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-6911/UKB-b-6911_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6911/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-6911/UKB-b-6911_data.vcf.gz ...
Read summary statistics for 5897625 SNPs.
Dropped 2603 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, 1207460 SNPs remain.
After merging with regression SNP LD, 1207460 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0072 (0.001)
Lambda GC: 1.0633
Mean Chi^2: 1.0653
Intercept: 0.9976 (0.0069)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:41:18 2019
Total time elapsed: 1.0m:0.66s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9231,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 9.9855e-07,
    "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": 53034,
    "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": 1207460,
    "ldsc_nsnp_merge_regression_ld": 1207460,
    "ldsc_observed_scale_h2_beta": 0.0072,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 0.9976,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.0633,
    "ldsc_mean_chisq": 1.0653,
    "ldsc_ratio": -0.0368
}

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 5895039 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 5897625 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 8.672029e+00 5.762840e+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 7.859132e+07 5.652926e+07 828.0000000 3.199764e+07 6.905044e+07 1.145191e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.000000e-06 4.649000e-04 -0.0039686 -2.807000e-04 -2.000000e-07 2.801000e-04 4.232900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.307000e-04 1.391000e-04 0.0002864 3.159000e-04 3.770000e-04 5.126000e-04 1.469600e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.891335e-01 2.910243e-01 0.0000016 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 4.891355e-01 2.909989e-01 0.0000016 2.347470e-01 4.853714e-01 7.411257e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.156441e-01 2.522354e-01 0.0363080 1.014080e-01 2.352520e-01 4.813110e-01 9.636900e-01 ▇▃▂▂▁
numeric AF_reference 53034 0.9910076 NA NA NA NA NA NA NA 3.118976e-01 2.456176e-01 0.0000000 1.100240e-01 2.422120e-01 4.716450e-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 0.0003498 0.0005271 0.5099998 0.5069268 0.623763 0.7821490 NA
1 54676 rs2462492 C T 0.0005347 0.0005222 0.3100002 0.3058532 0.400401 NA NA
1 86028 rs114608975 T C -0.0016378 0.0008349 0.0500000 0.0497985 0.103556 0.0277556 NA
1 91536 rs6702460 G T 0.0006864 0.0005142 0.1800002 0.1819183 0.456851 0.4207270 NA
1 234313 rs8179466 C T 0.0010335 0.0010138 0.3100002 0.3080122 0.074508 NA NA
1 534192 rs6680723 C T -0.0006865 0.0005873 0.2399999 0.2424318 0.240960 NA NA
1 546697 rs12025928 A G 0.0014925 0.0007327 0.0420001 0.0416539 0.913473 NA NA
1 693731 rs12238997 A G -0.0008477 0.0004922 0.0850002 0.0850141 0.116325 0.1417730 NA
1 705882 rs72631875 G A -0.0003564 0.0007213 0.6200004 0.6212468 0.067285 0.0315495 NA
1 706368 rs55727773 A G 0.0000440 0.0003646 0.9000000 0.9038883 0.515650 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0002989 0.0005698 0.5999997 0.5998036 0.073625 0.0826677 NA
22 51219006 rs28729663 G A -0.0001468 0.0004398 0.7400005 0.7386070 0.137953 0.2052720 NA
22 51219387 rs9616832 T C -0.0002220 0.0005709 0.6999999 0.6973782 0.073747 0.0654952 NA
22 51219704 rs147475742 G A 0.0001598 0.0007651 0.8300000 0.8345532 0.041955 0.0473243 NA
22 51221190 rs369304721 G A 0.0000983 0.0007638 0.9000000 0.8976186 0.049731 NA NA
22 51221731 rs115055839 T C -0.0002704 0.0005713 0.6400000 0.6359462 0.073238 0.0625000 NA
22 51222100 rs114553188 G T 0.0004180 0.0006726 0.5300002 0.5342596 0.054459 0.0880591 NA
22 51223637 rs375798137 G A 0.0004066 0.0006758 0.5500004 0.5474252 0.054088 0.0788738 NA
22 51229805 rs9616985 T C -0.0002630 0.0005733 0.6499995 0.6464102 0.073073 0.0730831 NA
22 51237063 rs3896457 T C 0.0004363 0.0003507 0.2099999 0.2133967 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.000349807:0.000527111:0.29243:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000534714:0.000522201:0.508638:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  -0.00163781:0.000834897:1.30103:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  0.000686363:0.000514179:0.744727:0.456851:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074508 ES:SE:LP:AF:ID  0.00103349:0.00101382:0.508638:0.074508:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -0.000686536:0.00058732:0.619789:0.24096:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913473 ES:SE:LP:AF:ID  0.00149251:0.000732714:1.37675:0.913473:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  -0.000847726:0.000492204:1.07058:0.116325:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067285 ES:SE:LP:AF:ID  -0.000356367:0.000721268:0.207608:0.067285:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  4.40259e-05:0.000364601:0.0457575:0.51565:rs12029736
