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/dev/ukb-d-import/processed/ukb-d-5325_4/ukb-d-5325_4.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5325_4/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 16:52:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5325_4/ukb-d-5325_4.vcf.gz ...
Read summary statistics for 9675798 SNPs.
Dropped 7306 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1275004 SNPs remain.
After merging with regression SNP LD, 1275004 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0732 (0.0738)
Lambda GC: 1.0144
Mean Chi^2: 1.0145
Intercept: 1.0062 (0.0068)
Ratio: 0.43 (0.4708)
Analysis finished at Mon Nov 25 16:53:36 2019
Total time elapsed: 1.0m:35.16s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9399,
    "inflation_factor": 1.0113,
    "mean_EFFECT": 0,
    "n": 5719,
    "n_snps": 9675798,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1062244,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 192791,
    "n_est": 5736.403,
    "ratio_se_n": 1.0015,
    "mean_diff": 0.0001,
    "ratio_diff": 201.0111,
    "sd_y_est1": 0.3961,
    "sd_y_est2": 0.3967,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1275004,
    "ldsc_nsnp_merge_regression_ld": 1275004,
    "ldsc_observed_scale_h2_beta": 0.0732,
    "ldsc_observed_scale_h2_se": 0.0738,
    "ldsc_intercept_beta": 1.0062,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0144,
    "ldsc_mean_chisq": 1.0145,
    "ldsc_ratio": 0.4276
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 9669038 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47031 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29676 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.078660e+00 6.175424e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.873775e+07 5.611975e+07 302.0000000 3.242880e+07 6.961632e+07 1.147430e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.470000e-05 1.663310e-02 -0.1446260 -8.047100e-03 -2.630000e-05 7.990200e-03 1.806680e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.444120e-02 8.213900e-03 0.0060088 8.107500e-03 1.080420e-02 1.847970e-02 4.595030e-02 ▇▂▂▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.980231e-01 2.890742e-01 0.0000002 2.471172e-01 4.975858e-01 7.478698e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.979951e-01 2.890910e-01 0.0000002 2.470679e-01 4.975589e-01 7.478584e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.622165e-01 2.628535e-01 0.0099366 4.454120e-02 1.604150e-01 4.172060e-01 9.900630e-01 ▇▂▂▁▁
numeric AF_reference 192791 0.9800749 NA NA NA NA NA 2.616603e-01 2.536628e-01 0.0000000 5.051920e-02 1.755190e-01 4.125400e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.719000e+03 0.000000e+00 5719.0000000 5.719000e+03 5.719000e+03 5.719000e+03 5.719000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0033418 0.0127972 0.7939973 0.7939876 0.1138240 0.1894970 5719
1 693731 rs12238997 A G -0.0009964 0.0123133 0.9355069 0.9355040 0.1160130 0.1417730 5719
1 707522 rs371890604 G C 0.0051719 0.0137167 0.7061517 0.7061376 0.0990976 0.1293930 5719
1 717587 rs144155419 G A -0.0128266 0.0355860 0.7185318 0.7185185 0.0137193 0.0045926 5719
1 730087 rs148120343 T C -0.0014497 0.0168018 0.9312460 0.9312433 0.0585695 0.0127796 5719
1 731718 rs142557973 T C 0.0010321 0.0116484 0.9293960 0.9293929 0.1224010 0.1543530 5719
1 732032 rs61770163 A C 0.0091535 0.0124549 0.4624130 0.4623826 0.1219710 0.1555510 5719
1 734349 rs141242758 T C 0.0011787 0.0116572 0.9194639 0.9194597 0.1216620 0.1525560 5719
1 749963 rs529266287 T TAA 0.0015748 0.0115652 0.8916939 0.8916885 0.8709570 0.7641770 5719
1 751343 rs28544273 T A -0.0028528 0.0114438 0.8031440 0.8031354 0.1216390 0.2426120 5719
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0099625 0.0130340 0.4446907 0.4446600 0.0574919 0.0309934 5719
23 154923374 rs111332691 T A -0.0073003 0.0139774 0.6014867 0.6014663 0.0479979 0.0116556 5719
23 154925045 rs509981 C T 0.0079767 0.0071325 0.2634602 0.2634126 0.2414960 0.3634440 5719
23 154925895 rs538470 C T 0.0074190 0.0073081 0.3100680 0.3100251 0.2380400 0.3634440 5719
23 154927581 rs644138 G A 0.0094852 0.0066753 0.1553878 0.1553337 0.2992670 0.4635760 5719
23 154929412 rs557132 C T 0.0083280 0.0071377 0.2433509 0.2433020 0.2413590 0.3568210 5719
23 154929637 rs35185538 CT C 0.0102270 0.0074688 0.1709641 0.1709090 0.2262820 0.3011920 5719
23 154929952 rs4012982 CAA C 0.0108965 0.0075438 0.1486709 0.1486177 0.2341500 0.3165560 5719
23 154930230 rs781880 A G 0.0085517 0.0071343 0.2307029 0.2306532 0.2420540 0.3618540 5719
23 154930487 rs781879 T A 0.0765827 0.0236571 0.0012140 0.0012071 0.0196661 0.1263580 5719

