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Created 2015-07-21 15:22:40 | Updated 2015-07-21 15:24:15 | Tags: vqsr vqslod
Comments (10)

We are doing WES on hundreds of samples and the average sequencing depth is 60X. I used the sensitivity 99.9% for the PASS filter in VQSR. Attached is the histagram of VQSLOD for around 900,000 SNPs with PASS filter and call rate > 95%. I wonder if you can help me with two questions? 1. is it normal to have half of the SNPs with VQSLOD < 0? 2. why so few SNPs around VQSLOD = 0?


Created 2015-07-08 20:05:08 | Updated | Tags: vqsr vqslod quality-score
Comments (8)

I am using GATK 3.4-0 / VQSR to evaluate variants called in ~300 germline genomes of varying coverage (8x-40x). When I do so, many "variants" pass using even a stringent tranche, despite not having a QUAL value or having AC=0 / AF=0. Additionally, some PASS variants have data fields GT:AD:DP, and others have GT:AD:DP:GQ:PL. Why does this occur?

For instance, VQSR Tranche SNP 99.00 to 99.90: -4.4822 <= x < -0.1962

Example: chr21 1419 . T G . PASS AC=0;AF=0.00;AN=524;BaseQRankSum=-1.733e+00;DP=5194;MQ=31.17;MQ0=0;MQRankSum=0.00;NCC=1;ReadPosRankSum=1.73;SNPEFF_EFFECT=INTERGENIC;SNPEFF_FUNCTIONAL_CLASS=NONE;SNPEFF_IMPACT=MODIFIER;VQSLOD=1.67;culprit=DP GT:AD:DP 0/0:2,0:2 0/0:14,0:14 0/0:25,0:25 0/0:1,0:1 0/0:20,0:20 0/0:36,0:36 ./.:8,2 0/0:4,0:4 0/0:4,0:4 0/0:12,0:12 0/0:38,0:38 0/0:3,0:3 0/0:39,0:39 0/0:39,0:39 0/0:14,0:14 0/0:22,0:22 0/0:4,0:4 0/0:22,0:22 0/0:17,0:17 0/0:25,0:25 0/0:32,0:32 0/0:3,0:3 0/0:32,0:32 0/0:30,0:30 0/0:7,0:7 0/0:76,0:76 0/0:28,0:28 0/0:14,0:14 0/0:36,0:36 0/0:24,0:24 0/0:24,0:24 0/0:17,0:17 0/0:7,0:7 0/0:37,0:37 0/0:23,0:23 0/0:23,0:23 0/0:20,0:20 0/0:4,0:4 0/0:4,0:4 0/0:31,0:31 0/0:3,0:3 0/0:24,0:24 0/0:9,0:9 0/0:13,0:13 0/0:5,0:5 0/0:38,0:38 0/0:5,0:5 0/0:23,0:23 0/0:16,0:16 0/0:11,0:11 0/0:32,0:32 0/0:38,0:38 0/0:56,0:56 0/0:28,0:28 0/0:32,0:32 0/0:46,0:46 0/0:18,0:18 0/0:6,0:6 0/0:29,0:29 0/0:7,0:7 0/0:50,0:50 0/0:14,0:14 0/0:33,0:33 0/0:19,0:19 0/0:33,0:33 0/0:28,0:28 0/0:26,0:26 0/0:6,0:6 0/0:19,0:19 0/0:19,0:19 0/0:26,0:26 0/0:23,0:23 0/0:16,0:16 0/0:26,0:26 0/0:22,0:22 