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-4294_0/ukb-d-4294_0.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-4294_0/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 16:56:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4294_0/ukb-d-4294_0.vcf.gz ...
Read summary statistics for 11888015 SNPs.
Dropped 10304 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, 1282949 SNPs remain.
After merging with regression SNP LD, 1282949 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0204 (0.004)
Lambda GC: 1.0466
Mean Chi^2: 1.0502
Intercept: 1.0019 (0.0065)
Ratio: 0.0387 (0.1302)
Analysis finished at Mon Nov 25 16:58:46 2019
Total time elapsed: 1.0m:55.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1.0385,
    "mean_EFFECT": 8.1571e-06,
    "n": 119729,
    "n_snps": 11888015,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1179439,
    "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": 272872,
    "n_est": 120018.612,
    "ratio_se_n": 1.0012,
    "mean_diff": 0,
    "ratio_diff": 20.705,
    "sd_y_est1": 0.1916,
    "sd_y_est2": 0.1918,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282949,
    "ldsc_nsnp_merge_regression_ld": 1282949,
    "ldsc_observed_scale_h2_beta": 0.0204,
    "ldsc_observed_scale_h2_se": 0.004,
    "ldsc_intercept_beta": 1.0019,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0466,
    "ldsc_mean_chisq": 1.0502,
    "ldsc_ratio": 0.0378
}

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 11878329 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 53135 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 32061 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.070054e+00 6.184413e+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 7.888406e+07 5.598010e+07 3.02000e+02 3.268693e+07 6.991469e+07 1.147452e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 8.200000e-06 3.012100e-03 -3.07833e-02 -1.054800e-03 -7.500000e-06 1.040200e-03 3.865170e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.314200e-03 1.887500e-03 6.43400e-04 8.979000e-04 1.411000e-03 3.181600e-03 1.157860e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.940185e-01 2.897600e-01 1.00000e-07 2.423511e-01 4.918651e-01 7.446017e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.940171e-01 2.897608e-01 1.00000e-07 2.423487e-01 4.918636e-01 7.446012e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.166146e-01 2.597048e-01 2.72870e-03 1.618240e-02 9.521750e-02 3.448070e-01 9.972710e-01 ▇▂▁▁▁
numeric AF_reference 272872 0.9770465 NA NA NA NA NA 2.178043e-01 2.511407e-01 0.00000e+00 1.297920e-02 1.146170e-01 3.464460e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.197290e+05 0.000000e+00 1.19729e+05 1.197290e+05 1.197290e+05 1.197290e+05 1.197290e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0029774 0.0013703 0.0297955 0.0297935 0.1114740 0.1894970 119729
1 693731 rs12238997 A G -0.0028210 0.0012963 0.0295488 0.0295474 0.1167380 0.1417730 119729
1 707522 rs371890604 G C -0.0033235 0.0014549 0.0223522 0.0223506 0.0981122 0.1293930 119729
1 717587 rs144155419 G A -0.0026100 0.0034915 0.4547451 0.4547421 0.0156883 0.0045926 119729
1 730087 rs148120343 T C -0.0021430 0.0018087 0.2361033 0.2360998 0.0567404 0.0127796 119729
1 731718 rs142557973 T C -0.0025592 0.0012306 0.0375604 0.0375583 0.1225600 0.1543530 119729
1 732032 rs61770163 A C -0.0029638 0.0013113 0.0238133 0.0238113 0.1220990 0.1555510 119729
1 734349 rs141242758 T C -0.0025088 0.0012314 0.0416188 0.0416170 0.1217760 0.1525560 119729
1 740284 rs61770167 C T 0.0023115 0.0055055 0.6745933 0.6745925 0.0060166 0.0023962 119729
1 749963 rs529266287 T TAA 0.0031373 0.0012138 0.0097472 0.0097458 0.8688930 0.7641770 119729
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0007332 0.0014349 0.6093825 0.6093807 0.0549736 0.0309934 119729
23 154923374 rs111332691 T A 0.0007905 0.0015660 0.6137323 0.6137325 0.0442291 0.0116556 119729
23 154925045 rs509981 C T 0.0009262 0.0007525 0.2183771 0.2183744 0.2439350 0.3634440 119729
23 154925895 rs538470 C T 0.0009048 0.0007694 0.2395918 0.2395892 0.2404170 0.3634440 119729
23 154927581 rs644138 G A 0.0009858 0.0007077 0.1636361 0.1636336 0.2993150 0.4635760 119729
23 154929412 rs557132 C T 0.0008762 0.0007527 0.2444190 0.2444169 0.2437600 0.3568210 119729
23 154929637 rs35185538 CT C 0.0008856 0.0007852 0.2593510 0.2593486 0.2277830 0.3011920 119729
