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-5843_1/ukb-d-5843_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-5843_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 16:50:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5843_1/ukb-d-5843_1.vcf.gz ...
Read summary statistics for 10084758 SNPs.
Dropped 7832 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, 1278758 SNPs remain.
After merging with regression SNP LD, 1278758 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0446 (0.0133)
Lambda GC: 1.018
Mean Chi^2: 1.0156
Intercept: 0.9899 (0.0056)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:52:22 2019
Total time elapsed: 1.0m:32.79s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9421,
    "inflation_factor": 1.0201,
    "mean_EFFECT": 1.8987e-06,
    "n": 29317,
    "n_snps": 10084758,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1087991,
    "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": 199043,
    "n_est": 29361.3058,
    "ratio_se_n": 1.0008,
    "mean_diff": 7.1793e-06,
    "ratio_diff": 9.3127,
    "sd_y_est1": 0.2284,
    "sd_y_est2": 0.2286,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1278758,
    "ldsc_nsnp_merge_regression_ld": 1278758,
    "ldsc_observed_scale_h2_beta": 0.0446,
    "ldsc_observed_scale_h2_se": 0.0133,
    "ldsc_intercept_beta": 0.9899,
    "ldsc_intercept_se": 0.0056,
    "ldsc_lambda_gc": 1.018,
    "ldsc_mean_chisq": 1.0156,
    "ldsc_ratio": -0.6474
}

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 1.000000 3 94 0 10077479 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 48457 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 30254 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.080182e+00 6.177831e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.875925e+07 5.607798e+07 3.02000e+02 3.249268e+07 6.966700e+07 1.147298e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 1.900000e-06 4.670200e-03 -4.26288e-02 -2.144400e-03 -1.980000e-05 2.090400e-03 5.066370e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 3.949600e-03 2.439600e-03 1.54770e-03 2.080900e-03 2.847700e-03 5.124600e-03 1.420340e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.972870e-01 2.892764e-01 2.00000e-07 2.465369e-01 4.957275e-01 7.480661e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.972816e-01 2.892797e-01 2.00000e-07 2.465276e-01 4.957216e-01 7.480638e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 2.526323e-01 2.629354e-01 7.77850e-03 3.705220e-02 1.466170e-01 4.032250e-01 9.922210e-01 ▇▂▂▁▁
numeric AF_reference 199043 0.980263 NA NA NA NA NA 2.523250e-01 2.537918e-01 0.00000e+00 4.093450e-02 1.625400e-01 3.995610e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.000000 NA NA NA NA NA 2.931700e+04 0.000000e+00 2.93170e+04 2.931700e+04 2.931700e+04 2.931700e+04 2.931700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0059320 0.0033042 0.0726190 0.0726080 0.1122900 0.1894970 29317
1 693731 rs12238997 A G -0.0046839 0.0031163 0.1328370 0.1328257 0.1171770 0.1417730 29317
1 707522 rs371890604 G C -0.0068045 0.0035184 0.0531264 0.0531168 0.0977152 0.1293930 29317
1 717587 rs144155419 G A -0.0026162 0.0082615 0.7514914 0.7514884 0.0161831 0.0045926 29317
1 730087 rs148120343 T C -0.0014650 0.0043704 0.7374728 0.7374710 0.0568591 0.0127796 29317
1 731718 rs142557973 T C -0.0035982 0.0029602 0.2241692 0.2241598 0.1232340 0.1543530 29317
1 732032 rs61770163 A C -0.0049015 0.0031604 0.1209381 0.1209273 0.1222040 0.1555510 29317
1 734349 rs141242758 T C -0.0036537 0.0029620 0.2173942 0.2173851 0.1224360 0.1525560 29317
1 749963 rs529266287 T TAA 0.0027660 0.0029216 0.3437851 0.3437770 0.8685340 0.7641770 29317
1 751343 rs28544273 T A -0.0028331 0.0028975 0.3282018 0.3281946 0.1240620 0.2426120 29317
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0059731 0.0034285 0.0814854 0.0814739 0.0555757 0.0309934 29317
23 154923374 rs111332691 T A -0.0005439 0.0037525 0.8847501 0.8847484 0.0446158 0.0116556 29317
23 154925045 rs509981 C T -0.0000184 0.0018178 0.9919220 0.9919220 0.2413810 0.3634440 29317
23 154925895 rs538470 C T 0.0002346 0.0018576 0.8994990 0.8994975 0.2380390 0.3634440 29317
23 154927581 rs644138 G A -0.0015912 0.0017077 0.3514746 0.3514684 0.2974820 0.4635760 29317
23 154929412 rs557132 C T 0.0000171 0.0018184 0.9924880 0.9924882 0.2412050 0.3568210 29317
23 154929637 rs35185538 CT C -0.0009850 0.0018973 0.6036303 0.6036259 0.2254660 0.3011920 29317
23 154929952 rs4012982 CAA C 0.0004212 0.0019127 0.8257111 0.8257097 0.2349990 0.3165560 29317
23 154930230 rs781880 A G 0.0002218 0.0018180 0.9028810 0.9028799 0.2415880 0.3618540 29317
23 154930487 rs781879 T A -0.0090741 0.0061910 0.1427421 0.1427311 0.0190625 0.1263580 29317

