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-1489/UKB-b-1489_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1489/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:47 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1489/UKB-b-1489_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: 0.0667 (0.0028)
Lambda GC: 1.5477
Mean Chi^2: 1.681
Intercept: 1.0808 (0.0109)
Ratio: 0.1187 (0.016)
Analysis finished at Thu Oct 17 14:45:37 2019
Total time elapsed: 1.0m:50.21s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.369,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 65,
    "n_p_sig": 3644,
    "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": 0.0667,
    "ldsc_observed_scale_h2_se": 0.0028,
    "ldsc_intercept_beta": 1.0808,
    "ldsc_intercept_se": 0.0109,
    "ldsc_lambda_gc": 1.5477,
    "ldsc_mean_chisq": 1.681,
    "ldsc_ratio": 0.1186
}

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 -8.970000e-05 1.129910e-02 -0.1857860 -3.877200e-03 -2.900000e-05 3.786000e-03 1.608850e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 7.704000e-03 7.293500e-03 0.0021558 2.638800e-03 4.425000e-03 1.021020e-02 1.131620e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.476580e-01 3.019005e-01 0.0000000 1.700000e-01 4.299995e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.476571e-01 3.018776e-01 0.0000000 1.729480e-01 4.282570e-01 7.085933e-01 9.999996e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035073e-01 2.568629e-01 0.0009770 1.317000e-02 7.791100e-02 3.164600e-01 9.990150e-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 0.0020915 0.0039646 0.5999997 0.5978277 0.623674 0.7821490 NA
1 54676 rs2462492 C T -0.0071467 0.0039275 0.0690001 0.0688127 0.400481 NA NA
1 86028 rs114608975 T C 0.0045324 0.0062764 0.4700002 0.4702105 0.103606 0.0277556 NA
1 91536 rs6702460 G T 0.0004612 0.0038673 0.9100000 0.9050724 0.456785 0.4207270 NA
1 234313 rs8179466 C T 0.0075432 0.0076298 0.3200000 0.3228339 0.074485 NA NA
1 534192 rs6680723 C T 0.0047802 0.0044184 0.2800000 0.2793037 0.240927 NA NA
1 546697 rs12025928 A G 0.0055670 0.0055129 0.3100002 0.3125874 0.913520 NA NA
1 693731 rs12238997 A G 0.0022661 0.0037014 0.5400003 0.5403910 0.116299 0.1417730 NA
1 705882 rs72631875 G A 0.0059923 0.0054233 0.2700001 0.2691904 0.067284 0.0315495 NA
1 706368 rs55727773 A G -0.0006895 0.0027422 0.8000000 0.8014658 0.515690 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0064846 0.0057614 0.2599998 0.2603644 0.041944 0.0473243 NA
22 51219766 rs182321900 C T -0.0132113 0.0268593 0.6200004 0.6228108 0.001934 NA NA
22 51220146 rs868950473 C T -0.0160999 0.0266136 0.5500004 0.5452122 0.001982 NA NA
22 51221190 rs369304721 G A -0.0022145 0.0057529 0.6999999 0.7002867 0.049714 NA NA
22 51221731 rs115055839 T C -0.0031194 0.0043024 0.4700002 0.4684387 0.073211 0.0625000 NA
22 51222100 rs114553188 G T 0.0055053 0.0050657 0.2800000 0.2771315 0.054435 0.0880591 NA
22 51223637 rs375798137 G A 0.0055058 0.0050902 0.2800000 0.2794092 0.054066 0.0788738 NA
22 51229805 rs9616985 T C -0.0029543 0.0043179 0.4899999 0.4938598 0.073050 0.0730831 NA
22 51232488 rs376461333 A G 0.0155746 0.0101702 0.1299999 0.1256716 0.020034 NA NA
22 51237063 rs3896457 T C -0.0010878 0.0026405 0.6800001 0.6803595 0.297893 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623674 ES:SE:LP:AF:ID  0.00209146:0.00396465:0.221849:0.623674:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400481 ES:SE:LP:AF:ID  -0.00714672:0.00392753:1.16115:0.400481:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103606 ES:SE:LP:AF:ID  0.00453244:0.00627643:0.327902:0.103606:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456785 ES:SE:LP:AF:ID  0.000461198:0.00386729:0.0409586:0.456785:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074485 ES:SE:LP:AF:ID  0.00754318:0.00762977:0.49485:0.074485:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240927 ES:SE:LP:AF:ID  0.0047802:0.0044184:0.552842:0.240927:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91352  ES:SE:LP:AF:ID  0.00556701:0.00551294:0.508638:0.91352:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116299 ES:SE:LP:AF:ID  0.00226609:0.00370142:0.267606:0.116299:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067284 ES:SE:LP:AF:ID  0.00599235:0.00542329:0.568636:0.067284:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51569  ES:SE:LP:AF:ID  -0.00068953:0.00274221:0.09691:0.51569:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032987 ES:SE:LP:AF:ID  