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-3957/UKB-b-3957_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3957/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3957/UKB-b-3957_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: 0.0614 (0.0022)
Lambda GC: 1.4652
Mean Chi^2: 1.5918
Intercept: 1.031 (0.0083)
Ratio: 0.0523 (0.0139)
Analysis finished at Thu Oct 17 14:45:41 2019
Total time elapsed: 1.0m:50.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 42,
    "n_p_sig": 2662,
    "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": 0.0614,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.031,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.4652,
    "ldsc_mean_chisq": 1.5918,
    "ldsc_ratio": 0.0524
}

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 4.510000e-05 7.320000e-03 -0.1210150 -2.451000e-03 1.670000e-05 2.502400e-03 1.394720e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.117900e-03 4.844400e-03 0.0014322 1.753200e-03 2.939800e-03 6.783300e-03 7.527650e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.564509e-01 3.007362e-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 4.564520e-01 3.007120e-01 0.0000000 1.847578e-01 4.405365e-01 7.171832e-01 9.999998e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035076e-01 2.568618e-01 0.0009920 1.316900e-02 7.791400e-02 3.164560e-01 9.990040e-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 -0.0009609 0.0026342 0.7199992 0.7152701 0.623762 0.7821490 NA
1 54676 rs2462492 C T 0.0000913 0.0026094 0.9699999 0.9720999 0.400420 NA NA
1 86028 rs114608975 T C -0.0017568 0.0041722 0.6700003 0.6737039 0.103549 0.0277556 NA
1 91536 rs6702460 G T -0.0010631 0.0025694 0.6800001 0.6790456 0.456865 0.4207270 NA
1 234313 rs8179466 C T 0.0047358 0.0050661 0.3500000 0.3498884 0.074509 NA NA
1 534192 rs6680723 C T 0.0023610 0.0029350 0.4199997 0.4211471 0.240949 NA NA
1 546697 rs12025928 A G 0.0005608 0.0036615 0.8800001 0.8782719 0.913476 NA NA
1 693731 rs12238997 A G -0.0007462 0.0024595 0.7600007 0.7615942 0.116337 0.1417730 NA
1 705882 rs72631875 G A 0.0060081 0.0036040 0.0959997 0.0955057 0.067291 0.0315495 NA
1 706368 rs55727773 A G -0.0025529 0.0018220 0.1600000 0.1611543 0.515651 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0036625 0.0038271 0.3400001 0.3385730 0.041939 0.0473243 NA
22 51219766 rs182321900 C T 0.0069631 0.0178511 0.6999999 0.6964876 0.001933 NA NA
22 51220146 rs868950473 C T 0.0072686 0.0176801 0.6800001 0.6809842 0.001982 NA NA
22 51221190 rs369304721 G A 0.0040136 0.0038211 0.2900000 0.2935481 0.049710 NA NA
22 51221731 rs115055839 T C 0.0038896 0.0028577 0.1700000 0.1734916 0.073213 0.0625000 NA
22 51222100 rs114553188 G T 0.0018244 0.0033633 0.5900000 0.5875132 0.054477 0.0880591 NA
22 51223637 rs375798137 G A 0.0018062 0.0033796 0.5900000 0.5930276 0.054106 0.0788738 NA
22 51229805 rs9616985 T C 0.0042633 0.0028681 0.1400000 0.1371581 0.073048 0.0730831 NA
22 51232488 rs376461333 A G -0.0008731 0.0067552 0.9000000 0.8971657 0.020046 NA NA
22 51237063 rs3896457 T C -0.0008199 0.0017538 0.6400000 0.6401479 0.297966 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  -0.000960912:0.00263417:0.142668:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40042  ES:SE:LP:AF:ID  9.12648e-05:0.00260945:0.0132283:0.40042:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -0.00175678:0.00417218:0.173925:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456865 ES:SE:LP:AF:ID  -0.00106313:0.0025694:0.167491:0.456865:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074509 ES:SE:LP:AF:ID  0.00473581:0.00506609:0.455932:0.074509:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240949 ES:SE:LP:AF:ID  0.00236101:0.002935:0.376751:0.240949:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  0.00056079:0.00366146:0.0555173:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116337 ES:SE:LP:AF:ID  -0.000746195:0.00245954:0.119186:0.116337:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067291 ES:SE:LP:AF:ID  0.00600811:0.00360405:1.01773:0.067291:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515651 ES:SE:LP:AF:ID  -0.00255293:0.00182196:0.79588:0.515651:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032999 ES:SE:LP:AF:ID  -0.00153145:0.00459357:0.130768:0.032999:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036615 