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Ino de Bruijn Compare kraken kmer purity against nucmer purity almost 10 years ago

Commit id: 1687da3740e4f2551e70f72c690932938e60641c

deletions | additions

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], "metadata": {}, "output_type": "pyout", "prompt_number": 215, 3, "text": [ " tax_id parent_tax_id rank embl_code division_id \\\n", "0 1 1 no rank 8 \n",

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"kraken = pd.read_csv(\"/media/milou/glob/projects/masmvali-partdeux/reassembly-filtered-reads/Sample_1ng_even/kraken/ma-contigs-velvetnoscaf31-kraken.tsv\", sep=\"\\t\",\n", " true_values=[\"C\"], false_values=[\"U\"],\n", " names=[\"classified\",\"seq_id\",\"tax_id\",\"length\",\"lca\"],\n", " converters={\"lca\":list_it})" converters={\"lca\":list_it}).sort(\"seq_id\").reset_index().set_index(\"seq_id\")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 152 33 }, { "cell_type": "code",

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"output_type": "stream", "stream": "stdout", "text": [ "CPU times: user 27.3 26.7 s, sys: 16 128 ms, total: 27.4 26.8 s\n", "Wall time: 27.5 26.9 s\n" ] }, {

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], "metadata": {}, "output_type": "pyout", "prompt_number": 383, 38, "text": [ " class domain family genusnon-existent order phylum species \\\n", "0 "seq_id \n", "NODE_100002_length_1265_cov_13.065613 0 0 0 0 \n", "NODE_100003_length_914_cov_11.903720 0 0 0 0 \n", "2 "NODE_100006_length_2564_cov_10.472309 0 0 0 0 \n", "NODE_100007_length_725_cov_8.630344 0 0 0 0 \n", "9 "NODE_100008_length_3591_cov_30.379004 0 0 0 0 \n", "\n", " non-existent order phylum species \\\n", "seq_id \n", "NODE_100002_length_1265_cov_13.065613 0 0 0 0 \n", "10 "NODE_100003_length_914_cov_11.903720 0 0 0 0 \n", "NODE_100006_length_2564_cov_10.472309 0 0 0 0 \n", "15 "NODE_100007_length_725_cov_8.630344 0 0 0 0 \n", "NODE_100008_length_3591_cov_30.379004 0 0 0 0 \n", "\n", " subspecies superkingdom correct \n", "0 "seq_id \n", "NODE_100002_length_1265_cov_13.065613 0 0 4050 1265 \n", "2 "NODE_100003_length_914_cov_11.903720 0 0 532 914 \n", "9 "NODE_100006_length_2564_cov_10.472309 0 0 1513 2564 \n", "10 "NODE_100007_length_725_cov_8.630344 0 0 1118 725 \n", "15 "NODE_100008_length_3591_cov_30.379004 0 0 777 3591 \n", "\n", "[5 rows x 11 columns]" ] } ], "prompt_number": 383 38 }, { "cell_type": "code",

"language": "python", "metadata": {}, "outputs": [], "prompt_number": 385 39 }, { "cell_type": "markdown",