0.00426341:0.00691518:0.267606:0.032987:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036597 ES:SE:LP:AF:ID  0.00313847:0.00628152:0.207608:0.036597:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036714 ES:SE:LP:AF:ID  0.00320116:0.00625762:0.21467:0.036714:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036415 ES:SE:LP:AF:ID  0.00385557:0.00630246:0.267606:0.036415:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01642  ES:SE:LP:AF:ID  0.00391265:0.00969463:0.161151:0.01642:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036952 ES:SE:LP:AF:ID  0.00300603:0.00623304:0.200659:0.036952:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037048 ES:SE:LP:AF:ID  0.00349406:0.00621173:0.244125:0.037048:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10123  ES:SE:LP:AF:ID  -0.00370756:0.00452335:0.387216:0.10123:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959128 ES:SE:LP:AF:ID  -0.00501303:0.0059916:0.39794:0.959128:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031421 ES:SE:LP:AF:ID  -0.0120541:0.0108831:0.568636:0.031421:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053266 ES:SE:LP:AF:ID  0.00529911:0.00864533:0.267606:0.053266:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036569 ES:SE:LP:AF:ID  0.00299941:0.00625165:0.200659:0.036569:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036885 ES:SE:LP:AF:ID  0.00373721:0.00619483:0.259637:0.036885:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843266 ES:SE:LP:AF:ID  -0.00352518:0.00320832:0.568636:0.843266:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055873 ES:SE:LP:AF:ID  0.00456781:0.0051949:0.420216:0.055873:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122262 ES:SE:LP:AF:ID  0.00241046:0.00351188:0.309804:0.122262:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025693 ES:SE:LP:AF:ID  -0.00684766:0.00864252:0.366532:0.025693:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121506 ES:SE:LP:AF:ID  0.00208974:0.00351334:0.259637:0.121506:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13226  ES:SE:LP:AF:ID  0.00252237:0.00346312:0.327902:0.13226:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011121 ES:SE:LP:AF:ID  -0.00520894:0.0125987:0.167491:0.011121:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005683 ES:SE:LP:AF:ID  0.00673582:0.0162763:0.167491:0.005683:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00226  ES:SE:LP:AF:ID  -0.000898794:0.0274021:0.0132283:0.00226:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001025 ES:SE:LP:AF:ID  0.027186:0.0449292:0.259637:0.001025:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036801 ES:SE:LP:AF:ID  0.00428198:0.00613233:0.309804:0.036801:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838992 ES:SE:LP:AF:ID  -0.00400272:0.00310694:0.69897:0.838992:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838621 ES:SE:LP:AF:ID  -0.00404822:0.00310357:0.721246:0.838621:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869821 ES:SE:LP:AF:ID  -0.00324515:0.00333041:0.481486:0.869821:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129832 ES:SE:LP:AF:ID  0.00321712:0.00333705:0.468521:0.129832:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037306 ES:SE:LP:AF:ID  0.00440869:0.0060288:0.337242:0.037306:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  0.00455201:0.00599059:0.346787:0.03755:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869161 ES:SE:LP:AF:ID  -0.00344962:0.00332383:0.522879:0.869161:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869255 ES:SE:LP:AF:ID  -0.00357065:0.00332513:0.552842:0.869255:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037508 ES:SE:LP:AF:ID  0.00400605:0.00601648:0.29243:0.037508:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869164 ES:SE:LP:AF:ID  -0.00336662:0.00332376:0.508638:0.869164:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005139 ES:SE:LP:AF:ID  0.00403296:0.017032:0.091515:0.005139:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005105 ES:SE:LP:AF:ID  0.00401697:0.0170771:0.091515:0.005105:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838071 ES:SE:LP:AF:ID  -0.00404113:0.00309495:0.721246:0.838071:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037521 ES:SE:LP:AF:ID  0.00424291:0.00602502:0.318759:0.037521:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.8387   ES:SE:LP:AF:ID  -0.0039769:0.0031036:0.69897:0.8387:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  -0.000426721:0.010831:0.0132283:0.013776:rs181660517