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-13824/UKB-b-13824_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13824/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13824/UKB-b-13824_data.vcf.gz ...
Read summary statistics for 9805968 SNPs.
Dropped 14234 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, 1289049 SNPs remain.
After merging with regression SNP LD, 1289049 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0038 (0.0009)
Lambda GC: 1.0769
Mean Chi^2: 1.0739
Intercept: 1.0397 (0.0059)
Ratio: 0.5374 (0.0793)
Analysis finished at Thu Oct 17 14:44:47 2019
Total time elapsed: 1.0m:48.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9498,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 179580,
    "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": 1289049,
    "ldsc_nsnp_merge_regression_ld": 1289049,
    "ldsc_observed_scale_h2_beta": 0.0038,
    "ldsc_observed_scale_h2_se": 0.0009,
    "ldsc_intercept_beta": 1.0397,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0769,
    "ldsc_mean_chisq": 1.0739,
    "ldsc_ratio": 0.5372
}

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 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 9791799 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 9805968 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 8.623134e+00 5.748704e+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 7.885952e+07 5.628786e+07 828.0000000 3.258534e+07 6.948590e+07 1.145921e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.780000e-05 4.520000e-03 -0.0623159 -1.349700e-03 2.070000e-05 1.416100e-03 6.242760e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.232400e-03 3.009400e-03 0.0009199 1.124600e-03 1.875900e-03 4.304700e-03 4.842520e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.898754e-01 2.912570e-01 0.0000001 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.898767e-01 2.912311e-01 0.0000001 2.347711e-01 4.863443e-01 7.421828e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.042566e-01 2.568722e-01 0.0010830 1.347900e-02 7.905700e-02 3.179150e-01 9.989170e-01 ▇▂▁▁▁
numeric AF_reference 179580 0.9816867 NA NA NA NA NA NA NA 2.073763e-01 2.483770e-01 0.0000000 1.218050e-02 1.006390e-01 3.214860e-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 0.0025455 0.0016931 0.1299999 0.1327126 0.623779 0.7821490 NA
1 54676 rs2462492 C T 0.0018091 0.0016772 0.2800000 0.2807381 0.400411 NA NA
1 86028 rs114608975 T C -0.0014147 0.0026816 0.5999997 0.5977980 0.103549 0.0277556 NA
1 91536 rs6702460 G T 0.0002117 0.0016515 0.9000000 0.8979863 0.456858 0.4207270 NA
1 234313 rs8179466 C T 0.0046974 0.0032560 0.1499999 0.1491026 0.074509 NA NA
1 534192 rs6680723 C T 0.0025068 0.0018864 0.1800002 0.1838706 0.240965 NA NA
1 546697 rs12025928 A G -0.0044770 0.0023535 0.0569994 0.0571322 0.913480 NA NA
1 693731 rs12238997 A G 0.0011727 0.0015806 0.4600002 0.4581275 0.116331 0.1417730 NA
1 705882 rs72631875 G A 0.0022380 0.0023165 0.3300000 0.3339833 0.067283 0.0315495 NA
1 706368 rs55727773 A G -0.0011263 0.0011710 0.3400001 0.3361026 0.515650 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0013053 0.0024576 0.5999997 0.5953283 0.041948 0.0473243 NA
22 51219766 rs182321900 C T 0.0108293 0.0114603 0.3400001 0.3446893 0.001933 NA NA
22 51220146 rs868950473 C T 0.0095696 0.0113518 0.4000000 0.3992259 0.001982 NA NA
22 51221190 rs369304721 G A -0.0014557 0.0024535 0.5500004 0.5529689 0.049727 NA NA
22 51221731 rs115055839 T C -0.0005381 0.0018350 0.7700005 0.7693302 0.073229 0.0625000 NA
22 51222100 rs114553188 G T -0.0015228 0.0021599 0.4799997 0.4807894 0.054466 0.0880591 NA
22 51223637 rs375798137 G A -0.0014825 0.0021704 0.4899999 0.4945719 0.054095 0.0788738 NA
22 51229805 rs9616985 T C -0.0004347 0.0018416 0.8100000 0.8133804 0.073064 0.0730831 NA
22 51232488 rs376461333 A G -0.0010203 0.0043371 0.8100000 0.8140098 0.020053 NA NA
22 51237063 rs3896457 T C 0.0009007 0.0011263 0.4199997 0.4238734 0.297982 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623779 ES:SE:LP:AF:ID  0.00254553:0.00169308:0.886057:0.623779:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400411 ES:SE:LP:AF:ID  0.00180909:0.00167716:0.552842:0.400411:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -0.00141471:0.00268156:0.221849:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456858 ES:SE:LP:AF:ID  0.000211729:0.00165148:0.0457575:0.456858:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074509 ES:SE:LP:AF:ID  0.00469743:0.00325598:0.823909:0.074509:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  0.00250683:0.00188635:0.744727:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91348  ES:SE:LP:AF:ID  -0.00447704:0.00235349:1.24413:0.91348:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116331 ES:SE:LP:AF:ID  