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-20544_1/ukb-d-20544_1.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-20544_1/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 16:50:56 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20544_1/ukb-d-20544_1.vcf.gz ...
Read summary statistics for 9938650 SNPs.
Dropped 7645 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, 1277632 SNPs remain.
After merging with regression SNP LD, 1277632 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0114 (0.0034)
Lambda GC: 1.026
Mean Chi^2: 1.0247
Intercept: 0.9986 (0.0064)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:52:36 2019
Total time elapsed: 1.0m:40.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9413,
    "inflation_factor": 1.0218,
    "mean_EFFECT": 1.4792e-07,
    "n": 117706,
    "n_snps": 9938650,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1079005,
    "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": 196713,
    "n_est": 117690.7484,
    "ratio_se_n": 0.9999,
    "mean_diff": 3.3965e-07,
    "ratio_diff": 0.403,
    "sd_y_est1": 0.1112,
    "sd_y_est2": 0.1112,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1277632,
    "ldsc_nsnp_merge_regression_ld": 1277632,
    "ldsc_observed_scale_h2_beta": 0.0114,
    "ldsc_observed_scale_h2_se": 0.0034,
    "ldsc_intercept_beta": 0.9986,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.026,
    "ldsc_mean_chisq": 1.0247,
    "ldsc_ratio": -0.0567
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
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 9931555 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47967 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30040 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.080732e+00 6.177056e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.875612e+07 5.609430e+07 3.02000e+02 3.246684e+07 6.965993e+07 1.147367e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.000000e-07 1.095900e-03 -1.04075e-02 -5.174000e-04 -7.000000e-06 5.052000e-04 1.237020e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.353000e-04 5.613000e-04 3.79800e-04 5.042000e-04 6.836000e-04 1.207900e-03 3.143600e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.963688e-01 2.892558e-01 1.00000e-07 2.450349e-01 4.953681e-01 7.464728e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.963675e-01 2.892566e-01 1.00000e-07 2.450333e-01 4.953660e-01 7.464728e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.559692e-01 2.629483e-01 8.48030e-03 3.955260e-02 1.514180e-01 4.081540e-01 9.915190e-01 ▇▂▂▁▁
numeric AF_reference 196713 0.9802073 NA NA NA NA NA 2.555947e-01 2.537763e-01 0.00000e+00 4.412940e-02 1.671330e-01 4.041530e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.177060e+05 0.000000e+00 1.17706e+05 1.177060e+05 1.177060e+05 1.177060e+05 1.177060e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0003794 0.0007989 0.6348454 0.6348448 0.1116930 0.1894970 117706
1 693731 rs12238997 A G 0.0005853 0.0007564 0.4390429 0.4390413 0.1167340 0.1417730 117706
1 707522 rs371890604 G C 0.0007932 0.0008486 0.3499266 0.3499254 0.0983981 0.1293930 117706
1 717587 rs144155419 G A 0.0006001 0.0020354 0.7681376 0.7681373 0.0157480 0.0045926 117706
1 730087 rs148120343 T C -0.0003160 0.0010524 0.7639994 0.7639996 0.0569246 0.0127796 117706
1 731718 rs142557973 T C 0.0007299 0.0007177 0.3091313 0.3091282 0.1226670 0.1543530 117706
1 732032 rs61770163 A C 0.0009165 0.0007650 0.2308580 0.2308558 0.1222730 0.1555510 117706
1 734349 rs141242758 T C 0.0007027 0.0007181 0.3277698 0.3277675 0.1219240 0.1525560 117706
1 749963 rs529266287 T TAA -0.0010225 0.0007076 0.1484390 0.1484364 0.8690160 0.7641770 117706
1 751343 rs28544273 T A 0.0008626 0.0007010 0.2185219 0.2185197 0.1237000 0.2426120 117706
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0001905 0.0008440 0.8214380 0.8214372 0.0554558 0.0309934 117706
23 154923374 rs111332691 T A -0.0004082 0.0009195 0.6570993 0.6570988 0.0447811 0.0116556 117706
23 154925045 rs509981 C T -0.0005606 0.0004430 0.2057278 0.2057256 0.2446510 0.3634440 117706
23 154925895 rs538470 C T -0.0004926 0.0004530 0.2768688 0.2768671 0.2410720 0.3634440 117706
23 154927581 rs644138 G A -0.0005280 0.0004168 0.2052008 0.2051991 0.3004720 0.4635760 117706
23 154929412 rs557132 C T -0.0005553 0.0004431 0.2100942 0.2100912 0.2445260 0.3568210 117706
23 154929637 rs35185538 CT C -0.0002497 0.0004628 0.5896102 0.5896088 0.2287970 0.3011920 117706
23 154929952 rs4012982 CAA C -0.0005240 0.0004663 0.2611217 0.2611192 0.2386280 0.3165560 117706
23 154930230 rs781880 A G -0.0005338 0.0004430 0.2281603 0.2281575 0.2449510 0.3618540 117706
23 154930487 rs781879 T A 0.0003324 0.0015058 0.8252879 0.8252881 0.0196769 0.1263580 117706

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111693 ES:SE:LP:AF:SS:ID   0.000379398:0.000798869:0.197332:0.111693:117706:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116734 ES:SE:LP:AF:SS:ID   0.00058531:0.000756397:0.357493:0.116734:117706:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983981    ES:SE:LP:AF:SS:ID   0.000793177:0.000848559:0.456023:0.0983981:117706:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015748 ES:SE:LP:AF:SS:ID   0.000600052:0.00203537:0.114561:0.015748:117706:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569246    ES:SE:LP:AF:SS:ID   -0.000315968:0.00105241:0.116907:0.0569246:117706:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122667 ES:SE:LP:AF:SS:ID   0.000729943:0.000717704:0.509857:0.122667:117706:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122273 ES:SE:LP:AF:SS:ID   