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-1428_2/ukb-d-1428_2.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-1428_2/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 16:57:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1428_2/ukb-d-1428_2.vcf.gz ...
Read summary statistics for 10388683 SNPs.
Dropped 8251 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, 1280262 SNPs remain.
After merging with regression SNP LD, 1280262 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0006 (0.0012)
Lambda GC: 1.0081
Mean Chi^2: 1.0097
Intercept: 1.0139 (0.0058)
Ratio: 1.4304 (0.602)
Analysis finished at Mon Nov 25 16:59:15 2019
Total time elapsed: 1.0m:44.4s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9435,
    "inflation_factor": 1.0074,
    "mean_EFFECT": 2.3394e-07,
    "n": 360291,
    "n_snps": 10388683,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1105656,
    "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": 204366,
    "n_est": 360492.5957,
    "ratio_se_n": 1.0003,
    "mean_diff": 3.0824e-06,
    "ratio_diff": 25.5432,
    "sd_y_est1": 0.0732,
    "sd_y_est2": 0.0732,
    "r2_sum1": 4.5168e-07,
    "r2_sum2": 0.0001,
    "r2_sum3": 0.0001,
    "r2_sum4": 0.0001,
    "ldsc_nsnp_merge_refpanel_ld": 1280262,
    "ldsc_nsnp_merge_regression_ld": 1280262,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0139,
    "ldsc_intercept_se": 0.0058,
    "ldsc_lambda_gc": 1.0081,
    "ldsc_mean_chisq": 1.0097,
    "ldsc_ratio": 1.433
}

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 TRUE
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 10380997 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 49398 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 30615 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.076514e+00 6.178243e+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 7.878827e+07 5.606053e+07 3.02000e+02 3.254736e+07 6.971684e+07 1.147375e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 2.000000e-07 4.574000e-04 -4.32160e-03 -1.996000e-04 -1.200000e-06 1.960000e-04 5.573700e-03 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 3.815000e-04 2.494000e-04 1.41900e-04 1.914000e-04 2.675000e-04 4.997000e-04 1.416000e-03 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.988566e-01 2.886629e-01 0.00000e+00 2.489671e-01 4.984195e-01 7.483625e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.988561e-01 2.886632e-01 0.00000e+00 2.489658e-01 4.984186e-01 7.483621e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 2.458368e-01 2.627312e-01 6.48000e-03 3.231970e-02 1.367470e-01 3.932460e-01 9.935200e-01 ▇▂▂▁▁
numeric AF_reference 204366 0.980328 NA NA NA NA NA 2.456713e-01 2.536487e-01 0.00000e+00 3.434500e-02 1.533550e-01 3.899760e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.000000 NA NA NA NA NA 3.602910e+05 0.000000e+00 3.60291e+05 3.602910e+05 3.602910e+05 3.602910e+05 3.602910e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0000839 0.0003022 0.7814047 0.7814041 0.1106410 0.1894970 360291
1 693731 rs12238997 A G -0.0003765 0.0002855 0.1872962 0.1872951 0.1158290 0.1417730 360291
1 707522 rs371890604 G C -0.0003519 0.0003210 0.2729342 0.2729322 0.0972946 0.1293930 360291
1 717587 rs144155419 G A 0.0001170 0.0007661 0.8786000 0.8786000 0.0156835 0.0045926 360291
1 730087 rs148120343 T C -0.0002373 0.0003978 0.5508724 0.5508714 0.0564617 0.0127796 360291
1 731718 rs142557973 T C -0.0002968 0.0002708 0.2730731 0.2730721 0.1217350 0.1543530 360291
1 732032 rs61770163 A C -0.0002988 0.0002889 0.3009997 0.3009993 0.1211610 0.1555510 360291
1 734349 rs141242758 T C -0.0002872 0.0002709 0.2890540 0.2890531 0.1209640 0.1525560 360291
1 749963 rs529266287 T TAA 0.0003449 0.0002671 0.1966319 0.1966308 0.8697520 0.7641770 360291
1 751343 rs28544273 T A -0.0003695 0.0002645 0.1624961 0.1624948 0.1229150 0.2426120 360291
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0001095 0.0003129 0.7263083 0.7263085 0.0561529 0.0309934 360291
23 154923374 rs111332691 T A -0.0004580 0.0003439 0.1829161 0.1829151 0.0447735 0.0116556 360291
23 154925045 rs509981 C T -0.0000303 0.0001654 0.8546620 0.8546626 0.2456550 0.3634440 360291
23 154925895 rs538470 C T -0.0000486 0.0001692 0.7741498 0.7741498 0.2419630 0.3634440 360291
23 154927581 rs644138 G A -0.0000081 0.0001556 0.9583320 0.9583322 0.3021960 0.4635760 360291
23 154929412 rs557132 C T -0.0000354 0.0001655 0.8308190 0.8308180 0.2455070 0.3568210 360291
23 154929637 rs35185538 CT C -0.0000697 0.0001727 0.6866114 0.6866110 0.2297500 0.3011920 360291
23 154929952 rs4012982 CAA C -0.0001266 0.0001740 0.4668819 0.4668791 0.2394730 0.3165560 360291
23 154930230 rs781880 A G -0.0000440 0.0001655 0.7904602 0.7904606 0.2459170 0.3618540 360291
23 154930487 rs781879 T A -0.0004727 0.0005676 0.4049617 0.4049610 0.0195664 0.1263580 360291