0.00117273:0.00158064:0.337242:0.116331:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067283 ES:SE:LP:AF:ID  0.00223804:0.00231652:0.481486:0.067283:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.00112634:0.00117096:0.468521:0.51565:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032979 ES:SE:LP:AF:ID  -0.00224175:0.00295311:0.346787:0.032979:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036592 ES:SE:LP:AF:ID  -0.00216443:0.00268244:0.376751:0.036592:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036709 ES:SE:LP:AF:ID  -0.00219357:0.00267229:0.387216:0.036709:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036409 ES:SE:LP:AF:ID  -0.00231663:0.0026915:0.408935:0.036409:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016399 ES:SE:LP:AF:ID  -0.00844684:0.00414387:1.37675:0.016399:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036948 ES:SE:LP:AF:ID  -0.00230542:0.00266169:0.408935:0.036948:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037047 ES:SE:LP:AF:ID  -0.00215395:0.00265247:0.376751:0.037047:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10123  ES:SE:LP:AF:ID  -0.0017894:0.00193154:0.455932:0.10123:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959131 ES:SE:LP:AF:ID  0.0017564:0.00255853:0.309804:0.959131:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031455 ES:SE:LP:AF:ID  4.48997e-05:0.00464198:0.00436481:0.031455:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053268 ES:SE:LP:AF:ID  -0.00350198:0.00369187:0.468521:0.053268:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036563 ES:SE:LP:AF:ID  -0.00190441:0.00266975:0.318759:0.036563:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03688  ES:SE:LP:AF:ID  -0.00164758:0.0026454:0.275724:0.03688:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843235 ES:SE:LP:AF:ID  -0.000444461:0.00137001:0.124939:0.843235:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055937 ES:SE:LP:AF:ID  0.00136107:0.00221759:0.267606:0.055937:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122313 ES:SE:LP:AF:ID  0.00108303:0.00149939:0.327902:0.122313:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  -0.00080468:0.00368792:0.0809219:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121556 ES:SE:LP:AF:ID  0.00109833:0.00150002:0.337242:0.121556:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132323 ES:SE:LP:AF:ID  0.00187913:0.00147858:0.69897:0.132323:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  0.0132413:0.00537511:1.85387:0.011135:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.0057   ES:SE:LP:AF:ID  0.00271561:0.00693905:0.154902:0.0057:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002268 ES:SE:LP:AF:ID  0.00105268:0.011671:0.0315171:0.002268:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036793 ES:SE:LP:AF:ID  -0.00145279:0.00261872:0.236572:0.036793:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838971 ES:SE:LP:AF:ID  -0.000871096:0.00132675:0.29243:0.838971:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838599 ES:SE:LP:AF:ID  -0.00080431:0.00132532:0.267606:0.838599:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869776 ES:SE:LP:AF:ID  -0.00131465:0.00142203:0.443698:0.869776:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129874 ES:SE:LP:AF:ID  0.00135224:0.00142491:0.468521:0.129874:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037303 ES:SE:LP:AF:ID  -0.00143539:0.00257435:0.236572:0.037303:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037546 ES:SE:LP:AF:ID  -0.00122611:0.00255807:0.200659:0.037546:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  -0.00124462:0.00141924:0.420216:0.869119:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869216 ES:SE:LP:AF:ID  -0.00124671:0.00141981:0.420216:0.869216:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037505 ES:SE:LP:AF:ID  -0.00144666:0.00256914:0.244125:0.037505:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  -0.00121031:0.00141922:0.408935:0.869122:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005126 ES:SE:LP:AF:ID  0.00892906:0.00728381:0.657577:0.005126:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005092 ES:SE:LP:AF:ID  0.00896479:0.00730292:0.657577:0.005092:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838051 ES:SE:LP:AF:ID  -0.000670523:0.00132164:0.21467:0.838051:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037517 ES:SE:LP:AF:ID  -0.00149128:0.00257276:0.251812:0.037517:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838682 ES:SE:LP:AF:ID  -0.000706571:0.00132535:0.229148:0.838682:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013779 ES:SE:LP:AF:ID  -0.000116493:0.00462493:0.00877392:0.013779:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005536 ES:SE:LP:AF:ID  0.00112651:0.00714524:0.0604807:0.005536:rs184270342