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-19379/UKB-b-19379_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19379/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19379/UKB-b-19379_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: 0.227 (0.0069)
Lambda GC: 2.3961
Mean Chi^2: 3.3504
Intercept: 1.2241 (0.0204)
Ratio: 0.0953 (0.0087)
Analysis finished at Thu Oct 17 14:43:12 2019
Total time elapsed: 1.0m:56.31s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.8418,
    "mean_EFFECT": -3.74e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 475,
    "n_p_sig": 73190,
    "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": 0.227,
    "ldsc_observed_scale_h2_se": 0.0069,
    "ldsc_intercept_beta": 1.2241,
    "ldsc_intercept_se": 0.0204,
    "ldsc_lambda_gc": 2.3961,
    "ldsc_mean_chisq": 3.3504,
    "ldsc_ratio": 0.0953
}

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 -3.700000e-06 7.672400e-03 -0.1088160 -2.928600e-03 6.000000e-06 2.924900e-03 2.061840e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.860700e-03 4.600500e-03 0.0013578 1.665200e-03 2.792300e-03 6.442400e-03 7.146740e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.003100e-01 3.114882e-01 0.0000000 1.100001e-01 3.599996e-01 6.700003e-01 1.000000e+00 ▇▅▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.003121e-01 3.114663e-01 0.0000000 1.051171e-01 3.581372e-01 6.678782e-01 1.000000e+00 ▇▅▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568614e-01 0.0009850 1.316900e-02 7.791350e-02 3.164550e-01 9.990060e-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 -0.0013092 0.0024946 0.5999997 0.5997140 0.623734 0.7821490 NA
1 54676 rs2462492 C T -0.0020167 0.0024719 0.4100001 0.4145798 0.400350 NA NA
1 86028 rs114608975 T C 0.0029562 0.0039514 0.4500005 0.4543781 0.103559 0.0277556 NA
1 91536 rs6702460 G T -0.0042085 0.0024333 0.0840001 0.0837107 0.456839 0.4207270 NA
1 234313 rs8179466 C T 0.0089038 0.0048001 0.0640000 0.0636111 0.074493 NA NA
1 534192 rs6680723 C T 0.0065150 0.0027798 0.0189998 0.0190969 0.240938 NA NA
1 546697 rs12025928 A G -0.0042131 0.0034679 0.2200002 0.2244117 0.913464 NA NA
1 693731 rs12238997 A G 0.0034484 0.0023308 0.1400000 0.1390032 0.116216 0.1417730 NA
1 705882 rs72631875 G A 0.0068592 0.0034129 0.0439997 0.0444541 0.067321 0.0315495 NA
1 706368 rs55727773 A G 0.0022435 0.0017259 0.1900002 0.1936316 0.515783 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0050170 0.0036456 0.1700000 0.1687609 0.041966 0.0473243 NA
22 51219766 rs182321900 C T 0.0046818 0.0169677 0.7800007 0.7826081 0.001942 NA NA
22 51220146 rs868950473 C T 0.0039201 0.0168061 0.8200001 0.8155646 0.001991 NA NA
22 51221190 rs369304721 G A 0.0031617 0.0036389 0.3800004 0.3849296 0.049761 NA NA
22 51221731 rs115055839 T C 0.0010232 0.0027220 0.7099994 0.7069946 0.073280 0.0625000 NA
22 51222100 rs114553188 G T -0.0006400 0.0032048 0.8400000 0.8417068 0.054487 0.0880591 NA
22 51223637 rs375798137 G A -0.0006670 0.0032203 0.8400000 0.8359100 0.054116 0.0788738 NA
22 51229805 rs9616985 T C 0.0009131 0.0027319 0.7400005 0.7381841 0.073113 0.0730831 NA
22 51232488 rs376461333 A G -0.0050940 0.0064348 0.4299995 0.4285753 0.020055 NA NA
22 51237063 rs3896457 T C -0.0003591 0.0016717 0.8300000 0.8299211 0.297892 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623734 ES:SE:LP:AF:ID  -0.00130918:0.00249457:0.221849:0.623734:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40035  ES:SE:LP:AF:ID  -0.00201671:0.00247188:0.387216:0.40035:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103559 ES:SE:LP:AF:ID  0.00295617:0.00395138:0.346787:0.103559:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456839 ES:SE:LP:AF:ID  -0.00420848:0.00243328:1.07572:0.456839:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074493 ES:SE:LP:AF:ID  0.00890376:0.00480014:1.19382:0.074493:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240938 ES:SE:LP:AF:ID  0.00651495:0.00277985:1.72125:0.240938:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913464 ES:SE:LP:AF:ID  -0.00421312:0.00346793:0.657577:0.913464:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116216 ES:SE:LP:AF:ID  0.00344842:0.00233078:0.853872:0.116216:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067321 ES:SE:LP:AF:ID  0.00685921:0.00341291:1.35655:0.067321:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515783 ES:SE:LP:AF:ID  