Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_plot
beta_std plot
beta_std_plot
Metadata
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LDSC
*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call:
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1019/ieu-a-1019.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1019/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Tue Feb 4 21:10:01 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1019/ieu-a-1019.vcf.gz ...
Read summary statistics for 722473 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 668247 SNPs remain.
After merging with regression SNP LD, 668247 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0759 (0.3235)
Lambda GC: 0.9979
Mean Chi^2: 0.9916
Intercept: 0.9896 (0.0063)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Tue Feb 4 21:10:15 2020
Total time elapsed: 14.56sQC metrics
Metrics
Metrics
{
"af_correlation": 0.922,
"inflation_factor": 0.9991,
"mean_EFFECT": -0.0012,
"n": 1374,
"n_snps": 722473,
"n_clumped_hits": 1,
"n_p_sig": 1,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 5000,
"n_est": 1363.545,
"ratio_se_n": 0.9962,
"mean_diff": 0.0013,
"ratio_diff": 2.0382,
"sd_y_est1": 2.1354,
"sd_y_est2": 2.1273,
"r2_sum1": 0.0981,
"r2_sum2": 0.0215,
"r2_sum3": 0.0217,
"r2_sum4": 0.0219,
"ldsc_nsnp_merge_refpanel_ld": 668247,
"ldsc_nsnp_merge_regression_ld": 668247,
"ldsc_observed_scale_h2_beta": 0.0759,
"ldsc_observed_scale_h2_se": 0.3235,
"ldsc_intercept_beta": 0.9896,
"ldsc_intercept_se": 0.0063,
"ldsc_lambda_gc": 0.9979,
"ldsc_mean_chisq": 0.9916,
"ldsc_ratio": 1.2381
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | FALSE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | FALSE |
| n_p_sig | FALSE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | TRUE |
| ldsc_intercept_beta | FALSE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations for<*>column.
se_n metrics
n_est: Estimated sample size value, \(\widehat{n}\).ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expectratio_se_nto be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean ofdiffand the mean ofdiff2(expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).
LDSC metrics
Metrics from LD regression
ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.ldsc_observed_scale_h2_{beta,se}Coefficient value and SE for total observed scale h2.ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.ldsc_lambda_gc: Lambda GC statistics.ldsc_mean_chisq: Mean \(\chi^2\) statistics.ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).
Flags
When a metric needs attention, the flag should return TRUE.
af_correlation:abs(af_correlation)< 0.7.inflation_factor:inflation_factor> 1.2.n:n(max reported sample size) < 10000.is_snpid_non_unique: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_sum<*>:r2_sum<*>> 0.5
Plots
- Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
- QQ plot
- AF plot
- P-Z plot
- beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)
Diagnostics
Details
Summary stats