0/0:20,0:20 0/0:18,0:18 0/0:18,0:18 0/0:29,0:29 0/0:1,0:1 0/0:34,0:34 0/0:67,0:67 0/0:22,0:22 0/0:16,0:16 0/0:37,0:37 0/0:19,0:19 0/0:5,0:5 0/0:23,0:23 0/0:26,0:26 0/0:24,0:24 0/0:31,0:31 0/0:27,0:27 0/0:23,0:23 0/0:33,0:33 0/0:6,0:6 0/0:42,0:42 0/0:9,0:9 0/0:7,0:7 0/0:34,0:34 0/0:16,0:16 0/0:28,0:28 0/0:5,0:5 0/0:11,0:11 0/0:25,0:25 0/0:39,0:39 0/0:22,1:23 0/0:28,0:28 0/0:15,0:15 0/0:30,0:30 0/0:19,0:19 0/0:5,0:5 0/0:2,0:2 0/0:2,0:2 0/0:8,0:8 0/0:3,0:3 0/0:16,0:16 0/0:31,0:31 0/0:5,0:5 0/0:26,0:26 0/0:20,0:20 0/0:14,0:14 0/0:23,0:23 0/0:49,0:49 0/0:14,0:14 0/0:23,0:23 0/0:48,0:48 0/0:52,1:53 0/0:5,0:5 0/0:6,0:6 0/0:31,0:31 0/0:44,0:44 0/0:7,0:7 0/0:10,0:10 0/0:18,0:18 0/0:14,1:15 0/0:11,0:11 0/0:16,0:16 0/0:17,0:17 0/0:22,0:22 0/0:24,1:25 0/0:15,0:15 0/0:21,0:21 0/0:11,0:11 0/0:12,0:12 0/0:5,1:6 0/0:51,0:51 0/0:40,0:40 0/0:63,0:63 0/0:49,0:49 0/0:73,0:73 0/0:90,0:90 0/0:38,0:38 0/0:56,0:56 0/0:43,0:43 0/0:39,0:39 0/0:45,0:45 0/0:41,0:41 0/0:58,0:58 0/0:22,0:22 0/0:25,0:25 0/0:28,0:28 0/0:30,0:30 0/0:17,0:17 0/0:5,0:5 0/0:2,0:2 0/0:6,0:6 0/0:6,0:6 0/0:16,0:16 0/0:10,0:10 0/0:4,0:4 0/0:11,0:11 0/0:5,0:5 0/0:3,0:3 0/0:2,0:2 0/0:2,0:2 0/0:10,0:10 0/0:22,0:22 0/0:15,0:15 0/0:13,0:13 0/0:22,0:22 0/0:10,0:10 0/0:17,0:17 0/0:15,0:15 0/0:14,0:14 0/0:33,0:33 0/0:14,0:14 0/0:22,0:22 0/0:21,0:21 0/0:22,1:23 0/0:20,0:20 0/0:18,0:18 0/0:14,0:14 0/0:29,0:29 0/0:12,0:12 0/0:21,0:21 0/0:13,0:13 0/0:23,0:23 0/0:21,0:21 0/0:20,0:20 0/0:13,0:13 0/0:9,0:9 0/0:13,0:13 0/0:14,0:14 0/0:23,0:23 0/0:19,0:19 0/0:14,0:14 0/0:19,0:19 0/0:22,0:22 0/0:10,0:10 0/0:15,0:15 0/0:26,0:26 0/0:30,0:30 0/0:16,0:16 0/0:9,0:9 0/0:12,0:12 0/0:12,0:12 0/0:11,0:11 0/0:17,0:17 0/0:10,0:10 0/0:12,0:12 0/0:16,0:16 0/0:9,0:9 0/0:9,0:9 0/0:11,0:11 0/0:14,0:14 0/0:3,0:3 0/0:12,0:12 0/0:5,0:5 0/0:4,0:4 0/0:9,0:9 0/0:4,0:4 0/0:19,0:19 0/0:21,0:21 0/0:6,0:6 0/0:7,0:7 0/0:10,0:10 0/0:13,0:13 0/0:11,0:11 0/0:2,0:2 0/0:9,0:9 0/0:9,0:9 0/0:5,0:5 0/0:6,0:6 0/0:32,0:32 0/0:7,0:7 0/0:12,0:12 0/0:8,0:8 0/0:2,0:2 0/0:19,0:19 0/0:9,0:9 0/0:3,0:3 0/0:8,0:8 0/0:19,0:19 0/0:7,0:7 0/0:9,0:9 0/0:14,0:14 0/0:7,0:7 0/0:8,0:8 0/0:5,0:5 0/0:11,0:11 0/0:14,0:14 0/0:8,1:9 0/0:12,0:12