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LY0OJiEjZVFmUJJOSmMluc62WuGkqa9riJrmsqixERKQo5Swip5yFiNQu5SxERKRsqixK\nkklJzGS3uVZL3DSVNW1xk1xWVRYiIlKUchaRU85CRGqXchYiIlI2VRYlyaQkZrLbXKslbprKmra4\nSS6rKgsRESlKOYvIKWchIrVLOQsRESmbKouSZFISM9ltrtUSN01lTVvcJJdVlYWIiBSlnEXklLMQ\nkdqlnIWIiJRNlUVJMimJmew212qJm6aypi1uksuqykJERIpSziJyylmISO1SzkJERMqmyqIkmZTE\nTHaba7XETVNZ0xY3yWXtS2XRANwNPA2sAI4CGoGFwCpggXtP4FKgA1gJnBTaPgxY7l67NrR9F+AO\nt/1x4MDQaxNdjFXA2X0og4iIlKAvOYvpwMPArUA9sBtwGfAycDVwMdAfuAQ4DJgBDAcGAQ8AQ7EG\n/MXA+W4+F7gOmA9MAg5383HA6cBZWIX0JFbJALS75U153085CxGRXoo6Z7EncCxWUQBsAzYDo7FK\nBDc/zS2PAWYCbwJrgdXYlchAYA+sogC4LfSZ8L7uAU5wyydjVy2b3LQQGFVmOUREpATlVhaDgb8A\n04AlwE3YlcU+wAb3ng1uHWA/YF3o8+uwK4z87S+47bj58245qIwGbGdfHmX87r5qYia7zbVa4qap\nrGmLm+Sy1vfhc0dizUdPAj/GmpvCOvHX1lOS1tZWmpqaAGhoaKC5uZmWlhb3asbNo153a+6XF8Tr\n/ssstr9sr+L3FK+368W+v6/1bDYba7xKl7cS69lstqq+TxLLG6il/59MJkNbWxvA28fLQsrNWewL\n/Ba7wgA4Bktgvwc4HliPNTEtAg4hV5Fc5ebzgcnAc+49h7rt44HjgPPce6Zgye164EVgbyxv0QKc\n6z5zI/AQlgwPU85CRKSXos5ZrMeaiA5y6ycCfwDuw3oq4eaz3PIc7CC/M1bBDMXyFOuBLVj+og6Y\nAMwOfSbY1xnAg255AdabqgFLoI8E7i+zHCIiUoK+dJ39MvALYCnwfuC/sCuHkViX1hHkriRWAHe6\n+Tysh1NwKjwJuBnrIrsau6IAuAXLUXQAF5C7OtkIXIE1fy0GptK9J1TEMn53XzUxk93mWi1x01TW\ntMVNclnLzVmAVRLDC2w/sYf3X+mmfO3AEQW2vw6M7WFf09wkIiIx0NhQkVPOQkRql8aGEhGRsqmy\nKEkmJTGT3eZaLXHTVNa0xU1yWVVZiIhIUcpZRE45CxGpXcpZiIhI2VRZlCSTkpjJbnOtlrhpKmva\n4ia5rKosRESkKOUsIqechYjULuUsRESkbKosSpJJScxkt7lWS9w0lTVtcZNcVlUWIiJSlHIWkVPO\nQkRql3IWIiJSNlUWJcmkJGay21yrJW6aypq2uEkuqyoLEREpSjmLyClnISK1SzkLEREpmyqLkmRS\nEjPZba7VEjdNZU1b3CSXVZWFiIgUpZxF5JSzEJHapZyFiIiUTZVFSTIpiZnsNtdqiZumsqYtbpLL\n2tfKYkfgd8B9br0RWAisAhYADaH3Xgp0ACuBk0LbhwHL3WvXhrbvAtzhtj8OHBh6baKLsQo4u49l\nEBGRIvqas7gQO9jvAYwGrgZedvOLgf7AJcBhwAxgODAIeAAYijXgLwbOd/O5wHXAfGAScLibjwNO\nB87CKqQnXVyAdre8Ke+7KWchItJLPnIW+wP/Atwc2vFoYLpbng6c5pbHADOBN4G1wGrgKGAgVtEs\ndu+7LfSZ8L7uAU5wyydjVy2b3LQQGNWHcoiISBF9qSx+BHwdeCu0bR9gg1ve4NYB9gPWhd63DrvC\nyN/+gtuOmz/vlrcBm4EB29mXRxm/u6+amMluc62WuGkqa9riJrms9WV+7lTgJSxf0dLDezrx19ZT\nktbWVpqamgBoaGigubmZlpYW92rGzaNed2vulxfE6/7LLLa/bK/i9xSvt+vFvr+v9Ww2G2u8Spe3\nEuvZbLaqvk8Syxuopf+fTCZDW1sbwNvHy0LKzVlcCUzAzvh3BfoB92I5iRZgPdbEtAg4BMtbAFzl\n5vOBycBz7j2Huu3jgeOA89x7pmDJ7XrgRWBvLG/RApzrPnMj8BCWDA9TzkJEpJeizll8EzgAGIwd\nvB/CKo85WE8l3HyWW57j3rez+8xQLE+xHtiC5S/q3D5mhz4T7OsM4EG3vADrTdWAJdBHAveXWQ4R\nESlBVPdZBKe1V2EH71XACHJXEiuAO918HtbDKfjMJCxJ3oElvue77bdgOYoO4AJyVycbgSuwHlGL\ngal07wkVsYzf3VdNzGS3uVZL3DSVNW1xk1zWcnMWYQ+7CexAfmIP77vSTfnagSMKbH8dGNvDvqa5\nSUREYqCxoSKnnIWI1C6NDSUiImVTZVGSTEpiJrvNtVripqmsaYub5LKqshARkaKUs4icchYiUruU\nsxARkbKpsihJJiUxk93mWi1x01TWtMVNcllVWYiISFHKWUROOQsRqV3KWYiISNlUWZQkk5KYyW5z\nrZa4aSpr2uImuayqLEREpCjlLCKnnIWI1C7lLEREpGyqLEqSSUnMZLe5VkvcNJU1bXGTXFZVFiIi\nUpRyFpFTzkJEapdyFiIiUjZVFiXJpCRmsttcqyVumsqatrhJLqsqCxERKUo5i8gpZyEitUs5CxER\nKZsqi5JkUhIz2W2u1RI3TWVNW9wkl7XcyuIAYBHwB+D3wFfc9kZgIbAKWAA0hD5zKdABrAROCm0f\nBix3r10b2r4LcIfb/jhwYOi1iS7GKuDsMssgIiIlKjdnsa+bssDuQDtwGnAO8DJwNXAx0B+4BDgM\nmAEMBwYBDwBDsQb8xcD5bj4XuA6YD0wCDnfzccDpwFlYhfQkVsngYg8DNuV9R+UsRER6KeqcxXqs\nogDYCjyNVQKjgelu+3SsAgEYA8wE3gTWAquBo4CBwB5YRQFwW+gz4X3dA5zglk/Grlo2uWkhMKrM\ncoiISAmiyFk0AR8EngD2ATa47RvcOsB+wLrQZ9ZhlUv+9hfcdtz8ebe8DdgMDNjOvjzK+N191cRM\ndptrtcRNU1nTFjfJZa3v4+d3x876vwq8mvdaJ/7aekrS2tpKU1MTAA0NDTQ3N9PS0uJezbh51Otu\nzf3ygnjdf5nF9pct8nrX9Z7i9Xa92Pf3tZ7NZmONV+nyVmI9m81W1fdJYnkDtfT/k8lkaGtrA3j7\neFlIX+6z2An4FTAP+LHbthI7eq3HmpgWAYdgeQuAq9x8PjAZeM6951C3fTxwHHCee88ULLldD7wI\n7I3lLVqAc91nbgQewpLhYcpZiIj0UtQ5izrgFmAFuYoCYA7WUwk3nxXafhawMzAYS24vxiqVLVj+\nog6YAMwusK8zgAfd8gKsN1UDlkAfCdxfZjlERKQE5VYWHwM+BxwP/M5No7Arh5FYl9YR5K4kVgB3\nuvk8rIdTcCo8CbgZ6yK7GruiAKuMBrjtF5C7OtkIXIH1iFoMTKV7T6iIZfzuvmpiJrvNtVripqms\naYub5LKWm7N4lJ4rmhN72H6lm/K1A0cU2P46MLaHfU1zk4iIxEBjQ0VOOQsRqV0aG0pERMqmyqIk\nmZTETHaba7XETVNZ0xY3yWVVZSEiIkUpZxE55SxEpHYpZyEiImVTZVGSTEpiJrvNtVripqmsaYub\n5LKqshARkaKUs4icchYiUruUsxARkbKpsihJJiUxk93mWi1x01TWtMVNcllVWYiISFHKWUROOQsR\n6bt+/Rp59dVXIt/vHnv0Z8uWjT2+3lPOQpVF5FRZiEjfVep4oQR3n2RSEjPZba7VEjdNZU1b3EqV\nNY7jhSoLEREpSs1QkVMzlIj0nZqhRESk5qiyKEkmJTHT1b5cqbhpKmva4ipnISIiqaacReSUsxCR\nvlPOQkREak4tVxajgJVAB3Cx31AZv7uvmpjpal+uVNw0lTVtcZWzqD47Av+NVRiHAeOBQ/2Fy/rb\ndVXFhGxWcZMYU3GTG9NF9h6hViuLDwOrgbXAm8DtwBh/4Tb523VVxYRNmxQ3iTEVN7kxXWTvEWq1\nshgEPB9aX+e2SQH9+jVSV1dX0jR16tSS39uvX2OliyYiManVyiLmrj9r4w0XcUwbubKzxGliye+N\nckTMtWvXRravao+bprKmLW6lyhrHMapWu84eDUzBchYAlwJvAd8LvScLfCDeryUiUvOWAs2V/hJR\nqQfWAE3AzljF4DHBLSIiteoU4Bks0X1phb+LiIiIiIiIiIhsV60muEXK9V6sq/VrwPHAEcBt+O2o\n3h84G8ux1bttncBXPMaspDSVd1fg03Qv6+We454J3FXCtsjUatdZ3y4A9sQq01uA3wEne475faAf\nsBPwIPAyMMFzTIBrgPfFECdsR+AHMccM3ANswyqNG4EDgBmeY84FDgSWAU8B7W7y7T3Aj4BfAve5\naU4McdNU3tnAaOzm4K1u+pvnmADfLHGbeLbMzU/G/vAOxyoMn5a6+elYBbVn6Hv49CXgN8Bi4FwX\nNw6PU5kr2+D3+A3gy3nbfFnief89WYadzY8AWtz08Rjipqm8v/e8/3ynANcDLwHXueXrgTbsf9ib\n+uJvSaXgIPYJ4OfE8wcR/C5OBe4GNhPPzYc3uekQoBVYDjzqti3yGDeLnZXdBfzdbesE7vUYE+AN\n4DNYM8knsd/1Tp5jzgD+FTvTfT20faPnuK9hB5S4pam8jwHvJ54TO4A/Y1dpY9w8OFZtAf7DZ2Dl\nLAprA/bDLmvfjx3IFwHDPMa8CjgN+4P/MNCA/bMd5TFmYEfswHkOsD9wJ3AMdhAf5ylmm5vnV4jn\neIoXeB/wb8BvgZnAYGAsXW/ojNr5wH9heZG33LZO7O/LpwnAEOB+uh60fZ/5p6m8T2NNms+GYnZi\nxw2fdsKavqTCdgS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"text": [ "0x7f03971b4d90>" 0x1f14de10>" ] } ], "prompt_number": 386 40 }, { "cell_type": "code",

