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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}

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-6991/UKB-b-6991_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6991/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6991/UKB-b-6991_data.vcf.gz ...
Read summary statistics for 9349405 SNPs.
Dropped 10580 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, 1288045 SNPs remain.
After merging with regression SNP LD, 1288045 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0602 (0.0024)
Lambda GC: 1.4326
Mean Chi^2: 1.5531
Intercept: 1.0148 (0.0094)
Ratio: 0.0267 (0.017)
Analysis finished at Thu Oct 17 14:42:52 2019
Total time elapsed: 2.0m:35.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 44,
    "n_p_sig": 4518,
    "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": 116673,
    "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": 1288045,
    "ldsc_nsnp_merge_regression_ld": 1288045,
    "ldsc_observed_scale_h2_beta": 0.0602,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0148,
    "ldsc_intercept_se": 0.0094,
    "ldsc_lambda_gc": 1.4326,
    "ldsc_mean_chisq": 1.5531,
    "ldsc_ratio": 0.0268
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 9338878 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 9349405 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 8.633041e+00 5.753421e+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 7.881785e+07 5.630663e+07 828.0000000 3.251041e+07 6.940004e+07 1.145461e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.710000e-05 3.852800e-03 -0.0478984 -1.513500e-03 9.100000e-06 1.530800e-03 4.639780e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.843300e-03 2.274400e-03 0.0009414 1.134100e-03 1.799400e-03 3.892900e-03 3.261840e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.565140e-01 3.007446e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.565140e-01 3.007215e-01 0.0000000 1.849758e-01 4.413151e-01 7.171272e-01 9.999999e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.128572e-01 2.576974e-01 0.0022080 1.708400e-02 9.116800e-02 3.340170e-01 9.977920e-01 ▇▂▁▁▁
numeric AF_reference 116673 0.9875208 NA NA NA NA NA NA NA 2.139899e-01 2.494795e-01 0.0000000 1.437700e-02 1.098240e-01 3.342650e-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 -0.0008570 0.0017320 0.6200004 0.6207606 0.623747 0.7821490 NA
1 54676 rs2462492 C T 0.0001870 0.0017157 0.9100000 0.9132118 0.400438 NA NA
1 86028 rs114608975 T C 0.0019417 0.0027431 0.4799997 0.4790456 0.103562 0.0277556 NA
1 91536 rs6702460 G T -0.0017156 0.0016895 0.3100002 0.3099063 0.456863 0.4207270 NA
1 234313 rs8179466 C T -0.0002193 0.0033316 0.9500000 0.9475090 0.074498 NA NA
1 534192 rs6680723 C T 0.0016437 0.0019296 0.3900004 0.3942928 0.240964 NA NA
1 546697 rs12025928 A G -0.0011383 0.0024070 0.6400000 0.6362932 0.913468 NA NA
1 693731 rs12238997 A G 0.0000386 0.0016170 0.9800000 0.9809498 0.116320 0.1417730 NA
1 705882 rs72631875 G A 0.0002121 0.0023692 0.9299999 0.9286520 0.067306 0.0315495 NA
1 706368 rs55727773 A G -0.0013215 0.0011980 0.2700001 0.2699844 0.515650 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0007958 0.0014462 0.5800000 0.5821460 0.137930 0.2052720 NA
22 51219387 rs9616832 T C -0.0020993 0.0018774 0.2599998 0.2634828 0.073731 0.0654952 NA
22 51219704 rs147475742 G A -0.0023202 0.0025158 0.3599996 0.3563874 0.041943 0.0473243 NA
22 51221190 rs369304721 G A -0.0012518 0.0025117 0.6200004 0.6181969 0.049718 NA NA
22 51221731 rs115055839 T C -0.0019541 0.0018786 0.2999998 0.2982368 0.073219 0.0625000 NA
22 51222100 rs114553188 G T 0.0001957 0.0022111 0.9299999 0.9294736 0.054458 0.0880591 NA
22 51223637 rs375798137 G A 0.0001963 0.0022218 0.9299999 0.9295860 0.054087 0.0788738 NA
22 51229805 rs9616985 T C -0.0019992 0.0018853 0.2900000 0.2889565 0.073058 0.0730831 NA
22 51232488 rs376461333 A G 0.0020203 0.0044403 0.6499995 0.6491116 0.020042 NA NA
22 51237063 rs3896457 T C 0.0007682 0.0011530 0.5099998 0.5052572 0.297917 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623747 ES:SE:LP:AF:ID  -0.000856961:0.00173203:0.207608:0.623747:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400438 ES:SE:LP:AF:ID  0.000186989:0.00171568:0.0409586:0.400438:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103562 ES:SE:LP:AF:ID  0.0019417:0.00274314:0.318759:0.103562:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  -0.00171557:0.00168952:0.508638:0.456863:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074498 ES:SE:LP:AF:ID  -0.000219334:0.00333156:0.0222764:0.074498:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240964 ES:SE:LP:AF:ID  0.00164372:0.00192957:0.408935:0.240964:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913468 ES:SE:LP:AF:ID  -0.00113826:0.00240704:0.19382:0.913468:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11632  