chr21 1432 . C T 1609.66 PASS AC=5;AF=9.542e-03;AN=524;BaseQRankSum=3.28;DP=6194;FS=0.000;GQ_MEAN=60.76;GQ_STDDEV=44.35;InbreedingCoeff=-0.0114;MLEAC=5;MLEAF=9.542e-03;MQ=39.30;MQ0=0;MQRankSum=0.780;NCC=1;QD=13.64;ReadPosRankSum=-5.450e-01;SNPEFF_EFFECT=INTERGENIC;SNPEFF_FUNCTIONAL_CLASS=NONE;SNPEFF_IMPACT=MODIFIER;SOR=0.627;VQSLOD=0.834;culprit=FS GT:AD:DP:GQ:PL 0/0:2,0:2:6:0,6,49 0/0:35,0:35:99:0,102,1530 0/0:39,0:39:93:0,93,1395 0/0:7,0:7:18:0,18,270 0/0:24,0:24:72:0,72,637 0/0:40,0:40:99:0,108,1620 0/0:2,0:2:6:0,6,47 0/0:7,0:7:21:0,21,184 0/0:6,0:6:18:0,18,160 0/0:17,1:18:23:0,23,376 0/0:24,0:24:66:0,66,990 0/0:9,0:9:21:0,21,315 0/0:51,0:51:99:0,120,1800 0/0:39,0:39:99:0,108,1620 0/0:9,0:9:27:0,27,240 0/0:18,0:18:48:0,48,720 0/0:7,0:7:18:0,18,270 0/0:24,0:24:69:0,69,1035 0/0:31,0:31:78:0,78,1170 0/1:18,18:.:99:492,0,409 0/0:30,0:30:84:0,84,1260 0/0:16,0:16:48:0,48,437 0/0:25,0:25:66:0,66,990 0/0:27,0:27:63:0,63,945 0/0:11,0:11:33:0,33,284 0/0:82,0:82:99:0,120,1800 0/0:63,0:63:99:0,120,1800 0/1:2,7:.:19:188,0,19 0/0:45,0:45:99:0,120,1800 0/0:35,0:35:90:0,90,1350 0/0:47,0:47:99:0,120,1800 0/0:16,0:16:48:0,48,451 0/0:19,0:19:45:0,45,675 0/0:47,0:47:99:0,120,1800 0/0:30,0:30:72:0,72,1080 0/0:22,0:22:54:0,54,810 0/0:7,0:7:18:0,18,270 0/0:2,0:2:6:0,6,63 0/0:5,0:5:12:0,12,180 0/0:66,0:66:99:0,120,1800 0/0:6,0:6:15:0,15,225 0/0:28,0:28:75:0,75,1125 0/0:13,1:14:11:0,11,313 0/0:12,0:12:33:0,33,495 0/0:16,0:16:45:0,45,675 0/0:58,0:58:99:0,120,1800 0/0:24,0:24:66:0,66,990 0/0:27,0:27:78:0,78,1170 0/0:25,0:25:66:0,66,990 0/0:25,0:25:75:0,75,660 0/0:41,0:41:99:0,114,1710 0/0:24,0:24:60:0,60,900 0/0:48,0:48:99:0,120,1800 0/0:44,0:44:99:0,120,1800 0/0:30,0:30:81:0,81,1215 0/0:48,0:48:99:0,120,1800 0/0:23,0:23:69:0,69,605 0/0:3,0:3:9:0,9,75 0/0:33,0:33:84:0,84,1260 0/0:8,0:8:21:0,21,315 0/0:75,0:75:99:0,120,1800 0/0:31,0:31:87:0,87,1305 0/0:39,0:39:99:0,111,1665 0/0:15,1:16:20:0,20,356 0/0:61,0:61:99:0,120,1800 0/0:28,0:28:75:0,75,1125 0/0:38,0:38:99:0,102,1530 0/0:11,0:11:30:0,30,450 0/0:15,0:15:45:0,45,449 0/0:24,0:24:72:0,72,633 0/0:29,0:29:84:0,84,1260 0/0:27,0:27:72:0,72,1080 0/0:19,0:19:54:0,54,810 0/0:24,0:24:72:0,72,634 0/0:21,0:21:57:0,57,855 0/0:18,0:18:51:0,51,765 0/0:14,0:14:39:0,39,585 