{ "metadata": {}, "output_type": "pyout", "prompt_number": 387, 41, "text": [ "0x7f039be5e410>" 0x24fca050>" ] }, {

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"text": [ "0x7f039be487d0>" 0x21c5b910>" ] } ], "prompt_number": 387 41 }, { "cell_type": "markdown",

"Note to self: check with only pure contigs to see if that is different from impure contigs" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Compare to nucmer alignment purity" ] }, { "cell_type": "code", "collapsed": false, "input": [ "cpurity = pd.read_csv(\"/media/milou/glob/projects/masmvali-partdeux/reassembly-filtered-reads/Sample_1ng_even/metassemble/assemblies/velvet/noscaf/noscaf_31/val/contig-purity.tsv\", \n", " sep=\"\\t\").sort(\"contig\").reset_index().set_index(\"contig\")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 42 }, { "cell_type": "code", "collapsed": false, "input": [ "cpurity.head()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "

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	index	contig_length	max_aln_strain	max_aln_purity	cov_mean	unamb_dominant_strain	unamb_dom_nr_reads	unamb_read_level_purity	unamb_tot_nr_reads	unamb_nr_reads_strain	unamb_nr_reads_species	unamb_nr_reads_genus	unamb_nr_reads_family	unamb_nr_reads_order	unamb_nr_reads_class	unamb_nr_reads_phylum	unamb_nr_reads_superphylum	unamb_nr_reads_superkingdom	unamb_nr_reads_life	amb_dominant_strain
contig
NODE_100002_length_1265_cov_13.065613	319595	1295	Hydrogenobaculum_sp_Y04AAS1	1.0000	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...
NODE_100003_length_914_cov_11.903720	22443	944	Gemmatimonas_aurantiaca_T-27_DNA	1.0000	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...
NODE_100004_length_31_cov_9.096774	199219	61	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...
NODE_100005_length_352_cov_11.269886	176568	382	Sulfurihydrogenibium_yellowstonense_SS-5	0.9895	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...
NODE_100006_length_2564_cov_10.472309	25076	2594	Bordetella_bronchiseptica_strain_RB50	1.0000	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...

