From 4a8a45ebd9d31c4574c57c6ac2d5cb36d71804a2 Mon Sep 17 00:00:00 2001 From: Greg Way Date: Mon, 2 Oct 2017 11:15:35 -0400 Subject: [PATCH] update results for additional cell line predictions (#53) --- scripts/ras_cell_line_predictions.ipynb | 262 +++++++++++++++++++++--- 1 file changed, 239 insertions(+), 23 deletions(-) diff --git a/scripts/ras_cell_line_predictions.ipynb b/scripts/ras_cell_line_predictions.ipynb index 7097952..2fe1e4f 100644 --- a/scripts/ras_cell_line_predictions.ipynb +++ b/scripts/ras_cell_line_predictions.ipynb @@ -812,12 +812,39 @@ "metadata": { "collapsed": false }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Statistic = 3.31, p = 1.16E-2\n" + ] + } + ], + "source": [ + "# Perform a t-test to determine if weights are significantly different\n", + "ras_geo_mutant = output[output['Ras_Mutation'] == 1]\n", + "ras_geo_wt = output[output['Ras_Mutation'] == -1]\n", + "\n", + "# Output t-test results\n", + "t_results_geo_ras = ttest_ind(a = ras_geo_mutant['weight'],\n", + " b = ras_geo_wt['weight'], equal_var = False)\n", + "print('Statistic = {:.2f}, p = {:.2E}'.format(t_results_geo_ras[0],\n", + " Decimal(t_results_geo_ras[1])))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, "outputs": [ { "data": { "image/png": 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c+eEINr+/uVJn66+KnLs5WNZ2GS5FXlIbp9OLT2OF7wqUFJaI78O9HCzzWIZL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\ndCnGjx+PP/74A3K5HLVq1UJISAhCQkJ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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -826,10 +853,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -880,7 +907,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": { "collapsed": false }, @@ -1146,7 +1173,7 @@ "[5 rows x 751 columns]" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -1161,7 +1188,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": { "collapsed": false }, @@ -1243,7 +1270,7 @@ "1520 MLPH 0.102069 0.102069" ] }, - "execution_count": 15, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -1258,7 +1285,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -1269,7 +1296,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": { "collapsed": true }, @@ -1283,7 +1310,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": { "collapsed": false }, @@ -1296,7 +1323,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": { "collapsed": false }, @@ -1305,7 +1332,7 @@ "data": { "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1319,7 +1346,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": { "collapsed": false }, @@ -1330,7 +1357,7 @@ "(63775, 1031)" ] }, - "execution_count": 20, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1345,7 +1372,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": { "collapsed": false }, @@ -1446,7 +1473,7 @@ "HUT78_HAEMATOPOIETIC_AND_LYMPHOID_TISSUE 1 " ] }, - "execution_count": 21, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1467,7 +1494,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": { "collapsed": false }, @@ -1580,7 +1607,7 @@ "TT2609C02_THYROID 0.975086 TT2609C02_THYROID " ] }, - "execution_count": 22, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1596,7 +1623,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": { "collapsed": true }, @@ -1617,7 +1644,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": { "collapsed": false }, @@ -1657,16 +1684,16 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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FYxuOpLMhokd2r4BeK5/b38Q1MxsMhk4D9uvq6rDZBm8kSdwIFSXSQrRuFQbn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NyMa0mDI7xtyGUEPUN3r4uulUxhT0zVP50IxonaYGCQn/V/uPeqy+8hePS5knTpzIX//6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\nd+5cbr31Vk/ZeV/vjIwM2rVrh0qlIjk5mXvucTseXcpf/WKUafZlIMl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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1713,6 +1740,195 @@ "ccle_fig_file = os.path.join('..', 'figures', 'cell_line', 'ccle_predictions.pdf')\n", "plt.savefig(ccle_fig_file)" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### What percentage of correct classifications in CCLE data?" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "positive_ras_ccle = ccle_full_df[ccle_full_df['weight'] > 0.5]\n", + "negative_ras_ccle = ccle_full_df[ccle_full_df['weight'] <= 0.5]" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0 357\n", + "1 36\n", + "Name: ras_status, dtype: int64" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Negative predictions of wild-type Ras\n", + "negative_ras_ccle['ras_status'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "357 of 393 Ras wt predicted correctly (90.8%)\n" + ] + } + ], + "source": [ + "neg_ccle_results = negative_ras_ccle['ras_status'].value_counts()\n", + "correct_neg = neg_ccle_results[0]\n", + "total_neg = neg_ccle_results.sum()\n", + "print('{} of {} Ras wt predicted correctly ({:.1f}%)'.format(correct_neg,\n", + " total_neg,\n", + " correct_neg * 100 / total_neg))" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0 191\n", + "1 153\n", + "Name: ras_status, dtype: int64" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Positive predictions of wild-type Ras\n", + "positive_ras_ccle['ras_status'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "153 of 344 Ras mut predicted correctly (44.5%)\n" + ] + } + ], + "source": [ + "pos_ccle_results = positive_ras_ccle['ras_status'].value_counts()\n", + "correct_pos = pos_ccle_results[1]\n", + "total_pos = pos_ccle_results.sum()\n", + "print('{} of {} Ras mut predicted correctly ({:.1f}%)'.format(correct_pos,\n", + " total_pos,\n", + " correct_pos * 100 / total_pos))" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0 135\n", + "1 56\n", + "Name: BRAF_MUT, dtype: int64" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Of the False positives, how many are BRAF mutant?\n", + "wt_ras_braf_ccle = positive_ras_ccle[positive_ras_ccle['ras_status'] == 0]\n", + "wt_ras_braf_ccle['BRAF_MUT'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Including BRAF mutants, 209 of 344 Ras mut predicted correctly (60.8%)\n" + ] + } + ], + "source": [ + "correct_braf = wt_ras_braf_ccle['BRAF_MUT'].value_counts()[1]\n", + "correct_pos += correct_braf\n", + "print('Including BRAF mutants'\n", + " ', {} of {} Ras mut predicted correctly ({:.1f}%)'.format(correct_pos,\n", + " total_pos,\n", + " correct_pos * 100 / total_pos))" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "566 of 737 Total predicted correctly (76.8%)\n" + ] + } + ], + "source": [ + "total_correct = correct_pos + correct_neg\n", + "print('{} of {} Total predicted correctly ({:.1f}%)'.format(total_correct,\n", + " ccle_full_df.shape[0],\n", + " total_correct * 100 / ccle_full_df.shape[0]))" + ] } ], "metadata": {