0/0:20,0:20:48:0,48,720 0/0:27,0:27:72:0,72,1080 0/0:2,0:2:3:0,3,45 0/0:32,0:32:81:0,81,1215 0/0:65,0:65:99:0,120,1800 0/0:22,0:22:66:0,66,581 0/0:15,0:15:39:0,39,585 0/0:56,0:56:99:0,120,1800 0/1:13,17:.:99:474,0,273 0/0:8,0:8:21:0,21,315 0/0:23,1:24:60:0,60,580 0/0:29,0:29:75:0,75,1125 0/0:36,0:36:96:0,96,1440 0/0:31,0:31:90:0,90,1350 0/0:29,0:29:78:0,78,1170 0/0:26,0:26:69:0,69,1035 0/0:33,0:33:87:0,87,1305 0/0:13,0:13:30:0,30,450 0/0:64,0:64:99:0,120,1800 0/0:8,0:8:24:0,24,201 0/0:12,0:12:36:0,36,342 0/0:38,0:38:93:0,93,1395 0/0:13,0:13:30:0,30,450 0/0:38,0:38:99:0,105,1575 0/0:6,0:6:15:0,15,225 0/0:6,0:6:18:0,18,141 0/0:26,0:26:75:0,75,1125 0/0:63,0:63:99:0,120,1800 0/0:9,0:9:24:0,24,360 0/0:22,0:22:63:0,63,945 0/0:17,0:17:45:0,45,675 0/0:54,0:54:99:0,120,1800 0/0:18,0:18:45:0,45,675 0/0:9,0:9:24:0,24,360 0/0:2,0:2:6:0,6,63 0/0:5,0:5:12:0,12,180 0/0:11,0:11:30:0,30,450 0/0:4,0:4:9:0,9,135 0/0:11,0:11:30:0,30,450 0/0:33,0:33:87:0,87,1305 0/0:4,0:4:12:0,12,100 0/0:23,0:23:60:0,60,900 0/0:29,0:29:78:0,78,1170 0/0:18,0:18:45:0,45,675 0/1:14,15:.:99:392,0,276 0/0:65,0:65:99:0,120,1800 0/0:31,0:31:78:0,78,1170 0/0:44,0:44:99:0,117,1755 0/0:93,0:93:99:0,120,1800 0/0:75,0:75:99:0,120,1800 0/0:6,0:6:18:0,18,155 0/0:7,0:7:15:0,15,225 0/0:33,0:33:93:0,93,1395 0/0:45,0:45:99:0,120,1800 0/0:17,0:17:45:0,45,675 0/0:14,0:14:42:0,42,377 0/0:28,0:28:78:0,78,1170 0/0:14,0:14:42:0,42,392 0/0:15,0:15:45:0,45,384 0/0:14,0:14:39:0,39,585 0/0:24,0:24:66:0,66,99 0/0:18,0:18:51:0,51,765 0/0:17,0:17:42:0,42,630 0/0:24,0:24:63:0,63,945 0/0:25,0:25:72:0,72,1080 0/0:16,0:16:48:0,48,413 0/0:14,0:14:36:0,36,54 0/0:6,0:6:15:0,15,225 0/0:56,0:56:99:0,120,1800 0/0:47,1:48:99:0,120,1800 0/0:68,0:68:99:0,120,1800 0/0:62,1:63:99:0,120,1800 0/0:64,0:64:99:0,120,1800 0/0:108,1:109:99:0,120,1800 0/0:60,2:62:99:0,120,1800 0/0:76,0:76:99:0,120,1800 0/0:38,0:38:99:0,108,1620 0/0:45,0:45:99:0,120,1800 0/0:39,1:40:87:0,87,1009 0/0:48,0:48:99:0,120,1800 0/0:33,0:33:90:0,90,1350 0/0:29,0:29:75:0,75,1125 0/0:33,0:33:81:0,81,1215 0/0:29,0:29:87:0,87,759 0/0:28,0:28:69:0,69,1035 0/0:22,0:22:60:0,60,900 0/0:7,0:7:21:0,21,183 0/0:6,0:6:15:0,15,225 0/0:7,0:7:15:0,15,225 0/0:15,0:15:36:0,36,540 0/0:9,1:10:4:0,4,195 0/0:7,0:7:21:0,21,175 