    "    i+=1\n",
+    "\n",
+    "axs[0].set_title('(a) netMHCIIpan',fontsize=20)\n",
+    "axs[1].set_title('(b) Tepitope',fontsize=20)\n",
+    "plt.tight_layout()\n",
+    "fig.savefig('mtb_sette_hits.png',dpi=300)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 190,
+   "execution_count": null,
    "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>peptide</th>\n",
-       "      <th>pos</th>\n",
-       "      <th>name</th>\n",
-       "      <th>alleles</th>\n",
-       "      <th>core</th>\n",
-       "      <th>score</th>\n",
-       "      <th>mean</th>\n",
-       "      <th>median_rank</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>LNNALQNLART</td>\n",
-       "      <td>65</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>25</td>\n",
-       "      <td>LNNALQNLA</td>\n",
-       "      <td>197.54</td>\n",
-       "      <td>2182.812800</td>\n",
-       "      <td>5.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>GNVTSIHSLLD</td>\n",
-       "      <td>20</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>20</td>\n",
-       "      <td>VTSIHSLLD</td>\n",
-       "      <td>420.21</td>\n",
-       "      <td>2448.403000</td>\n",
-       "      <td>3.5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>NALQNLARTIS</td>\n",
-       "      <td>67</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>19</td>\n",
-       "      <td>ALQNLARTI</td>\n",
-       "      <td>196.24</td>\n",
-       "      <td>2079.516842</td>\n",
-       "      <td>5.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>NNALQNLARTI</td>\n",
-       "      <td>66</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>18</td>\n",
-       "      <td>NNALQNLAR</td>\n",
-       "      <td>519.66</td>\n",
-       "      <td>2465.490556</td>\n",
-       "      <td>6.5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>WNFAGIEAAAS</td>\n",
-       "      <td>6</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>13</td>\n",
-       "      <td>WNFAGIEAA</td>\n",
-       "      <td>60.82</td>\n",
-       "      <td>1608.739231</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>IQGNVTSIHSL</td>\n",
-       "      <td>18</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>11</td>\n",
-       "      <td>IQGNVTSIH</td>\n",
-       "      <td>690.27</td>\n",
-       "      <td>3304.701818</td>\n",
-       "      <td>5.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>NFAGIEAAASA</td>\n",
-       "      <td>7</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>10</td>\n",
-       "      <td>FAGIEAAAS</td>\n",
-       "      <td>48.83</td>\n",
-       "      <td>1504.297000</td>\n",
-       "      <td>2.5</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>KQSLTKLAAAW</td>\n",
-       "      <td>33</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>10</td>\n",
-       "      <td>KQSLTKLAA</td>\n",
-       "      <td>263.44</td>\n",
-       "      <td>1584.218000</td>\n",
-       "      <td>5.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>QSLTKLAAAWG</td>\n",
-       "      <td>34</td>\n",
-       "      <td>Rv3875</td>\n",
-       "      <td>10</td>\n",
-       "      <td>LTKLAAAWG</td>\n",
-       "      <td>114.99</td>\n",
-       "      <td>2291.129000</td>\n",
-       "      <td>5.5</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "        peptide  pos    name  alleles       core   score         mean  median_rank\n",
-       "12  LNNALQNLART   65  Rv3875       25  LNNALQNLA  197.54  2182.812800          5.0\n",
-       "6   GNVTSIHSLLD   20  Rv3875       20  VTSIHSLLD  420.21  2448.403000          3.5\n",
-       "15  NALQNLARTIS   67  Rv3875       19  ALQNLARTI  196.24  2079.516842          5.0\n",
-       "17  NNALQNLARTI   66  Rv3875       18  NNALQNLAR  519.66  2465.490556          6.5\n",
-       "30  WNFAGIEAAAS    6  Rv3875       13  WNFAGIEAA   60.82  1608.739231          2.0\n",
-       "9   IQGNVTSIHSL   18  Rv3875       11  IQGNVTSIH  690.27  3304.701818          5.0\n",
-       "16  NFAGIEAAASA    7  Rv3875       10  FAGIEAAAS   48.83  1504.297000          2.5\n",
-       "10  KQSLTKLAAAW   33  Rv3875       10  KQSLTKLAA  263.44  1584.218000          5.0\n",
-       "23  QSLTKLAAAWG   34  Rv3875       10  LTKLAAAWG  114.99  2291.129000          5.5"
-      ]
-     },
-     "execution_count": 190,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "r=Pn.promiscuous_binders(cutoff_method='rank',cutoff=10,n=7,name='Rv3875')\n",
-    "r"
+    "p=Pn.promiscuous_binders(cutoff_method='score',cutoff=500,n=5)\n",
+    "p.name.value_counts()"
    ]
   },
   {
diff --git a/examples/sarscov2.ipynb b/examples/sarscov2.ipynb
index 679dc20..fddc8f7 100644
--- a/examples/sarscov2.ipynb
+++ b/examples/sarscov2.ipynb
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 50,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -39,7 +39,7 @@
     "import pandas as pd\n",
     "pd.set_option('display.width', 180)\n",
     "import epitopepredict as ep\n",
-    "from epitopepredict import base, sequtils, plotting, peptutils, analysis\n",
+    "from epitopepredict import base, sequtils, plotting, peptutils, analysis, utilities\n",
     "from IPython.display import display, HTML, Image\n",
     "%matplotlib inline\n",
     "import matplotlib as mpl\n",
@@ -77,7 +77,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -101,14 +101,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "SingleLetterAlphabet() alignment with 6 rows and 1475 columns\n",