| skim_type | skim_variable | n_missing | complete_rate | character.min | character.max | character.empty | character.n_unique | character.whitespace | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 25 | 0 | 722473 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 24 | 0.9999668 | NA | NA | NA | NA | NA | 9.182708e+00 | 6.235181e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.400000e+01 | ▇▆▃▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.872254e+07 | 5.641375e+07 | 1.4380e+03 | 3.161567e+07 | 7.005013e+07 | 1.156412e+08 | 2.491982e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -1.245300e-03 | 1.333402e-01 | -2.6818e+00 | -7.267820e-02 | 0.000000e+00 | 7.232070e-02 | 1.431290e+00 | ▁▁▁▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.199889e-01 | 5.619980e-02 | 7.6200e-02 | 8.501000e-02 | 9.752000e-02 | 1.304000e-01 | 1.123000e+00 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.002108e-01 | 2.880157e-01 | 0.0000e+00 | 2.509002e-01 | 5.002004e-01 | 7.492004e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.002111e-01 | 2.880187e-01 | 0.0000e+00 | 2.508665e-01 | 5.002401e-01 | 7.492259e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.638353e-01 | 2.672112e-01 | 8.7340e-03 | 1.332000e-01 | 3.046000e-01 | 5.591000e-01 | 9.915560e-01 | ▇▅▃▃▂ |
| numeric | AF_reference | 5000 | 0.9930793 | NA | NA | NA | NA | NA | 3.676907e-01 | 2.508123e-01 | 7.9870e-04 | 1.561500e-01 | 3.095050e-01 | 5.497200e-01 | 9.994700e-01 | ▇▇▅▃▂ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.367842e+03 | 1.664977e+01 | 4.6400e+02 | 1.367000e+03 | 1.373000e+03 | 1.374000e+03 | 1.374000e+03 | ▁▁▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 721290 | rs12565286 | G | C | -0.3143000 | 0.19980 | 0.1156999 | 0.1157019 | 0.05033 | 0.0371406 | 1371 |
| 1 | 752566 | rs3094315 | G | A | 0.0177567 | 0.10100 | 0.8603000 | 0.8604441 | 0.81360 | 0.7182510 | 1368 |
| 1 | 761732 | rs2286139 | C | T | -0.0953102 | 0.11370 | 0.4043002 | 0.4018845 | 0.85380 | 0.6257990 | 1351 |
| 1 | 777122 | rs2980319 | A | T | -0.0723207 | 0.11600 | 0.5309003 | 0.5329860 | 0.86230 | 0.7472040 | 1373 |
| 1 | 785989 | rs2980300 | T | C | -0.0198026 | 0.11070 | 0.8604000 | 0.8580278 | 0.83980 | 0.6269970 | 1373 |
| 1 | 798959 | rs11240777 | G | A | 0.1570040 | 0.09259 | 0.0906192 | 0.0899445 | 0.23030 | 0.4099440 | 1374 |
| 1 | 888659 | rs3748597 | T | C | 0.0155198 | 0.17160 | 0.9280001 | 0.9279362 | 0.94169 | 0.9227240 | 1372 |
| 1 | 918573 | rs2341354 | A | G | -0.1544360 | 0.08341 | 0.0641594 | 0.0640935 | 0.57470 | 0.5491210 | 1346 |
| 1 | 926431 | rs4970403 | A | T | -0.0468836 | 0.20010 | 0.8152999 | 0.8147514 | 0.95670 | 0.8927720 | 1374 |
| 1 | 947034 | rs2465126 | G | A | -0.0049875 | 0.18960 | 0.9794000 | 0.9790136 | 0.95070 | 0.8256790 | 1359 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| NA | 11719 | rs2853495 | G | A | -0.1052610 | 0.1144 | 0.3592998 | 0.3575134 | 0.50870 | NA | 1374 |
| NA | 11812 | rs3088053 | A | G | -0.1423700 | 0.2116 | 0.5010003 | 0.5010579 | 0.08333 | NA | 1368 |
| NA | 11914 | rs2853496 | G | A | -0.0068232 | 0.2945 | 0.9814000 | 0.9815156 | 0.03956 | NA | 1365 |