1   715265  rs12184267  C   T   .   PASS    AF=0.036621 ES:SE:LP:AF:ID  -0.000688822:0.000834915:0.387216:0.036621:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036737 ES:SE:LP:AF:ID  -0.000746374:0.000831756:0.431798:0.036737:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036437 ES:SE:LP:AF:ID  -0.000665388:0.00083775:0.366532:0.036437:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036976 ES:SE:LP:AF:ID  -0.000640735:0.000828471:0.356547:0.036976:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037072 ES:SE:LP:AF:ID  -0.00068131:0.000825632:0.387216:0.037072:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101199 ES:SE:LP:AF:ID  0.000489261:0.000601568:0.376751:0.101199:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959096 ES:SE:LP:AF:ID  0.000440053:0.000796306:0.236572:0.959096:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.000579729:0.00114998:0.21467:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  -0.000543623:0.000830977:0.29243:0.03659:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036907 ES:SE:LP:AF:ID  -0.000595778:0.000823412:0.327902:0.036907:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  0.000654071:0.000426558:0.886057:0.843212:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055911 ES:SE:LP:AF:ID  -4.7795e-05:0.000690663:0.0268721:0.055911:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122307 ES:SE:LP:AF:ID  -0.000721636:0.000466904:0.920819:0.122307:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  -0.000680441:0.0004671:0.823909:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  -0.00076588:0.000460374:1.01773:0.13233:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036821 ES:SE:LP:AF:ID  -0.00049588:0.000815085:0.267606:0.036821:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  0.000653116:0.000413091:0.958607:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  0.000635348:0.000412646:0.920819:0.83858:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  0.000646725:0.000442786:0.853872:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129871 ES:SE:LP:AF:ID  -0.000591479:0.000443692:0.744727:0.129871:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037332 ES:SE:LP:AF:ID  -0.000540543:0.000801264:0.30103:0.037332:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037576 ES:SE:LP:AF:ID  -0.000477017:0.000796201:0.259637:0.037576:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  0.000637164:0.000441919:0.823909:0.869123:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  0.000631826:0.000442094:0.823909:0.869221:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037534 ES:SE:LP:AF:ID  -0.000504735:0.000799645:0.275724:0.037534:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  0.000634805:0.00044191:0.823909:0.869126:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  0.000637132:0.000411501:0.920819:0.838033:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037547 ES:SE:LP:AF:ID  -0.00050513:0.000800775:0.275724:0.037547:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  0.000648563:0.000412657:0.920819:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  0.000637683:0.000418238:0.886057:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869405 ES:SE:LP:AF:ID  0.000616751:0.000441399:0.79588:0.869405:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  0.000597243:0.000440288:0.769551:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867905 ES:SE:LP:AF:ID  0.000597263:0.000439444:0.769551:0.867905:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  0.000604407:0.000440649:0.769551:0.869095:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  0.000603883:0.000440683:0.769551:0.869104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  0.000608193:0.000440693:0.769551:0.869112:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869589 ES:SE:LP:AF:ID  0.000637821:0.000441902:0.823909:0.869589:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037596 ES:SE:LP:AF:ID  -0.00074087:0.000796086:0.455932:0.037596:rs114525117
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  0.000712463:0.00041072:1.08092:0.838313:rs1048488
1   760998  rs148828841 C   A   .   PASS    AF=0.037033 ES:SE:LP:AF:ID  -0.000712856:0.000810981:0.420216:0.037033:rs148828841