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110641 ES:SE:LP:AF:SS:ID   -8.3851e-05:0.000302177:0.107124:0.110641:360291:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115829 ES:SE:LP:AF:SS:ID   -0.000376488:0.000285516:0.727471:0.115829:360291:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972946    ES:SE:LP:AF:SS:ID   -0.000351929:0.000321005:0.563942:0.0972946:360291:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156835    ES:SE:LP:AF:SS:ID   0.000117025:0.00076615:0.0562088:0.0156835:360291:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0564617    ES:SE:LP:AF:SS:ID   -0.000237259:0.000397782:0.258949:0.0564617:360291:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121735 ES:SE:LP:AF:SS:ID   -0.000296779:0.00027078:0.563721:0.121735:360291:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121161 ES:SE:LP:AF:SS:ID   -0.000298772:0.000288866:0.521434:0.121161:360291:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120964 ES:SE:LP:AF:SS:ID   -0.000287235:0.000270925:0.539021:0.120964:360291:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.869752 ES:SE:LP:AF:SS:ID   0.00034489:0.000267106:0.706346:0.869752:360291:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.122915 ES:SE:LP:AF:SS:ID   -0.000369477:0.00026453:0.789157:0.122915:360291:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142717 ES:SE:LP:AF:SS:ID   -0.000176676:0.000261473:0.301695:0.142717:360291:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123031 ES:SE:LP:AF:SS:ID   -0.000365853:0.000264162:0.779719:0.123031:360291:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870894 ES:SE:LP:AF:SS:ID   0.000301427:0.000257422:0.616862:0.870894:360291:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875476 ES:SE:LP:AF:SS:ID   0.000314122:0.000261691:0.638267:0.875476:360291:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128629 ES:SE:LP:AF:SS:ID   -0.000321778:0.000258061:0.67278:0.128629:360291:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036347 ES:SE:LP:AF:SS:ID   -0.0010344:0.000468285:1.56573:0.036347:360291:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870487 ES:SE:LP:AF:SS:ID   0.000294515:0.000257154:0.598441:0.870487:360291:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870591 ES:SE:LP:AF:SS:ID   0.000289232:0.000257271:0.583499:0.870591:360291:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870484 ES:SE:LP:AF:SS:ID   0.000294725:0.000257145:0.599055:0.870484:360291:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.870567 ES:SE:LP:AF:SS:ID   0.000308984:0.000256692:0.640732:0.870567:360291:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125982 ES:SE:LP:AF:SS:ID   -0.000342619:0.000261914:0.719356:0.125982:360291:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87013  ES:SE:LP:AF:SS:ID   0.000301565:0.000256074:0.621715:0.87013:360291:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869418 ES:SE:LP:AF:SS:ID   0.000291896:0.00025584:0.595339:0.869418:360291:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870285 ES:SE:LP:AF:SS:ID   0.000317303:0.000256295:0.666148:0.870285:360291:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870291 ES:SE:LP:AF:SS:ID   0.000317657:0.000256313:0.667109:0.870291:360291:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870299 ES:SE:LP:AF:SS:ID   0.000317331:0.000256321:0.666134:0.870299:360291:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870743 ES:SE:LP:AF:SS:ID   0.000313395:0.000256974:0.652409:0.870743:360291:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988398    ES:SE:LP:AF:SS:ID   -0.00054486:0.000298627:1.16705:0.0988398:360291:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.874641 ES:SE:LP:AF:SS:ID   0.000285634:0.000260808:0.563147:0.874641:360291:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864033 ES:SE:LP:AF:SS:ID   0.000354938:0.000255754:0.782003:0.864033:360291:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869431 ES:SE:LP:AF:SS:ID   0.00030568:0.000258239:0.626114:0.869431:360291:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866373 ES:SE:LP:AF:SS:ID   0.000348896:0.000258291:0.752604:0.866373:360291:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098771 ES:SE:LP:AF:SS:ID   -0.000368583:0.000309248:0.632061:0.098771:360291:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000335957:0.000261238:0.702375:0.87156:360291:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.00033596:0.000261238:0.702384:0.87156:360291:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000335782:0.000261243:0.701846:0.87156:360291:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871934 ES:SE:LP:AF:SS:ID   0.000320912:0.000261393:0.658445:0.871934:360291:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125558 ES:SE:LP:AF:SS:ID   -0.000340393:0.000261591:0.714045:0.125558:360291:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10543  ES:SE:LP:AF:SS:ID   -0.000449177:0.000284781:0.940308:0.10543:360291:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855385 ES:SE:LP:AF:SS:ID   0.000247735:0.000255661:0.478147:0.855385:360291:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838383 ES:SE:LP:AF:SS:ID   0.00013729:0.000251895:0.2323:0.838383:360291:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763375 ES:SE:LP:AF:SS:ID   0.000266326:0.000202716:0.723727:0.763375:360291:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105903 ES:SE:LP:AF:SS:ID   -0.000142751:0.000279295:0.215189:0.105903:360291:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00768211   ES:SE:LP:AF:SS:ID   -0.00116024:0.00103777:0.579119:0.00768211:360291:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.128935 ES:SE:LP:AF:SS:ID   -0.000367686:0.000257929:0.812465:0.128935:360291:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.128605 ES:SE:LP:AF:SS:ID   -0.000354207:0.000257691:0.77141:0.128605:360291:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.105196 ES:SE:LP:AF:SS:ID   -0.000156512:0.000281404:0.238008:0.105196:360291:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00908813   ES:SE:LP:AF:SS:ID   0.000715954:0.000991366:0.327737:0.00908813:360291:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00769684   ES:SE:LP:AF:SS:ID   -0.00107064:0.00104236:0.516615:0.00769684:360291:rs112563271
1   770886  rs371458725 G   A   .   PASS    AF=0.104251 ES:SE:LP:AF:SS:ID   -0.000165482:0.000283653:0.252101:0.104251:360291:rs371458725