\n", "

5 rows \u00d7 33 columns

\n", "

" ], "metadata": {}, "output_type": "pyout", "prompt_number": 43, "text": [ " index contig_length \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 319595 1295 \n", "NODE_100003_length_914_cov_11.903720 22443 944 \n", "NODE_100004_length_31_cov_9.096774 199219 61 \n", "NODE_100005_length_352_cov_11.269886 176568 382 \n", "NODE_100006_length_2564_cov_10.472309 25076 2594 \n", "\n", " max_aln_strain \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 Hydrogenobaculum_sp_Y04AAS1 \n", "NODE_100003_length_914_cov_11.903720 Gemmatimonas_aurantiaca_T-27_DNA \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 Sulfurihydrogenibium_yellowstonense_SS-5 \n", "NODE_100006_length_2564_cov_10.472309 Bordetella_bronchiseptica_strain_RB50 \n", "\n", " max_aln_purity cov_mean \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 1.0000 NaN \n", "NODE_100003_length_914_cov_11.903720 1.0000 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN NaN \n", "NODE_100005_length_352_cov_11.269886 0.9895 NaN \n", "NODE_100006_length_2564_cov_10.472309 1.0000 NaN \n", "\n", " unamb_dominant_strain \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_dom_nr_reads \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_read_level_purity \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_tot_nr_reads \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_strain \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_species \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_genus \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_family \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_order \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_class \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_phylum \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_superphylum \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_superkingdom \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " unamb_nr_reads_life \\\n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN \n", "NODE_100003_length_914_cov_11.903720 NaN \n", "NODE_100004_length_31_cov_9.096774 NaN \n", "NODE_100005_length_352_cov_11.269886 NaN \n", "NODE_100006_length_2564_cov_10.472309 NaN \n", "\n", " amb_dominant_strain \n", "contig \n", "NODE_100002_length_1265_cov_13.065613 NaN ... \n", "NODE_100003_length_914_cov_11.903720 NaN ... \n", "NODE_100004_length_31_cov_9.096774 NaN ... \n", "NODE_100005_length_352_cov_11.269886 NaN ... \n", "NODE_100006_length_2564_cov_10.472309 NaN ... \n", "\n", "[5 rows x 33 columns]" ] } ], "prompt_number": 43 }, { "cell_type": "code", "collapsed": false, "input": [ "len(cpurity[cpurity.contig_length > 500])" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 20, "text": [ "54467" ] } ], "prompt_number": 20 }, { "cell_type": "code", "collapsed": false, "input": [ "len(rank_kmer_short)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 18, "text": [ "54467" ] } ], "prompt_number": 18 }, { "cell_type": "code", "collapsed": false, "input": [ "rank_kmer_purity = rank_kmer.copy()\n", "rank_kmer_purity.max_aln_purity = cpurity.max_aln_purity\n", "pure = rank_kmer_purity.max_aln_purity == 1\n", "impure = rank_kmer_purity.max_aln_purity < 1" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 51 }, { "cell_type": "code", "collapsed": false, "input": [ "(rank_kmer_purity[pure].sum() / rank_kmer_purity[pure].sum().sum() * 100.0).plot(kind='bar', ylim=[0,100])" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 52, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 52 }, { "cell_type": "code", "collapsed": false, "input": [ "(rank_kmer_purity[impure].sum() / rank_kmer_purity[impure].sum().sum() * 100.0).plot(kind='bar', ylim=[0,100])" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 53, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 53 }, { "cell_type": "code", "collapsed": false, "input": [ "rank_kmer_purity[(rank_kmer_purity.max_aln_purity == 1) & (rank_kmer_purity.genus > 1)].head(1)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "

	class	domain	family	genus	non-existent	order	phylum	species	subspecies	superkingdom	correct
seq_id
NODE_10005_length_507_cov_15.684418	0	0	0	300	0	0	0	0	0	0	207

\n", "

1 rows \u00d7 11 columns

\n", "

" ], "metadata": {}, "output_type": "pyout", "prompt_number": 61, "text": [ " class domain family genus \\\n", "seq_id \n", "NODE_10005_length_507_cov_15.684418 0 0 0 300 \n", "\n", " non-existent order phylum species \\\n", "seq_id \n", "NODE_10005_length_507_cov_15.684418 0 0 0 0 \n", "\n", " subspecies superkingdom correct \n", "seq_id \n", "NODE_10005_length_507_cov_15.684418 0 0 207 \n", "\n", "[1 rows x 11 columns]" ] } ], "prompt_number": 61 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Oops. Turns out the kmer LCA of Kraken is not based on the classification of the contig. It is simply the LCA of a kmer in case it is not specific enough to be assigned to a lower rank in the taxonomy. The way to fix this would be to get the full taxonomic line for each genome in the reference and write some functions that give the LCA of two taxonomy ids." ] }, { "cell_type": "code", "collapsed": false,