0/0:11,0:11:21:0,21,315 0/0:4,0:4:9:0,9,135 0/0:9,0:9:27:0,27,239 0/0:5,0:5:12:0,12,180 0/0:7,0:7:21:0,21,197 0/0:7,0:7:18:0,18,270 0/0:13,0:13:30:0,30,450 0/0:18,0:18:51:0,51,765 0/0:18,0:18:51:0,51,765 0/0:17,0:17:51:0,51,442 0/0:21,0:21:54:0,54,810 0/0:19,0:19:51:0,51,765 0/0:22,0:22:57:0,57,855 0/0:16,0:16:45:0,45,675 0/0:22,0:22:66:0,66,594 0/0:30,0:30:75:0,75,1125 0/0:23,0:23:63:0,63,945 0/0:8,0:8:24:0,24,237 0/0:21,0:21:57:0,57,855 0/0:14,0:14:42:0,42,389 0/0:14,0:14:39:0,39,585 0/0:13,0:13:36:0,36,540 0/0:15,0:15:45:0,45,371 0/0:11,0:11:33:0,33,266 0/0:24,0:24:69:0,69,1035 0/0:21,0:21:57:0,57,855 0/0:16,0:16:42:0,42,630 0/0:22,0:22:66:0,66,579 0/0:19,0:19:54:0,54,810 0/0:19,0:19:54:0,54,810 0/0:22,0:22:63:0,63,945 0/0:17,0:17:45:0,45,675 0/0:20,0:20:60:0,60,534 0/0:12,0:12:36:0,36,323 0/0:16,0:16:42:0,42,630 0/0:18,0:18:45:0,45,675 0/0:20,0:20:54:0,54,810 0/0:23,0:23:63:0,63,945 0/0:7,0:7:21:0,21,188 0/0:18,0:18:51:0,51,765 0/0:9,0:9:27:0,27,241 0/0:16,0:16:48:0,48,439 0/0:21,0:21:51:0,51,765 0/0:13,0:13:30:0,30,450 0/0:11,0:11:33:0,33,301 0/0:15,0:15:42:0,42,630 0/0:5,0:5:12:0,12,180 0/0:10,0:10:27:0,27,405 0/0:22,0:22:57:0,57,855 0/0:10,0:10:30:0,30,268 0/0:9,0:9:21:0,21,315 0/0:18,0:18:42:0,42,630 0/0:9,0:9:24:0,24,360 0/0:10,0:10:27:0,27,405 0/0:12,0:12:33:0,33,495 0/0:21,0:21:57:0,57,855 0/0:7,0:7:18:0,18,270 0/0:23,0:23:60:0,60,900 0/0:16,0:16:48:0,48,433 0/0:18,0:18:48:0,48,720 0/0:9,0:9:27:0,27,241 0/0:11,0:11:33:0,33,269 0/0:22,0:22:57:0,57,855 0/0:22,0:22:60:0,60,900 0/1:7,7:.:99:185,0,123 0/0:15,0:15:42:0,42,630 0/0:16,0:16:39:0,39,585 0/0:21,0:21:54:0,54,810 0/0:13,0:13:36:0,36,540 0/0:14,0:14:39:0,39,585 0/0:14,0:14:42:0,42,380 0/0:12,0:12:33:0,33,495 0/0:8,0:8:24:0,24,199 0/0:10,0:10:27:0,27,405 0/0:36,0:36:93:0,93,1395 0/0:8,0:8:24:0,24,170 0/0:10,0:10:30:0,30,248 0/0:13,0:13:39:0,39,305 ./.:0,0:0 0/0:24,0:24:69:0,69,1035 0/0:17,0:17:42:0,42,630 0/0:12,0:12:36:0,36,298 0/0:32,0:32:90:0,90,1350 0/0:22,0:22:66:0,66,535 0/0:9,0:9:27:0,27,216 0/0:17,0:17:42:0,42,630 0/0:17,0:17:39:0,39,585 0/0:11,0:11:30:0,30,450 0/0:18,0:18:54:0,54,417 0/0:11,0:11:27:0,27,405 0/0:17,1:18:40:0,40,404 0/0:22,0:22:63:0,63,945 0/0:6,0:6:18:0,18,162 0/0:14,1:15:34:0,34,351