0.00224349:0.00172588:0.721246:0.515783:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032987 ES:SE:LP:AF:ID  -0.00609152:0.00435142:0.79588:0.032987:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036599 ES:SE:LP:AF:ID  -0.00564047:0.00395291:0.823909:0.036599:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036717 ES:SE:LP:AF:ID  -0.00646107:0.00393766:1:0.036717:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036414 ES:SE:LP:AF:ID  -0.00557172:0.00396628:0.79588:0.036414:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016391 ES:SE:LP:AF:ID  0.000893274:0.00610844:0.0555173:0.016391:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036954 ES:SE:LP:AF:ID  -0.00554588:0.00392231:0.79588:0.036954:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  -0.00569518:0.00390877:0.823909:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101236 ES:SE:LP:AF:ID  -0.00101006:0.00284701:0.142668:0.101236:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959097 ES:SE:LP:AF:ID  0.00499557:0.003769:0.721246:0.959097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031461 ES:SE:LP:AF:ID  0.0089292:0.00683811:0.721246:0.031461:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  -0.00179317:0.00543918:0.130768:0.053255:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036573 ES:SE:LP:AF:ID  -0.00574323:0.00393387:0.853872:0.036573:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  -0.00463307:0.00389805:0.638272:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843322 ES:SE:LP:AF:ID  -0.000840609:0.00201945:0.167491:0.843322:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055858 ES:SE:LP:AF:ID  0.00809446:0.00327042:1.88606:0.055858:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122192 ES:SE:LP:AF:ID  0.00238327:0.00221094:0.552842:0.122192:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  -0.00575322:0.00543273:0.537602:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121432 ES:SE:LP:AF:ID  0.00229972:0.00221187:0.522879:0.121432:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132218 ES:SE:LP:AF:ID  0.000375517:0.0021797:0.0655015:0.132218:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011122 ES:SE:LP:AF:ID  -0.00199683:0.0079303:0.09691:0.011122:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  -0.0105828:0.0102302:0.522879:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002287 ES:SE:LP:AF:ID  0.00409628:0.0171272:0.091515:0.002287:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  0.0244969:0.0280162:0.420216:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036805 ES:SE:LP:AF:ID  -0.00564272:0.00385865:0.853872:0.036805:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839051 ES:SE:LP:AF:ID  -0.000759802:0.00195557:0.154902:0.839051:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838678 ES:SE:LP:AF:ID  -0.000674891:0.00195342:0.136677:0.838678:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869873 ES:SE:LP:AF:ID  -0.00232014:0.00209637:0.568636:0.869873:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129766 ES:SE:LP:AF:ID  0.00248112:0.00210075:0.619789:0.129766:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  -0.0044584:0.00379326:0.619789:0.037317:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037562 ES:SE:LP:AF:ID  -0.00457854:0.00376923:0.657577:0.037562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869218 ES:SE:LP:AF:ID  -0.00230258:0.00209225:0.568636:0.869218:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869315 ES:SE:LP:AF:ID  -0.00223799:0.00209308:0.552842:0.869315:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037515 ES:SE:LP:AF:ID  -0.00441267:0.00378575:0.619789:0.037515:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86922  ES:SE:LP:AF:ID  -0.0023028:0.00209221:0.568636:0.86922:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005131 ES:SE:LP:AF:ID  0.00674961:0.0107258:0.275724:0.005131:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005098 ES:SE:LP:AF:ID  0.00703939:0.0107536:0.29243:0.005098:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838135 ES:SE:LP:AF:ID  -0.000695043:0.00194804:0.142668:0.838135:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037528 ES:SE:LP:AF:ID  -0.00448492:0.00379111:0.619789:0.037528:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838767 ES:SE:LP:AF:ID  -0.0008586:0.00195354:0.180456:0.838767:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  -0.00695212:0.00681633:0.508638:0.013775:rs181660517