ES:SE:LP:AF:ID  -0.00188882:0.00417253:0.187087:0.036615:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036731 ES:SE:LP:AF:ID  -0.00168666:0.00415677:0.167491:0.036731:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03643  ES:SE:LP:AF:ID  -0.00143574:0.00418671:0.136677:0.03643:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016406 ES:SE:LP:AF:ID  -0.0080909:0.00644605:0.677781:0.016406:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03697  ES:SE:LP:AF:ID  -0.00145735:0.00414024:0.142668:0.03697:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  -0.00165013:0.00412613:0.161151:0.037066:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101211 ES:SE:LP:AF:ID  0.00681183:0.00300587:1.63827:0.101211:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959106 ES:SE:LP:AF:ID  0.00256285:0.00397972:0.283997:0.959106:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031444 ES:SE:LP:AF:ID  0.014048:0.00722519:1.284:0.031444:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  -0.00617429:0.00574634:0.552842:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036584 ES:SE:LP:AF:ID  -0.0013557:0.00415283:0.130768:0.036584:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.0369   ES:SE:LP:AF:ID  -0.00157555:0.00411501:0.154902:0.0369:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  0.000529554:0.00213161:0.09691:0.843212:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055916 ES:SE:LP:AF:ID  0.00424738:0.00345128:0.657577:0.055916:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122317 ES:SE:LP:AF:ID  0.000102727:0.00233313:0.0177288:0.122317:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025711 ES:SE:LP:AF:ID  0.00377107:0.00573963:0.29243:0.025711:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12156  ES:SE:LP:AF:ID  0.000324081:0.00233412:0.05061:0.12156:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132335 ES:SE:LP:AF:ID  -0.000391393:0.00230054:0.0655015:0.132335:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011134 ES:SE:LP:AF:ID  -0.00315191:0.00836459:0.148742:0.011134:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005699 ES:SE:LP:AF:ID  -0.0242831:0.0107985:1.60206:0.005699:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002268 ES:SE:LP:AF:ID  -0.00941254:0.018162:0.221849:0.002268:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001029 ES:SE:LP:AF:ID  -0.00382264:0.0297414:0.0457575:0.001029:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036815 ES:SE:LP:AF:ID  -0.00270221:0.00407347:0.29243:0.036815:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838952 ES:SE:LP:AF:ID  -8.97255e-05:0.00206431:0.0132283:0.838952:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  8.18715e-05:0.00206209:0.0132283:0.83858:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869773 ES:SE:LP:AF:ID  -0.000811354:0.0022127:0.148742:0.869773:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129877 ES:SE:LP:AF:ID  0.0010328:0.00221721:0.19382:0.129877:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037324 ES:SE:LP:AF:ID  -0.00144214:0.00400448:0.142668:0.037324:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037568 ES:SE:LP:AF:ID  -0.00103428:0.00397918:0.102373:0.037568:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  -0.000716733:0.00220837:0.124939:0.869116:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -0.000748364:0.00220924:0.136677:0.869214:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  -0.00145276:0.0039964:0.142668:0.037526:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869118 ES:SE:LP:AF:ID  -0.000683668:0.00220832:0.119186:0.869118:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005123 ES:SE:LP:AF:ID  0.00695471:0.0113362:0.267606:0.005123:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005089 ES:SE:LP:AF:ID  0.0076417:0.0113659:0.30103:0.005089:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  2.35326e-05:0.00205636:0.00436481:0.838033:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -0.001697:0.00400204:0.173925:0.037539:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838663 ES:SE:LP:AF:ID  1.65077e-05:0.00206214:0.00436481:0.838663:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013777 ES:SE:LP:AF:ID  -0.00352285:0.00719672:0.207608:0.013777:rs181660517