Created 2015-02-02 21:24:31 | Updated | Tags: vqsr dbsnp vqslod genotypegvcfs gvcf gq-pl
Comments (18)

From my whole-genome (human) BAM files, I want to obtain: For each variant in dbSNP, the GQ and VQSLOD associated with seeing that variant in my data.

Here's my situation using HaplotypeCaller -ERC GVCF followed by GenotypeGVCFs: CHROM POS ID REF ALT chr1 1 . A # my data chr1 1 . A T # dbSNP I would like to know the confidence (in terms of GQ and/or PL) of calling A/A, A/T. or T/T. The call of isn't useful to me for the reason explained below.

How can I get something like this to work? Besides needing a GATK-style GVCF file for dbSNP, I'm not sure how GenotypeGVCFs behaves if "tricked" with a fake GVCF not from HaplotypeCaller.

My detailed reason for needing this is below:

For positions of known variation (those in dbSNP), the reference base is arbitrary. For these positions, I need to distinguish between three cases: 1. We have sufficient evidence to call position n as the variant genotype 0/1 (or 1/1) with confidence scores GQ=x1 and VQSLOD=y1. 2. We have sufficient evidence to call position n as homozygous reference (0/0) with confidence scores GQ=x2 and VQSLOD=y2. 3. We do not have sufficient evidence to make any call for position n.

I was planning to use VQSR because the annotations it uses seem useful to distinguish between case 3 and either of 1 and 2. For example, excessive depth suggests a bad alignment, which decreases our confidence in making any call, homozygous reference or not.

Following the best practices pipeline using HaplotypeCaller -ERC GVCF, I get ALTs with associated GQs and PLs, and GT=./.. However, GenotypeGVCF removes all of these, meaning that whenever the call by HaplotypeCaller was ./. (due to lack of evidence for variation), it isn't carried forward for use in VQSR.

Consequently, this seems to distinguish only between these two cases: 1. We have sufficient evidence to call position n as the variant genotype 0/1 (or 1/1) with confidence scores GQ=x1 and VQSLOD=y1. 2. We do not have sufficient evidence to call position n as a variant (it's either 0/0 or unknown).

This isn't sufficient for my application, because we care deeply about the difference between "definitely homozygous reference" and "we don't know".

Thanks in advance!

Douglas


Created 2013-05-13 14:10:51 | Updated | Tags: vqsr indels vqslod
Comments (1)

Hi Mark, Eric -

First, I wanted to thank you guys for providing advice with respect to running VQSR. I am already sold and a huge fan of the method :-).

I was wondering if either of you could comment on VQSLOD and sensitivity filter tranche? To be more specific, if I set a filter threshold of 99% for sensitivity and VQSLOD < 0 I imagine that probably is not a good idea! However, a VQSLOD of 3 or 5 may be appropriate in the statistical sense, i.e. pretty confident that this is a real variant. Finally, I am thinking we should include VQSLOD in our statistical genetic association mapping methods. I wanted to get a sense from either of you what VQSLOD you would want to completely remove from analysis?

Best Wishes,

Manny.