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.113824 ES:SE:LP:AF:SS:ID   0.00334181:0.0127972:0.100181:0.113824:5719:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116013 ES:SE:LP:AF:SS:ID   -0.000996417:0.0123133:0.028953:0.116013:5719:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0990976    ES:SE:LP:AF:SS:ID   0.00517186:0.0137167:0.151102:0.0990976:5719:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0137193    ES:SE:LP:AF:SS:ID   -0.0128266:0.035586:0.143554:0.0137193:5719:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0585695    ES:SE:LP:AF:SS:ID   -0.00144967:0.0168018:0.0309356:0.0585695:5719:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122401 ES:SE:LP:AF:SS:ID   0.00103215:0.0116484:0.0317992:0.122401:5719:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121971 ES:SE:LP:AF:SS:ID   0.00915347:0.0124549:0.33497:0.121971:5719:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121662 ES:SE:LP:AF:SS:ID   0.00117871:0.0116572:0.0364653:0.121662:5719:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.870957 ES:SE:LP:AF:SS:ID   0.00157481:0.0115652:0.0497842:0.870957:5719:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.121639 ES:SE:LP:AF:SS:ID   -0.00285284:0.0114438:0.0952066:0.121639:5719:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.141418 ES:SE:LP:AF:SS:ID   0.00746269:0.0113918:0.290362:0.141418:5719:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.121759 ES:SE:LP:AF:SS:ID   -0.00274957:0.011424:0.0916174:0.121759:5719:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87174  ES:SE:LP:AF:SS:ID   -0.00187859:0.0111469:0.0623959:0.87174:5719:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.877726 ES:SE:LP:AF:SS:ID   0.00229645:0.0113484:0.0759053:0.877726:5719:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128329 ES:SE:LP:AF:SS:ID   0.00256151:0.0111439:0.0871347:0.128329:5719:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0368071    ES:SE:LP:AF:SS:ID   0.0387329:0.0199616:1.2808:0.0368071:5719:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.871439 ES:SE:LP:AF:SS:ID   -0.00212208:0.0111331:0.0711747:0.871439:5719:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.871612 ES:SE:LP:AF:SS:ID   -0.00240836:0.0111388:0.0815356:0.871612:5719:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.871443 ES:SE:LP:AF:SS:ID   -0.00214689:0.0111329:0.0720704:0.871443:5719:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   -0.00188155:0.0111164:0.0626833:0.871574:5719:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125065 ES:SE:LP:AF:SS:ID   0.00245893:0.0113427:0.0817683:0.125065:5719:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.871044 ES:SE:LP:AF:SS:ID   -0.00211039:0.0110882:0.0710621:0.871044:5719:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.870569 ES:SE:LP:AF:SS:ID   -0.00190853:0.0110712:0.0639188:0.870569:5719:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.871429 ES:SE:LP:AF:SS:ID   -0.00200295:0.0111032:0.0670952:0.871429:5719:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.871434 ES:SE:LP:AF:SS:ID   -0.00201284:0.0111039:0.0674451:0.871434:5719:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.871436 ES:SE:LP:AF:SS:ID   -0.00199836:0.0111038:0.066927:0.871436:5719:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.871832 ES:SE:LP:AF:SS:ID   -0.0017229:0.0111332:0.05699:0.871832:5719:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0993774    ES:SE:LP:AF:SS:ID   -0.00127051:0.0128852:0.0355245:0.0993774:5719:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.876855 ES:SE:LP:AF:SS:ID   0.0016152:0.0113265:0.0522684:0.876855:5719:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.865308 ES:SE:LP:AF:SS:ID   -0.00344039:0.0110682:0.121514:0.865308:5719:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.870343 ES:SE:LP:AF:SS:ID   -0.00335597:0.0112018:0.116624:0.870343:5719:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.8667   ES:SE:LP:AF:SS:ID   -0.000508455:0.0111769:0.0160505:0.8667:5719:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0966894    ES:SE:LP:AF:SS:ID   -0.00420586:0.013455:0.12228:0.0966894:5719:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.872497 ES:SE:LP:AF:SS:ID   0.0024255:0.0113042:0.0808628:0.872497:5719:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.872497 ES:SE:LP:AF:SS:ID   0.0024255:0.0113042:0.0808628:0.872497:5719:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.872493 ES:SE:LP:AF:SS:ID   0.00243024:0.0113042:0.0810339:0.872493:5719:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.873202 ES:SE:LP:AF:SS:ID   0.00281663:0.0113308:0.0949098:0.873202:5719:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12448  ES:SE:LP:AF:SS:ID   0.00087606:0.0113294:0.0276273:0.12448:5719:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107419 ES:SE:LP:AF:SS:ID   0.00354612:0.0121591:0.113188:0.107419:5719:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.857652 ES:SE:LP:AF:SS:ID   -0.000568488:0.0110898:0.018128:0.857652:5719:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838448 ES:SE:LP:AF:SS:ID   0.00225345:0.0108016:0.0784431:0.838448:5719:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.7626   ES:SE:LP:AF:SS:ID   -0.0021101:0.00873249:0.0920144:0.7626:5719:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.107449 ES:SE:LP:AF:SS:ID   0.000409012:0.0118696:0.0121046:0.107449:5719:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.128341 ES:SE:LP:AF:SS:ID   0.0037866:0.0111483:0.134229:0.128341:5719:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.12843  ES:SE:LP:AF:SS:ID   0.00346095:0.0111171:0.121725:0.12843:5719:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.106733 ES:SE:LP:AF:SS:ID   0.00126982:0.0119678:0.0383393:0.106733:5719:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.105437 ES:SE:LP:AF:SS:ID   -0.00019518:0.0120818:0.00563401:0.105437:5719:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.831893 ES:SE:LP:AF:SS:ID   0.00251841:0.0109587:0.087115:0.831893:5719:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.870864 ES:SE:LP:AF:SS:ID   -0.0025951:0.0110994:0.0887657:0.870864:5719:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.128464 ES:SE:LP:AF:SS:ID   0.00314612:0.0111179:0.109464:0.128464:5719:rs59066358