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11229  ES:SE:LP:AF:SS:ID   -0.00593197:0.00330419:1.13895:0.11229:29317:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117177 ES:SE:LP:AF:SS:ID   -0.0046839:0.00311626:0.876681:0.117177:29317:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977152    ES:SE:LP:AF:SS:ID   -0.00680446:0.00351839:1.27469:0.0977152:29317:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0161831    ES:SE:LP:AF:SS:ID   -0.00261623:0.0082615:0.124076:0.0161831:29317:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0568591    ES:SE:LP:AF:SS:ID   -0.00146496:0.00437035:0.132254:0.0568591:29317:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123234 ES:SE:LP:AF:SS:ID   -0.00359822:0.00296018:0.649424:0.123234:29317:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122204 ES:SE:LP:AF:SS:ID   -0.00490152:0.00316045:0.917437:0.122204:29317:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122436 ES:SE:LP:AF:SS:ID   -0.00365366:0.002962:0.662752:0.122436:29317:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868534 ES:SE:LP:AF:SS:ID   0.00276601:0.00292165:0.463713:0.868534:29317:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.124062 ES:SE:LP:AF:SS:ID   -0.00283308:0.00289753:0.483859:0.124062:29317:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143368 ES:SE:LP:AF:SS:ID   -0.00421382:0.0028711:0.847082:0.143368:29317:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124208 ES:SE:LP:AF:SS:ID   -0.00276561:0.00289292:0.469694:0.124208:29317:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869483 ES:SE:LP:AF:SS:ID   0.0030685:0.00281613:0.559261:0.869483:29317:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874513 ES:SE:LP:AF:SS:ID   0.00293275:0.00286418:0.514462:0.874513:29317:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129978 ES:SE:LP:AF:SS:ID   -0.00303171:0.00282259:0.548534:0.129978:29317:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363782    ES:SE:LP:AF:SS:ID   -0.00249148:0.00511979:0.203066:0.0363782:29317:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869204 ES:SE:LP:AF:SS:ID   0.00300316:0.00281417:0.543769:0.869204:29317:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869328 ES:SE:LP:AF:SS:ID   0.00308909:0.00281591:0.564402:0.869328:29317:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869171 ES:SE:LP:AF:SS:ID   0.00301782:0.00281385:0.54743:0.869171:29317:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869276 ES:SE:LP:AF:SS:ID   0.00336799:0.00280971:0.637035:0.869276:29317:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127187 ES:SE:LP:AF:SS:ID   -0.00306568:0.00286663:0.545333:0.127187:29317:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868864 ES:SE:LP:AF:SS:ID   0.00339933:0.00280383:0.647098:0.868864:29317:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86813  ES:SE:LP:AF:SS:ID   0.00330327:0.00280129:0.622823:0.86813:29317:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869004 ES:SE:LP:AF:SS:ID   0.00345773:0.00280564:0.661938:0.869004:29317:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86901  ES:SE:LP:AF:SS:ID   0.00346025:0.00280585:0.662539:0.86901:29317:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869017 ES:SE:LP:AF:SS:ID   0.00345793:0.00280593:0.661898:0.869017:29317:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86944  ES:SE:LP:AF:SS:ID   0.00332674:0.0028125:0.625466:0.86944:29317:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.099544 ES:SE:LP:AF:SS:ID   -0.00444269:0.00326909:0.759059:0.099544:29317:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873595 ES:SE:LP:AF:SS:ID   0.00314284:0.00285544:0.566939:0.873595:29317:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86293  ES:SE:LP:AF:SS:ID   0.00311807:0.00280358:0.575001:0.86293:29317:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868409 ES:SE:LP:AF:SS:ID   0.00319921:0.00283052:0.587744:0.868409:29317:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865238 ES:SE:LP:AF:SS:ID   0.00304661:0.00282864:0.55058:0.865238:29317:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0991348    ES:SE:LP:AF:SS:ID   -0.00267652:0.00338412:0.367538:0.0991348:29317:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   0.0026698:0.00285913:0.455405:0.87041:29317:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   0.00266976:0.00285913:0.455397:0.87041:29317:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870408 ES:SE:LP:AF:SS:ID   0.00266919:0.00285913:0.455269:0.870408:29317:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870781 ES:SE:LP:AF:SS:ID   0.00296775:0.00286243:0.52311:0.870781:29317:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126677 ES:SE:LP:AF:SS:ID   -0.00296722:0.00286375:0.522663:0.126677:29317:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106304 ES:SE:LP:AF:SS:ID   -0.00404224:0.00311421:0.711532:0.106304:29317:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854014 ES:SE:LP:AF:SS:ID   0.00408755:0.00280448:0.838668:0.854014:29317:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838154 ES:SE:LP:AF:SS:ID   -5.33565e-05:0.002753:0.00676796:0.838154:29317:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762666 ES:SE:LP:AF:SS:ID   0.00194906:0.00221536:0.421386:0.762666:29317:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105297 ES:SE:LP:AF:SS:ID   0.000404572:0.003047:0.0484823:0.105297:29317:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.130002 ES:SE:LP:AF:SS:ID   -0.0033346:0.00282561:0.623502:0.130002:29317:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129764 ES:SE:LP:AF:SS:ID   -0.0032791:0.00282165:0.610488:0.129764:29317:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104434 ES:SE:LP:AF:SS:ID   0.000571721:0.00307352:0.0693392:0.104434:29317:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00929756   ES:SE:LP:AF:SS:ID   -0.00418417:0.0107973:0.155911:0.00929756:29317:rs146076599
1   770886  rs371458725 G   A   .   PASS    AF=0.103397 ES:SE:LP:AF:SS:ID   0.000529628:0.00310034:0.0633058:0.103397:29317:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.828456 ES:SE:LP:AF:SS:ID   0.00364076:0.00275998:0.72784:0.828456:29317:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.869    ES:SE:LP:AF:SS:ID   0.0033759:0.00281034:0.638901:0.869:29317:rs2977605