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-20175/UKB-b-20175_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20175/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20175/UKB-b-20175_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1207 (0.0045)
Lambda GC: 1.7742
Mean Chi^2: 2.1779
Intercept: 1.1164 (0.0137)
Ratio: 0.0988 (0.0116)
Analysis finished at Thu Oct 17 14:43:47 2019
Total time elapsed: 1.0m:40.79s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.4921,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 244,
    "n_p_sig": 26410,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.1207,
    "ldsc_observed_scale_h2_se": 0.0045,
    "ldsc_intercept_beta": 1.1164,
    "ldsc_intercept_se": 0.0137,
    "ldsc_lambda_gc": 1.7742,
    "ldsc_mean_chisq": 2.1779,
    "ldsc_ratio": 0.0988
}

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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.005000e-04 1.065490e-02 -0.1573190 -3.802300e-03 -2.470000e-05 3.713100e-03 1.840180e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.145900e-03 6.755900e-03 0.0020005 2.449400e-03 4.107000e-03 9.475200e-03 1.051200e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.335212e-01 3.054628e-01 0.0000000 1.499999e-01 4.100001e-01 6.999999e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.335222e-01 3.054387e-01 0.0000000 1.521711e-01 4.083817e-01 6.972980e-01 9.999998e-01 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035090e-01 2.568554e-01 0.0009400 1.317300e-02 7.792000e-02 3.164497e-01 9.990220e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 -0.0049584 0.0036807 0.1800002 0.1779335 0.623965 0.7821490 NA
1 54676 rs2462492 C T 0.0083085 0.0036444 0.0230001 0.0226195 0.400338 NA NA
1 86028 rs114608975 T C 0.0114591 0.0058352 0.0500000 0.0495530 0.103468 0.0277556 NA
1 91536 rs6702460 G T 0.0001042 0.0035890 0.9800000 0.9768377 0.456859 0.4207270 NA
1 234313 rs8179466 C T -0.0005451 0.0070749 0.9400001 0.9385882 0.074567 NA NA
1 534192 rs6680723 C T 0.0027491 0.0041012 0.5000000 0.5026574 0.240921 NA NA
1 546697 rs12025928 A G -0.0016524 0.0051093 0.7499995 0.7463841 0.913350 NA NA
1 693731 rs12238997 A G 0.0026283 0.0034305 0.4400003 0.4435828 0.116610 0.1417730 NA
1 705882 rs72631875 G A 0.0059142 0.0050313 0.2399999 0.2398052 0.067340 0.0315495 NA
1 706368 rs55727773 A G 0.0024981 0.0025446 0.3300000 0.3262350 0.515644 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0001229 0.0053606 0.9800000 0.9817044 0.041824 0.0473243 NA
22 51219766 rs182321900 C T 0.0459246 0.0248436 0.0649995 0.0645230 0.001950 NA NA
22 51220146 rs868950473 C T 0.0440995 0.0246075 0.0729995 0.0731144 0.001999 NA NA
22 51221190 rs369304721 G A 0.0020977 0.0053545 0.6999999 0.6952398 0.049531 NA NA
22 51221731 rs115055839 T C 0.0009723 0.0040032 0.8100000 0.8080996 0.072972 0.0625000 NA
22 51222100 rs114553188 G T -0.0001501 0.0046983 0.9699999 0.9745182 0.054573 0.0880591 NA
22 51223637 rs375798137 G A -0.0001313 0.0047209 0.9800000 0.9778160 0.054203 0.0788738 NA
22 51229805 rs9616985 T C 0.0010287 0.0040173 0.8000000 0.7979001 0.072823 0.0730831 NA
22 51232488 rs376461333 A G 0.0054763 0.0094367 0.5600000 0.5616991 0.020095 NA NA
22 51237063 rs3896457 T C 0.0029160 0.0024528 0.2300001 0.2345130 0.297842 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623965 ES:SE:LP:AF:ID  -0.00495845:0.00368071:0.744727:0.623965:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400338 ES:SE:LP:AF:ID  0.00830853:0.00364441:1.63827:0.400338:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103468 ES:SE:LP:AF:ID  0.0114591:0.00583516:1.30103:0.103468:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  0.000104202:0.003589:0.00877392:0.456859:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074567 ES:SE:LP:AF:ID  -0.000545082:0.0070749:0.0268721:0.074567:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240921 ES:SE:LP:AF:ID  0.0027491:0.00410121:0.30103:0.240921:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91335  ES:SE:LP:AF:ID  -0.00165239:0.00510926:0.124939:0.91335:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11661  ES:SE:LP:AF:ID  0.00262831:0.00343051:0.356547:0.11661:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06734  ES:SE:LP:AF:ID  0.00591415:0.00503129:0.619789:0.06734:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515644 ES:SE:LP:AF:ID  0.00249806:0.00254456:0.481486:0.515644:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033052 ES:SE:LP:AF:ID  -0.00326928:0.00641011:0.21467:0.033052:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036673 ES:SE:LP:AF:ID  -0.00257279:0.00582213:0.180456:0.036673:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036796 ES:SE:LP:AF:ID  -0.00249556:0.00579931:0.173925:0.036796:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036492 ES:SE:LP:AF:ID  -0.00252931:0.0058414:0.173925:0.036492:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016423 ES:SE:LP:AF:ID  0.00586219:0.00899863:0.29243:0.016423:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037034 ES:SE:LP:AF:ID  -0.00306786:0.0057767:0.221849:0.037034:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037127 ES:SE:LP:AF:ID  -0.00323178:0.00575731:0.244125:0.037127:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101398 ES:SE:LP:AF:ID  0.00309619:0.0041935:0.337242:0.101398:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958986 ES:SE:LP:AF:ID  0.00122434:0.00554947:0.0809219:0.958986:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031554 ES:SE:LP:AF:ID  -0.0053419:0.0100565:0.221849:0.031554:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053101 ES:SE:LP:AF:ID  0.00580262:0.00804775:0.327902:0.053101:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036652 ES:SE:LP:AF:ID  -0.00316213:0.00579354:0.229148:0.036652:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036968 ES:SE:LP:AF:ID  -0.00306366:0.00574117:0.229148:0.036968:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842838 ES:SE:LP:AF:ID  -0.000553439:0.00297351:0.0705811:0.842838:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056025 ES:SE:LP:AF:ID  0.00451551:0.0048158:0.455932:0.056025:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122593 ES:SE:LP:AF:ID  0.00160105:0.00325447:0.207608:0.122593:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025654 ES:SE:LP:AF:ID  0.00690325:0.00802182:0.408935:0.025654:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121836 ES:SE:LP:AF:ID  0.00181621:0.00325587:0.236572:0.121836:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132627 ES:SE:LP:AF:ID  0.000533529:0.00320983:0.0604807:0.132627:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011113 ES:SE:LP:AF:ID  0.00843341:0.0116948:0.327902:0.011113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005767 ES:SE:LP:AF:ID  -0.0130323:0.0149787:0.420216:0.005767:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00229  ES:SE:LP:AF:ID  0.0209677:0.0252326:0.387216:0.00229:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001038 ES:SE:LP:AF:ID  -0.0515861:0.0413429:0.677781:0.001038:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.03689  ES:SE:LP:AF:ID  -0.00344279:0.00568255:0.267606:0.03689:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83857  ES:SE:LP:AF:ID  0.0022051:0.00287978:0.356547:0.83857:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838187 ES:SE:LP:AF:ID  0.0020838:0.0028766:0.327902:0.838187:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86944  ES:SE:LP:AF:ID  0.000794294:0.003086:0.09691:0.86944:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.13021  ES:SE:LP:AF:ID  -0.000590883:0.00309233:0.0705811:0.13021:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037398 ES:SE:LP:AF:ID  -0.00290506:0.0055863:0.221849:0.037398:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037642 ES:SE:LP:AF:ID  -0.00296495:0.00555103:0.229148:0.037642:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868765 ES:SE:LP:AF:ID  0.000656323:0.00307979:0.0809219:0.868765:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868866 ES:SE:LP:AF:ID  0.00073008:0.00308102:0.091515:0.868866:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037601 ES:SE:LP:AF:ID  -0.0027773:0.00557509:0.207608:0.037601:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868767 ES:SE:LP:AF:ID  0.000633049:0.00307969:0.0757207:0.868767:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005156 ES:SE:LP:AF:ID  -0.0424189:0.0157797:2.14267:0.005156:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005122 ES:SE:LP:AF:ID  -0.0417896:0.0158205:2.08092:0.005122:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837633 ES:SE:LP:AF:ID  0.00201575:0.00286848:0.318759:0.837633:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037612 ES:SE:LP:AF:ID  -0.00297613:0.00558312:0.229148:0.037612:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838265 ES:SE:LP:AF:ID  0.00206396:0.00287653:0.327902:0.838265:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013667 ES:SE:LP:AF:ID  -0.00465146:0.0100945:0.19382:0.013667:rs181660517