Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_1598.vcf.gz --id UKB-b:1707 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_1598.txt.gz --cohort_controls 326565 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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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/public/UKB-b-1707/UKB-b-1707_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1707/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1707/UKB-b-1707_data.vcf.gz ...
Read summary statistics for 9792186 SNPs.
Dropped 14226 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1289025 SNPs remain.
After merging with regression SNP LD, 1289025 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0321 (0.0021)
Lambda GC: 1.2177
Mean Chi^2: 1.2411
Intercept: 1.0349 (0.0078)
Ratio: 0.1448 (0.0323)
Analysis finished at Thu Oct 17 14:47:01 2019
Total time elapsed: 1.0m:30.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9496,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -6.3492e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 420,
    "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": 180707,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1289025,
    "ldsc_nsnp_merge_regression_ld": 1289025,
    "ldsc_observed_scale_h2_beta": 0.0321,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.0349,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.2177,
    "ldsc_mean_chisq": 1.2411,
    "ldsc_ratio": 0.1448
}
 

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 FALSE
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 between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations 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 expect ratio_se_n to 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 of diff and the mean of diff2 (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<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 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: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 9778026 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9792186 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.622950e+00 5.748724e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.885810e+07 5.628830e+07 828.0000000 3.258175e+07 6.948198e+07 1.145921e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.300000e-06 1.039680e-02 -0.1678280 -3.337000e-03 -1.300000e-05 3.326500e-03 1.635570e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.390500e-03 6.882000e-03 0.0021087 2.576400e-03 4.292300e-03 9.835100e-03 1.100910e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.765372e-01 2.948592e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.765372e-01 2.948336e-01 0.0000000 2.154098e-01 4.682959e-01 7.319801e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.044082e-01 2.568244e-01 0.0010720 1.355800e-02 7.929200e-02 3.182610e-01 9.989280e-01 ▇▂▁▁▁
numeric AF_reference 180707 0.9815458 NA NA NA NA NA NA NA 2.074734e-01 2.483870e-01 0.0000000 1.198080e-02 1.008390e-01 3.218850e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0005558 0.0038755 0.8900000 0.8859683 0.623743 0.7821490 NA
1 54676 rs2462492 C T -0.0028916 0.0038412 0.4500005 0.4515772 0.400544 NA NA
1 86028 rs114608975 T C -0.0089888 0.0061344 0.1400000 0.1428395 0.103649 0.0277556 NA
1 91536 rs6702460 G T 0.0003321 0.0037857 0.9299999 0.9300927 0.456724 0.4207270 NA
1 234313 rs8179466 C T 0.0083509 0.0074582 0.2599998 0.2628498 0.074492 NA NA
1 534192 rs6680723 C T 0.0016021 0.0043243 0.7099994 0.7110219 0.241162 NA NA
1 546697 rs12025928 A G -0.0037087 0.0053970 0.4899999 0.4919673 0.913621 NA NA
1 693731 rs12238997 A G 0.0026522 0.0036234 0.4600002 0.4641857 0.116308 0.1417730 NA
1 705882 rs72631875 G A 0.0060050 0.0052985 0.2599998 0.2570698 0.067421 0.0315495 NA
1 706368 rs55727773 A G 0.0021060 0.0026842 0.4299995 0.4326951 0.516227 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0020244 0.0056385 0.7199992 0.7195700 0.041898 0.0473243 NA
22 51219766 rs182321900 C T 0.0450337 0.0269211 0.0940005 0.0943661 0.001854 NA NA
22 51220146 rs868950473 C T 0.0412804 0.0266095 0.1199999 0.1208201 0.001908 NA NA
22 51221190 rs369304721 G A 0.0012755 0.0056267 0.8200001 0.8206733 0.049592 NA NA
22 51221731 rs115055839 T C -0.0005161 0.0042086 0.9000000 0.9023941 0.073079 0.0625000 NA
22 51222100 rs114553188 G T -0.0026755 0.0049558 0.5900000 0.5892807 0.054343 0.0880591 NA
22 51223637 rs375798137 G A -0.0031712 0.0049792 0.5199996 0.5241992 0.053984 0.0788738 NA
22 51229805 rs9616985 T C -0.0002827 0.0042236 0.9500000 0.9466263 0.072913 0.0730831 NA
22 51232488 rs376461333 A G -0.0077044 0.0099559 0.4400003 0.4390176 0.019959 NA NA