| NA | 12007 | rs2853497 | G | A | -0.5461070 | 0.5120 | 0.2861001 | 0.2861456 | 0.01602 | NA | 1373 |
| NA | 12308 | rs2853498 | A | G | -0.1638140 | 0.1419 | 0.2482001 | 0.2483228 | 0.21410 | NA | 1373 |
| NA | 12612 | rs28359172 | A | G | 0.0953102 | 0.1950 | 0.6242995 | 0.6250044 | 0.09243 | NA | 1374 |
| NA | 13617 | rs2853503 | T | C | 0.0188218 | 0.2058 | 0.9271000 | 0.9271297 | 0.08382 | NA | 1372 |
| NA | 13708 | rs28359178 | G | A | 0.1371500 | 0.1754 | 0.4338005 | 0.4342575 | 0.11650 | NA | 1373 |
| NA | 14470 | rs3135030 | T | C | 0.1406310 | 0.3833 | 0.7129006 | 0.7136971 | 0.02187 | NA | 1372 |
| NA | 15218 | rs2853506 | A | G | 0.1856490 | 0.2822 | 0.5104004 | 0.5106260 | 0.04079 | NA | 1373 |
bcf preview
1 721290 rs12565286 G C . PASS AF=0.05033 ES:SE:LP:AF:SS:ID -0.3143:0.1998:0.936667:0.05033:1371:rs12565286
1 752566 rs3094315 G A . PASS AF=0.8136 ES:SE:LP:AF:SS:ID 0.0177567:0.101:0.0653501:0.8136:1368:rs3094315
1 761732 rs2286139 C T . PASS AF=0.8538 ES:SE:LP:AF:SS:ID -0.0953102:0.1137:0.393296:0.8538:1351:rs2286139
1 777122 rs2980319 A T . PASS AF=0.8623 ES:SE:LP:AF:SS:ID -0.0723207:0.116:0.274987:0.8623:1373:rs2980319
1 785989 rs2980300 T C . PASS AF=0.8398 ES:SE:LP:AF:SS:ID -0.0198026:0.1107:0.0652996:0.8398:1373:rs2980300
1 798959 rs11240777 G A . PASS AF=0.2303 ES:SE:LP:AF:SS:ID 0.157004:0.09259:1.04278:0.2303:1374:rs11240777
1 888659 rs3748597 T C . PASS AF=0.94169 ES:SE:LP:AF:SS:ID 0.0155198:0.1716:0.032452:0.94169:1372:rs3748597
1 918573 rs2341354 A G . PASS AF=0.5747 ES:SE:LP:AF:SS:ID -0.154436:0.08341:1.19274:0.5747:1346:rs2341354
1 926431 rs4970403 A T . PASS AF=0.9567 ES:SE:LP:AF:SS:ID -0.0468836:0.2001:0.0886826:0.9567:1374:rs4970403
1 947034 rs2465126 G A . PASS AF=0.9507 ES:SE:LP:AF:SS:ID -0.00498754:0.1896:0.0090399:0.9507:1359:rs2465126
1 949608 rs1921 G A . PASS AF=0.3999 ES:SE:LP:AF:SS:ID 0.0962189:0.08437:0.593119:0.3999:1364:rs1921
1 990417 rs2465136 T C . PASS AF=0.2991 ES:SE:LP:AF:SS:ID -0.058795:0.08856:0.295163:0.2991:1371:rs2465136
1 1018704 rs9442372 A G . PASS AF=0.5512 ES:SE:LP:AF:SS:ID 0.086975:0.08275:0.532688:0.5512:1358:rs9442372
1 1039098 rs11260595 C A . PASS AF=0.02725 ES:SE:LP:AF:SS:ID -0.390675:0.2726:0.819014:0.02725:1358:rs11260595
1 1041700 rs6604968 A G . PASS AF=0.1348 ES:SE:LP:AF:SS:ID -0.138113:0.12:0.602234:0.1348:1372:rs6604968
1 1048955 rs4970405 A G . PASS AF=0.09767 ES:SE:LP:AF:SS:ID -0.10948:0.1379:0.369369:0.09767:1372:rs4970405
1 1097335 rs9442385 T G . PASS AF=0.93252 ES:SE:LP:AF:SS:ID 0.0381173:0.1651:0.0875122:0.93252:1356:rs9442385
1 1129672 rs11260554 G T . PASS AF=0.1107 ES:SE:LP:AF:SS:ID -0.106472:0.1296:0.385841:0.1107:1368:rs11260554
1 1130727 rs10907175 A C . PASS AF=0.09789 ES:SE:LP:AF:SS:ID 0.0944007:0.1376:0.307858:0.09789:1374:rs10907175
1 1156131 rs2887286 T C . PASS AF=0.1696 ES:SE:LP:AF:SS:ID 0.14583:0.1053:0.780154:0.1696:1374:rs2887286
1 1158277 rs3813199 G A . PASS AF=0.103 ES:SE:LP:AF:SS:ID 0.00498754:0.1343:0.0120211:0.103:1374:rs3813199
1 1158631 rs6603781 A G . PASS AF=0.8927 ES:SE:LP:AF:SS:ID -0.00299551:0.13:0.008641:0.8927:1351:rs6603781