ES:SE:LP:AF:ID  3.8612e-05:0.00161704:0.00877392:0.11632:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067306 ES:SE:LP:AF:ID  0.000212145:0.00236925:0.0315171:0.067306:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.00132149:0.00119798:0.568636:0.51565:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03301  ES:SE:LP:AF:ID  0.00207037:0.00301974:0.309804:0.03301:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036628 ES:SE:LP:AF:ID  0.0023936:0.00274284:0.420216:0.036628:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03674  ES:SE:LP:AF:ID  0.00246149:0.00273265:0.431798:0.03674:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036438 ES:SE:LP:AF:ID  0.00262469:0.00275235:0.468521:0.036438:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016406 ES:SE:LP:AF:ID  -0.00142253:0.00423793:0.130768:0.016406:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036982 ES:SE:LP:AF:ID  0.00262529:0.00272167:0.481486:0.036982:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037075 ES:SE:LP:AF:ID  0.00243383:0.00271248:0.431798:0.037075:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101235 ES:SE:LP:AF:ID  -0.000504973:0.00197583:0.09691:0.101235:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959103 ES:SE:LP:AF:ID  -0.00251725:0.00261638:0.468521:0.959103:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031455 ES:SE:LP:AF:ID  -0.000240402:0.00474821:0.0177288:0.031455:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053251 ES:SE:LP:AF:ID  -0.00140228:0.00377845:0.148742:0.053251:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  0.00293204:0.00273002:0.552842:0.036594:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036908 ES:SE:LP:AF:ID  0.00226175:0.00270528:0.39794:0.036908:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843236 ES:SE:LP:AF:ID  -0.000835124:0.0014014:0.259637:0.843236:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055917 ES:SE:LP:AF:ID  0.00141808:0.00226888:0.275724:0.055917:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122301 ES:SE:LP:AF:ID  0.000606465:0.00153391:0.161151:0.122301:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025696 ES:SE:LP:AF:ID  0.00167592:0.00377392:0.180456:0.025696:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121543 ES:SE:LP:AF:ID  0.000610315:0.00153456:0.161151:0.121543:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132328 ES:SE:LP:AF:ID  0.000565276:0.00151243:0.148742:0.132328:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011137 ES:SE:LP:AF:ID  0.00394747:0.00549828:0.327902:0.011137:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005713 ES:SE:LP:AF:ID  -0.0027344:0.00709101:0.154902:0.005713:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002261 ES:SE:LP:AF:ID  0.0152449:0.0119601:0.69897:0.002261:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036825 ES:SE:LP:AF:ID  0.0020522:0.00267783:0.356547:0.036825:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838974 ES:SE:LP:AF:ID  -0.000768025:0.00135722:0.244125:0.838974:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838604 ES:SE:LP:AF:ID  -0.000695906:0.00135576:0.21467:0.838604:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869799 ES:SE:LP:AF:ID  -0.000788829:0.00145485:0.229148:0.869799:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129856 ES:SE:LP:AF:ID  0.0006814:0.0014578:0.19382:0.129856:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037334 ES:SE:LP:AF:ID  0.0018771:0.00263248:0.318759:0.037334:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037578 ES:SE:LP:AF:ID  0.00199659:0.00261585:0.346787:0.037578:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869144 ES:SE:LP:AF:ID  -0.000822343:0.00145201:0.244125:0.869144:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869241 ES:SE:LP:AF:ID  -0.000798317:0.00145258:0.236572:0.869241:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037536 ES:SE:LP:AF:ID  0.00212111:0.00262717:0.376751:0.037536:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869146 ES:SE:LP:AF:ID  -0.000794496:0.00145198:0.236572:0.869146:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005127 ES:SE:LP:AF:ID  -0.00669438:0.00744988:0.431798:0.005127:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005093 ES:SE:LP:AF:ID  -0.00702697:0.00746941:0.455932:0.005093:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838061 ES:SE:LP:AF:ID  -0.000821374:0.00135203:0.267606:0.838061:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037549 ES:SE:LP:AF:ID  0.00222749:0.00263087:0.39794:0.037549:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838693 ES:SE:LP:AF:ID  -0.000863224:0.00135584:0.283997:0.838693:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013794 ES:SE:LP:AF:ID  0.0028217:0.00472821:0.259637:0.013794:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005553 ES:SE:LP:AF:ID  -0.0113827:0.00729537:0.920819:0.005553:rs184270342