+      "Alignment with 6 rows and 1475 columns\n",
       "--MFIFLLFLT----------------LTSGSDLDRCTTFDDVQ...HYT sars\n",
       "--MFVFLVLLP----------------LVSSQCVN--LTTRTQL...HYT scov2\n",
       "-MFLILLISLPTAFAVIGD-------LKCTSDNINDKDTGPPPI...D-- OC43\n",
@@ -148,7 +148,7 @@
     {
      "data": {
       "text/plain": [
-       "Seq('MFIFLLFLTLTSGSDLDRCTTFDDVQAPNYTQHTSSMRGVYYPDEIFRSDTLYL...HYT', None)"
+       "Seq('MFIFLLFLTLTSGSDLDRCTTFDDVQAPNYTQHTSSMRGVYYPDEIFRSDTLYL...HYT')"
       ]
      },
      "execution_count": 6,
@@ -163,7 +163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -180,7 +180,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -190,9 +190,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "predictions done for 11 sequences in 26 alleles\n",
+      "results saved to /home/damien/gitprojects/epitopepredict/examples/scov2_netmhcpan\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py:3331: DtypeWarning: Columns (3) have mixed types.Specify dtype option on import or set low_memory=False.\n",
+      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
+     ]
+    }
+   ],
    "source": [
     "P1 = base.get_predictor('netmhcpan') \n",
     "P1.predict_sequences(sc2, alleles=m1_alleles,threads=10,path='scov2_netmhcpan',length=9,overwrite=False)\n",
@@ -202,7 +219,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -222,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -242,7 +259,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [
     {
@@ -254,14 +271,14 @@
        "GU280_gp05    30\n",
        "GU280_gp10    19\n",
        "GU280_gp07    14\n",
-       "GU280_gp04    11\n",
        "GU280_gp09    11\n",
+       "GU280_gp04    11\n",
        "GU280_gp11    10\n",
        "GU280_gp06     9\n",
        "Name: name, dtype: int64"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 60,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -269,10 +286,17 @@
    "source": [
     "P2.load(path='scov2_netmhciipan')\n",
     "pb2 = P2.promiscuous_binders(n=3, cutoff=.95, limit=70)\n",
-    "#rb2 = P2.promiscuous_binders(n=3, cutoff_method='rank', cutoff=40)\n",
-    "pb2.name.value_counts()\n",
-    "#pb3 = P3.promiscuous_binders(n=3, cutoff=50, cutoff_method='rank', limit=50)\n",
-    "#pb3.name.value_counts()"
+    "rb2 = P2.promiscuous_binders(n=3, cutoff_method='rank', limit=50, cutoff=100)\n",
+    "pb2.name.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "b = P2.get_binders(cutoff_method='rank', cutoff=100, limit=50)"
    ]
   },
   {
@@ -284,9 +308,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 59,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6 70\n"
+     ]
+    }
+   ],
    "source": [
     "import difflib\n",
     "\n",
@@ -302,7 +334,7 @@
     "def find_epitopes_conserved(pb,gene,locus_tag):\n",
     "    \n",
     "    seqs = get_orthologs(gene)\n",
-    "    df = pb[pb.name==locus_tag]\n",
+    "    df = pb[pb.name==locus_tag].copy()\n",
     "    #print (df)\n",
     "    print (len(seqs),len(df))\n",
     "    s=seqs[0]\n",
@@ -331,9 +363,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GU280_gp01 ORF1ab\n",
+      "6 70\n",
+      "GU280_gp02 S\n",
+      "6 70\n",
+      "GU280_gp03 ORF3a\n",
+      "2 38\n",
+      "GU280_gp04 E\n",
+      "3 11\n",
+      "GU280_gp05 M\n",
+      "6 30\n",
+      "GU280_gp06 ORF6\n",
+      "2 9\n",
+      "GU280_gp07 ORF7a\n",
+      "2 14\n",
+      "GU280_gp08 ORF7b\n",
+      "2 0\n",
+      "GU280_gp09 ORF8\n",
+      "2 11\n",
+      "GU280_gp10 N\n",
+      "6 19\n",
+      "GU280_gp11 ORF10\n",
+      "1 10\n",
+      "162 282\n"
+     ]
+    }
+   ],
    "source": [
     "res=[]\n",
     "for i,r in scov2_df.iterrows():\n",
@@ -348,7 +410,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -367,7 +429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [
     {
@@ -550,14 +612,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## check epitope selection method\n",
+    "## The epitope selection method\n",
     "\n",
     "Promiscuous binders are those high scoring above some threshold in multiple alleles. There are several ways to select them that can give different results. By default epitopepredict selects those in each allele above a percentile score cutoff and then counts how many alleles each peptide is present in. We can also limit our set in each protein across a genome to prevent large proteins dominating the list. We can also select by score and protein rank. The overlap is shown in the venn diagram."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
@@ -577,7 +639,7 @@
        "Name: name, dtype: int64"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -592,7 +654,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
@@ -605,7 +667,7 @@
        "Name: name, dtype: int64"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 62,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -617,7 +679,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -630,7 +692,7 @@
        "Name: name, dtype: int64"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 63,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -642,7 +704,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
@@ -663,7 +725,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 168,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [],
    "source": [