1 1165310 rs11260562 G A . PASS AF=0.04492 ES:SE:LP:AF:SS:ID -0.113617:0.1975:0.247721:0.04492:1369:rs11260562
1 1195690 rs11260568 G C . PASS AF=0.01202 ES:SE:LP:AF:SS:ID -1.05757:0.4889:1.51499:0.01202:1373:rs11260568
1 1198618 rs12563338 T A . PASS AF=0.03621 ES:SE:LP:AF:SS:ID 0.34359:0.2059:1.02091:0.03621:1367:rs12563338
1 1211292 rs6685064 C T . PASS AF=0.06477 ES:SE:LP:AF:SS:ID 0.260825:0.1562:1.02393:0.06477:1374:rs6685064
1 1217058 rs3753340 G A . PASS AF=0.02054 ES:SE:LP:AF:SS:ID -0.740868:0.3414:1.52259:0.02054:1363:rs3753340
1 1218086 rs6603788 C T . PASS AF=0.07465 ES:SE:LP:AF:SS:ID 0.0563803:0.1508:0.150212:0.07465:1373:rs6603788
1 1242215 rs4970431 A G . PASS AF=0.97785 ES:SE:LP:AF:SS:ID 0.0320068:0.2811:0.0412928:0.97785:1309:rs4970431
1 1297065 rs2765023 C T . PASS AF=0.1129 ES:SE:LP:AF:SS:ID 0.0227395:0.1291:0.0657036:0.1129:1373:rs2765023
1 1297422 rs2765021 C T . PASS AF=0.93061 ES:SE:LP:AF:SS:ID 0.0143018:0.1594:0.0322181:0.93061:1369:rs2765021
1 1311716 rs2649589 G A . PASS AF=0.92978 ES:SE:LP:AF:SS:ID 0.00110061:0.1624:0.00230788:0.92978:1360:rs2649589
1 1333436 rs1240743 C A . PASS AF=0.6267 ES:SE:LP:AF:SS:ID 0.164639:0.0857:1.26209:0.6267:1373:rs1240743
1 1365570 rs1695824 A C . PASS AF=0.2031 ES:SE:LP:AF:SS:ID -0.018979:0.1024:0.069051:0.2031:1374:rs1695824
1 1462766 rs9439462 C T . PASS AF=0.03367 ES:SE:LP:AF:SS:ID 0.107957:0.2153:0.209996:0.03367:1366:rs9439462
1 1467485 rs1987191 T C . PASS AF=0.01969 ES:SE:LP:AF:SS:ID -0.26958:0.3043:0.425274:0.01969:1371:rs1987191
1 1478153 rs3766180 T C . PASS AF=0.274 ES:SE:LP:AF:SS:ID 0.00697561:0.08979:0.0290491:0.274:1374:rs3766180
1 1500941 rs6603791 A G . PASS AF=0.3126 ES:SE:LP:AF:SS:ID 0.0544882:0.08595:0.281831:0.3126:1374:rs6603791
1 1506035 rs7540231 G A . PASS AF=0.8452 ES:SE:LP:AF:SS:ID -0.127513:0.1088:0.615288:0.8452:1373:rs7540231
1 1510801 rs7519837 C T . PASS AF=0.2999 ES:SE:LP:AF:SS:ID 0.0168571:0.0876:0.0697643:0.2999:1374:rs7519837
1 1647686 rs909823 A C . PASS AF=0.93421 ES:SE:LP:AF:SS:ID -0.150143:0.1623:0.450016:0.93421:1368:rs909823
1 1688192 rs2281173 A G . PASS AF=0.92031 ES:SE:LP:AF:SS:ID -0.220741:0.1494:0.855426:0.92031:1374:rs2281173
1 1692321 rs1107910 T C . PASS AF=0.4429 ES:SE:LP:AF:SS:ID -0.0565704:0.08192:0.309715:0.4429:1374:rs1107910
1 1721479 rs2272908 C T . PASS AF=0.516 ES:SE:LP:AF:SS:ID -0.0246926:0.08158:0.118729:0.516:1374:rs2272908
1 1722932 rs3737628 C T . PASS AF=0.5144 ES:SE:LP:AF:SS:ID -0.0478373:0.08306:0.24849:0.5144:1356:rs3737628
1 1746694 rs12742323 G T . PASS AF=0.1619 ES:SE:LP:AF:SS:ID -0.0968414:0.1108:0.418164:0.1619:1353:rs12742323
1 1759026 rs9786963 T C . PASS AF=0.94756 ES:SE:LP:AF:SS:ID -0.290428:0.1795:0.975104:0.94756:1373:rs9786963
1 1759054 rs10907187 G A . PASS AF=0.2616 ES:SE:LP:AF:SS:ID 0.0592119:0.08988:0.291919:0.2616:1374:rs10907187
1 1778090 rs12126768 T G . PASS AF=0.1653 ES:SE:LP:AF:SS:ID -0.117208:0.1104:0.540608:0.1653:1373:rs12126768
1 1783201 rs12402876 G A . PASS AF=0.2593 ES:SE:LP:AF:SS:ID 0.07139:0.09301:0.355069:0.2593:1313:rs12402876