22 51237063 rs3896457 T C 0.0015495 0.0025814 0.5500004 0.5483369 0.298226 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623743 ES:SE:LP:AF:ID  -0.000555779:0.00387552:0.05061:0.623743:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400544 ES:SE:LP:AF:ID  -0.00289161:0.0038412:0.346787:0.400544:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103649 ES:SE:LP:AF:ID  -0.00898877:0.00613443:0.853872:0.103649:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456724 ES:SE:LP:AF:ID  0.000332111:0.00378568:0.0315171:0.456724:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074492 ES:SE:LP:AF:ID  0.00835086:0.00745825:0.585027:0.074492:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241162 ES:SE:LP:AF:ID  0.00160208:0.00432429:0.148742:0.241162:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913621 ES:SE:LP:AF:ID  -0.0037087:0.00539696:0.309804:0.913621:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116308 ES:SE:LP:AF:ID  0.00265222:0.00362339:0.337242:0.116308:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067421 ES:SE:LP:AF:ID  0.00600499:0.00529847:0.585027:0.067421:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516227 ES:SE:LP:AF:ID  0.00210596:0.00268416:0.366532:0.516227:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032822 ES:SE:LP:AF:ID  -0.00102263:0.00678005:0.0555173:0.032822:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036421 ES:SE:LP:AF:ID  0.00196284:0.00615896:0.124939:0.036421:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036533 ES:SE:LP:AF:ID  0.00188213:0.0061361:0.119186:0.036533:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036235 ES:SE:LP:AF:ID  0.00202793:0.00618008:0.130768:0.036235:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016297 ES:SE:LP:AF:ID  -0.00549061:0.00952803:0.251812:0.016297:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036766 ES:SE:LP:AF:ID  0.00220892:0.00611212:0.142668:0.036766:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036855 ES:SE:LP:AF:ID  0.00175169:0.00609223:0.113509:0.036855:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  -0.00146622:0.00442971:0.130768:0.101206:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959456 ES:SE:LP:AF:ID  0.00243274:0.00588525:0.167491:0.959456:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031518 ES:SE:LP:AF:ID  -0.0037736:0.0106268:0.142668:0.031518:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053175 ES:SE:LP:AF:ID  -0.000526369:0.00847396:0.0222764:0.053175:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036394 ES:SE:LP:AF:ID  0.00206519:0.00613064:0.130768:0.036394:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036704 ES:SE:LP:AF:ID  0.000906189:0.00607464:0.0555173:0.036704:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843547 ES:SE:LP:AF:ID  -0.00178494:0.00314161:0.244125:0.843547:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056173 ES:SE:LP:AF:ID  0.00248715:0.00507165:0.207608:0.056173:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122326 ES:SE:LP:AF:ID  0.00364675:0.00343626:0.537602:0.122326:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025986 ES:SE:LP:AF:ID  0.00215052:0.00840047:0.09691:0.025986:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121577 ES:SE:LP:AF:ID  0.00349054:0.00343774:0.508638:0.121577:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132354 ES:SE:LP:AF:ID  0.00425794:0.00338723:0.677781:0.132354:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011076 ES:SE:LP:AF:ID  0.0117492:0.0123686:0.468521:0.011076:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005705 ES:SE:LP:AF:ID  0.00360411:0.0158734:0.0861861:0.005705:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002155 ES:SE:LP:AF:ID  -0.0348047:0.0276248:0.677781:0.002155:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036623 ES:SE:LP:AF:ID  0.000686226:0.00601361:0.0409586:0.036623:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839255 ES:SE:LP:AF:ID  -0.00342272:0.00304316:0.585027:0.839255:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838922 ES:SE:LP:AF:ID  -0.00340157:0.00304042:0.585027:0.838922:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86988  ES:SE:LP:AF:ID  -0.00369123:0.00326133:0.585027:0.86988:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129767 ES:SE:LP:AF:ID  0.00381296:0.00326824:0.619789:0.129767:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037133 ES:SE:LP:AF:ID  0.00151809:0.00591172:0.09691:0.037133:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03737  ES:SE:LP:AF:ID  0.00145188:0.00587449:0.09691:0.03737:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869266 ES:SE:LP:AF:ID  -0.00369616:0.00325542:0.585027:0.869266:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869366 ES:SE:LP:AF:ID  -0.00379605:0.00325672:0.619789:0.869366:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037319 ES:SE:LP:AF:ID  0.00156217:0.00590138:0.102373:0.037319:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869268 ES:SE:LP:AF:ID  -0.00372681:0.0032554:0.60206:0.869268:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005167 ES:SE:LP:AF:ID  0.039661:0.0165972:1.76955:0.005167:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00513  ES:SE:LP:AF:ID  0.0386659:0.0166447:1.69897:0.00513:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838397 ES:SE:LP:AF:ID  -0.00345585:0.00303216:0.60206:0.838397:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037332 ES:SE:LP:AF:ID  0.00165176:0.0059097:0.107905:0.037332:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839031 ES:SE:LP:AF:ID  -0.00348778:0.00304076:0.60206:0.839031:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013903 ES:SE:LP:AF:ID  -0.00371506:0.0105395:0.142668:0.013903:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005512 ES:SE:LP:AF:ID  0.00954867:0.0163782:0.251812:0.005512:rs184270342