0.00091654:0.000764958:0.636655:0.122273:117706:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121924 ES:SE:LP:AF:SS:ID   0.000702724:0.000718076:0.484431:0.121924:117706:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.869016 ES:SE:LP:AF:SS:ID   -0.00102249:0.000707568:0.828452:0.869016:117706:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.1237   ES:SE:LP:AF:SS:ID   0.000862577:0.000701012:0.660505:0.1237:117706:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143341 ES:SE:LP:AF:SS:ID   0.00081285:0.000693292:0.617949:0.143341:117706:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123822 ES:SE:LP:AF:SS:ID   0.00088096:0.00070004:0.681448:0.123822:117706:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869774 ES:SE:LP:AF:SS:ID   -0.000729275:0.00068175:0.545533:0.869774:117706:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874549 ES:SE:LP:AF:SS:ID   -0.000888762:0.000693191:0.699407:0.874549:117706:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129687 ES:SE:LP:AF:SS:ID   0.000744849:0.000683656:0.559198:0.129687:117706:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365232    ES:SE:LP:AF:SS:ID   -0.00191565:0.00124154:0.91065:0.0365232:117706:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869367 ES:SE:LP:AF:SS:ID   -0.000732116:0.0006811:0.549105:0.869367:117706:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869439 ES:SE:LP:AF:SS:ID   -0.000740098:0.000681353:0.556917:0.869439:117706:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869367 ES:SE:LP:AF:SS:ID   -0.000731222:0.000681081:0.54822:0.869367:117706:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869442 ES:SE:LP:AF:SS:ID   -0.000702078:0.000679832:0.520373:0.869442:117706:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126965 ES:SE:LP:AF:SS:ID   0.000720259:0.000693957:0.523867:0.126965:117706:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868962 ES:SE:LP:AF:SS:ID   -0.00066133:0.000678045:0.482291:0.868962:117706:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868361 ES:SE:LP:AF:SS:ID   -0.000710618:0.000677787:0.531005:0.868361:117706:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869152 ES:SE:LP:AF:SS:ID   -0.000682255:0.000678721:0.501967:0.869152:117706:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869159 ES:SE:LP:AF:SS:ID   -0.000681695:0.00067877:0.501371:0.869159:117706:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869161 ES:SE:LP:AF:SS:ID   -0.000682243:0.000678772:0.501903:0.869161:117706:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869596 ES:SE:LP:AF:SS:ID   -0.000700885:0.000680508:0.518503:0.869596:117706:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996031    ES:SE:LP:AF:SS:ID   0.000753834:0.000790985:0.467786:0.0996031:117706:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873655 ES:SE:LP:AF:SS:ID   -0.000844114:0.000690959:0.65396:0.873655:117706:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862936 ES:SE:LP:AF:SS:ID   -0.000746448:0.000677631:0.567579:0.862936:117706:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868346 ES:SE:LP:AF:SS:ID   -0.000664178:0.000684169:0.479307:0.868346:117706:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865358 ES:SE:LP:AF:SS:ID   -0.000803016:0.000684273:0.618731:0.865358:117706:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997425    ES:SE:LP:AF:SS:ID   0.00118697:0.00081765:0.83389:0.0997425:117706:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870648 ES:SE:LP:AF:SS:ID   -0.000869846:0.000692352:0.679881:0.870648:117706:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870648 ES:SE:LP:AF:SS:ID   -0.000869846:0.000692352:0.679881:0.870648:117706:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870647 ES:SE:LP:AF:SS:ID   -0.000869907:0.000692354:0.679945:0.870647:117706:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870969 ES:SE:LP:AF:SS:ID   -0.000834828:0.000692646:0.641875:0.870969:117706:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126556 ES:SE:LP:AF:SS:ID   0.000782449:0.000693198:0.586692:0.126556:117706:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106336 ES:SE:LP:AF:SS:ID   0.000773166:0.000753348:0.516056:0.106336:117706:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854391 ES:SE:LP:AF:SS:ID   -0.000701808:0.000677473:0.522529:0.854391:117706:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839149 ES:SE:LP:AF:SS:ID   -0.0010587:0.000671316:0.940115:0.839149:117706:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763043 ES:SE:LP:AF:SS:ID   -0.000684846:0.000538015:0.692395:0.763043:117706:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105241 ES:SE:LP:AF:SS:ID   0.000337265:0.000744203:0.186811:0.105241:117706:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.129962 ES:SE:LP:AF:SS:ID   0.000689756:0.000683349:0.504739:0.129962:117706:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129662 ES:SE:LP:AF:SS:ID   0.000705711:0.000682522:0.521217:0.129662:117706:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104493 ES:SE:LP:AF:SS:ID   0.00040154:0.000750003:0.227396:0.104493:117706:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00916679   ES:SE:LP:AF:SS:ID   0.00149144:0.00262436:0.244257:0.00916679:117706:rs146076599
1   770886  rs371458725 G   A   .   PASS    AF=0.103535 ES:SE:LP:AF:SS:ID   0.000477185:0.000756275:0.277314:0.103535:117706:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.829221 ES:SE:LP:AF:SS:ID   -0.000954343:0.000665835:0.818803:0.829221:117706:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.869016 ES:SE:LP:AF:SS:ID   -0.000691925:0.000679336:0.510846:0.869016:117706:rs2977605