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-20401/ukb-d-20401.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-20401/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 17:18:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20401/ukb-d-20401.vcf.gz ...
Read summary statistics for 12641709 SNPs.
Dropped 11364 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, 1283291 SNPs remain.
After merging with regression SNP LD, 1283291 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0175 (0.0045)
Lambda GC: 1.0316
Mean Chi^2: 1.0439
Intercept: 1.0024 (0.0071)
Ratio: 0.0548 (0.161)
Analysis finished at Mon Nov 25 17:20:34 2019
Total time elapsed: 2.0m:4.61s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9505,
    "inflation_factor": 1.0261,
    "mean_EFFECT": -0,
    "n": 116746,
    "n_snps": 12641709,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1213024,
    "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": 366173,
    "n_est": 117066.0825,
    "ratio_se_n": 1.0014,
    "mean_diff": -0,
    "ratio_diff": 16.017,
    "sd_y_est1": 0.2379,
    "sd_y_est2": 0.2383,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283291,
    "ldsc_nsnp_merge_regression_ld": 1283291,
    "ldsc_observed_scale_h2_beta": 0.0175,
    "ldsc_observed_scale_h2_se": 0.0045,
    "ldsc_intercept_beta": 1.0024,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.0316,
    "ldsc_mean_chisq": 1.0439,
    "ldsc_ratio": 0.0547
}

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 12630986 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 54955 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32676 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.061139e+00 6.184979e+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 7.895509e+07 5.595544e+07 3.02000e+02 3.279255e+07 7.001261e+07 1.148108e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.060000e-05 4.539500e-03 -4.69664e-02 -1.440200e-03 -2.660000e-05 1.380600e-03 5.674060e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.395400e-03 3.008600e-03 8.15800e-04 1.149700e-03 1.934200e-03 4.771100e-03 1.693250e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.957442e-01 2.896481e-01 1.00000e-07 2.439349e-01 4.944541e-01 7.465055e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.957428e-01 2.896489e-01 1.00000e-07 2.439327e-01 4.944529e-01 7.465045e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.043052e-01 2.574682e-01 1.77990e-03 1.142190e-02 7.788850e-02 3.219750e-01 9.982200e-01 ▇▂▁▁▁
numeric AF_reference 366173 0.9710345 NA NA NA NA NA 2.069920e-01 2.493333e-01 0.00000e+00 8.386600e-03 9.924120e-02 3.278750e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.167460e+05 0.000000e+00 1.16746e+05 1.167460e+05 1.167460e+05 1.167460e+05 1.167460e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0010249 0.0017152 0.5501676 0.5501650 0.1117380 0.1894970 116746
1 693731 rs12238997 A G -0.0001263 0.0016247 0.9380440 0.9380440 0.1167610 0.1417730 116746
1 707522 rs371890604 G C -0.0002101 0.0018234 0.9082489 0.9082483 0.0983468 0.1293930 116746
1 717587 rs144155419 G A 0.0004850 0.0043632 0.9114990 0.9114986 0.0157960 0.0045926 116746
1 730087 rs148120343 T C 0.0003640 0.0022611 0.8721219 0.8721217 0.0569136 0.0127796 116746
1 731718 rs142557973 T C 0.0001773 0.0015414 0.9084370 0.9084363 0.1226930 0.1543530 116746
1 732032 rs61770163 A C -0.0000556 0.0016433 0.9730120 0.9730118 0.1222720 0.1555510 116746
1 734349 rs141242758 T C 0.0001786 0.0015423 0.9078241 0.9078237 0.1219490 0.1525560 116746
1 740284 rs61770167 C T -0.0036452 0.0070537 0.6053060 0.6053054 0.0058410 0.0023962 116746
1 742813 rs112573343 C T -0.0077667 0.0135257 0.5658209 0.5658208 0.0018323 0.1030350 116746
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0012389 0.0018125 0.4942856 0.4942853 0.0554682 0.0309934 116746
23 154923374 rs111332691 T A -0.0012047 0.0019749 0.5418649 0.5418628 0.0447981 0.0116556 116746
23 154925045 rs509981 C T 0.0003103 0.0009514 0.7443325 0.7443311 0.2447810 0.3634440 116746
23 154925895 rs538470 C T 0.0004972 0.0009729 0.6092801 0.6092786 0.2411990 0.3634440 116746
23 154927581 rs644138 G A 0.0005777 0.0008951 0.5187188 0.5187174 0.3006130 0.4635760 116746
23 154929412 rs557132 C T 0.0003241 0.0009516 0.7334204 0.7334197 0.2446550 0.3568210 116746
23 154929637 rs35185538 CT C 0.0007169 0.0009942 0.4708873 0.4708862 0.2288100 0.3011920 116746
23 154929952 rs4012982 CAA C 0.0004045 0.0010015 0.6862763 0.6862781 0.2387680 0.3165560 116746
23 154930230 rs781880 A G 0.0003828 0.0009513 0.6874102 0.6874096 0.2450820 0.3618540 116746
23 154930487 rs781879 T A 0.0017597 0.0032373 0.5867350 0.5867338 0.0196508 0.1263580 116746

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111738 ES:SE:LP:AF:SS:ID   -0.00102486:0.00171521:0.259505:0.111738:116746:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116761 ES:SE:LP:AF:SS:ID   -0.000126284:0.00162468:0.0277768:0.116761:116746:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983468    ES:SE:LP:AF:SS:ID   -0.000210138:0.00182335:0.0417951:0.0983468:116746:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015796 ES:SE:LP:AF:SS:ID   0.000484963:0.0043632:0.0402438:0.015796:116746:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569136    ES:SE:LP:AF:SS:ID   0.000363956:0.0022611:0.0594228:0.0569136:116746:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122693 ES:SE:LP:AF:SS:ID   0.000177284:0.00154145:0.0417052:0.122693:116746:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122272 ES:SE:LP:AF:SS:ID   -5.55954e-05:0.00164332:0.0118818:0.122272:116746:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121949 ES:SE:LP:AF:SS:ID   0.000178569:0.00154226:0.0419983:0.121949:116746:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00584104   ES:SE:LP:AF:SS:ID   -0.00364525:0.00705369:0.218025:0.00584104:116746:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00183233   ES:SE:LP:AF:SS:ID   -0.00776669:0.0135257:0.247321:0.00183233:116746:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868979 ES:SE:LP:AF:SS:ID   -0.00052759:0.00151972:0.137588:0.868979:116746:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123706 ES:SE:LP:AF:SS:ID   9.6458e-05:0.00150574:0.0227695:0.123706:116746:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143383 ES:SE:LP:AF:SS:ID   0.000342257:0.00148916:0.0871288:0.143383:116746:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123828 ES:SE:LP:AF:SS:ID   0.000113528:0.00150365:0.0269572:0.123828:116746:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869732 ES:SE:LP:AF:SS:ID   -0.000530241:0.00146413:0.144337:0.869732:116746:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874543 ES:SE:LP:AF:SS:ID   -0.0004526:0.00148886:0.118538:0.874543:116746:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129734 ES:SE:LP:AF:SS:ID   0.000567688:0.00146822:0.155514:0.129734:116746:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365537    ES:SE:LP:AF:SS:ID   -0.000548733:0.00266571:0.0773212:0.0365537:116746:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869323 ES:SE:LP:AF:SS:ID   -0.000570893:0.00146273:0.157191:0.869323:116746:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869395 ES:SE:LP:AF:SS:ID   -0.00061684:0.00146328:0.171755:0.869395:116746:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869322 ES:SE:LP:AF:SS:ID   -0.000576658:0.00146269:0.159016:0.869322:116746:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0051394    ES:SE:LP:AF:SS:ID   0.00288661:0.00746523:0.155524:0.0051394:116746:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00510827   ES:SE:LP:AF:SS:ID   0.00300083:0.00748166:0.162188:0.00510827:116746:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00570615   ES:SE:LP:AF:SS:ID   0.00495854:0.00719509:0.309161:0.00570615:116746:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869388 ES:SE:LP:AF:SS:ID   -0.000529303:0.00145996:0.144514:0.869388:116746:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127007 ES:SE:LP:AF:SS:ID   0.000502487:0.00149045:0.133114:0.127007:116746:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868903 ES:SE:LP:AF:SS:ID   -0.00051047:0.00145609:0.139119:0.868903:116746:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868299 ES:SE:LP:AF:SS:ID   -0.000486457:0.00145552:0.131815:0.868299:116746:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:SS:ID   -0.000521376:0.00145754:0.142329:0.869095:116746:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869101 ES:SE:LP:AF:SS:ID   -0.000523164:0.00145765:0.14287:0.869101:116746:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869104 ES:SE:LP:AF:SS:ID   -0.000522669:0.00145766:0.142717:0.869104:116746:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869542 ES:SE:LP:AF:SS:ID   -0.000590231:0.00146142:0.163483:0.869542:116746:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.099572 ES:SE:LP:AF:SS:ID   -0.000351021:0.00169955:0.077601:0.099572:116746:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00655951   ES:SE:LP:AF:SS:ID   0.00517051:0.00653836:0.367477:0.00655951:116746:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873634 ES:SE:LP:AF:SS:ID   -0.000476844:0.00148402:0.126116:0.873634:116746:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86289  ES:SE:LP:AF:SS:ID   -0.000422488:0.00145522:0.112626:0.86289:116746:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868299 ES:SE:LP:AF:SS:ID   -0.000249517:0.00146926:0.0629091:0.868299:116746:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865294 ES:SE:LP:AF:SS:ID   -0.000725476:0.00146949:0.206542:0.865294:116746:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997639    ES:SE:LP:AF:SS:ID   0.000255393:0.0017561:0.053366:0.0997639:116746:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870619 ES:SE:LP:AF:SS:ID   -0.000593085:0.00148702:0.161145:0.870619:116746:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870619 ES:SE:LP:AF:SS:ID   -0.000593058:0.00148702:0.161136:0.870619:116746:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870618 ES:SE:LP:AF:SS:ID   -0.000594476:0.00148702:0.161578:0.870618:116746:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870937 ES:SE:LP:AF:SS:ID   -0.000528249:0.00148764:0.141149:0.870937:116746:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126594 ES:SE:LP:AF:SS:ID   0.000511614:0.00148878:0.136015:0.126594:116746:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10633  ES:SE:LP:AF:SS:ID   0.000289699:0.00161842:0.0665446:0.10633:116746:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854304 ES:SE:LP:AF:SS:ID   -0.000863699:0.00145487:0.257478:0.854304:116746:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839004 ES:SE:LP:AF:SS:ID   -0.000511227:0.00144156:0.140943:0.839004:116746:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762921 ES:SE:LP:AF:SS:ID   -0.000289461:0.00115545:0.0957244:0.762921:116746:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105297 ES:SE:LP:AF:SS:ID   -8.60234e-06:0.00159846:0.00186888:0.105297:116746:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00769735   ES:SE:LP:AF:SS:ID   0.00163202:0.00591841:0.106384:0.00769735:116746:rs12562811