23 154929952 rs4012982 CAA C 0.0007628 0.0007921 0.3355637 0.3355621 0.2378170 0.3165560 119729
23 154930230 rs781880 A G 0.0008751 0.0007526 0.2449041 0.2449017 0.2442410 0.3618540 119729
23 154930487 rs781879 T A 0.0021632 0.0026192 0.4088481 0.4088462 0.0190090 0.1263580 119729

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111474 ES:SE:LP:AF:SS:ID   -0.0029774:0.00137029:1.52585:0.111474:119729:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116738 ES:SE:LP:AF:SS:ID   -0.00282095:0.00129633:1.52946:0.116738:119729:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981122    ES:SE:LP:AF:SS:ID   -0.00332351:0.0014549:1.65068:0.0981122:119729:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156883    ES:SE:LP:AF:SS:ID   -0.00261004:0.00349154:0.342232:0.0156883:119729:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0567404    ES:SE:LP:AF:SS:ID   -0.00214298:0.00180874:0.626898:0.0567404:119729:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12256  ES:SE:LP:AF:SS:ID   -0.00255925:0.00123062:1.42527:0.12256:119729:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122099 ES:SE:LP:AF:SS:ID   -0.00296377:0.00131131:1.62318:0.122099:119729:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121776 ES:SE:LP:AF:SS:ID   -0.00250885:0.00123144:1.38071:0.121776:119729:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00601661   ES:SE:LP:AF:SS:ID   0.00231152:0.00550554:0.170958:0.00601661:119729:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.868893 ES:SE:LP:AF:SS:ID   0.00313728:0.00121378:2.01112:0.868893:119729:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123687 ES:SE:LP:AF:SS:ID   -0.00326774:0.00120244:2.18197:0.123687:119729:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143308 ES:SE:LP:AF:SS:ID   -0.00296573:0.00119077:1.89434:0.143308:119729:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123805 ES:SE:LP:AF:SS:ID   -0.00327577:0.0012007:2.19594:0.123805:119729:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870077 ES:SE:LP:AF:SS:ID   0.00300981:0.00116953:1.99706:0.870077:119729:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874766 ES:SE:LP:AF:SS:ID   0.00329067:0.00118922:2.24742:0.874766:119729:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129502 ES:SE:LP:AF:SS:ID   -0.00290961:0.00117205:1.88446:0.129502:119729:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0367288    ES:SE:LP:AF:SS:ID   0.000873412:0.00211562:0.167666:0.0367288:119729:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869686 ES:SE:LP:AF:SS:ID   0.00295357:0.00116834:1.94034:0.869686:119729:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869807 ES:SE:LP:AF:SS:ID   0.00294936:0.00116898:1.9342:0.869807:119729:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869677 ES:SE:LP:AF:SS:ID   0.00295778:0.00116827:1.94499:0.869677:119729:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00508457   ES:SE:LP:AF:SS:ID   -0.00949939:0.00599254:0.947218:0.00508457:119729:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050518    ES:SE:LP:AF:SS:ID   -0.00940506:0.00600821:0.929966:0.0050518:119729:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00552511   ES:SE:LP:AF:SS:ID   0.0062178:0.00582865:0.543513:0.00552511:119729:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869811 ES:SE:LP:AF:SS:ID   0.00303479:0.00116639:2.03278:0.869811:119729:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126782 ES:SE:LP:AF:SS:ID   -0.00306678:0.00119014:2.0012:0.126782:119729:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869397 ES:SE:LP:AF:SS:ID   0.00304259:0.00116371:2.04887:0.869397:119729:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868601 ES:SE:LP:AF:SS:ID   0.00303252:0.00116229:2.04194:0.868601:119729:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869543 ES:SE:LP:AF:SS:ID   0.00304539:0.00116464:2.04929:0.869543:119729:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86955  ES:SE:LP:AF:SS:ID   0.0030453:0.00116472:2.04896:0.86955:119729:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869558 ES:SE:LP:AF:SS:ID   0.00304384:0.00116476:2.04726:0.869558:119729:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869982 ES:SE:LP:AF:SS:ID   0.00301147:0.00116772:2.00384:0.869982:119729:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996592    ES:SE:LP:AF:SS:ID   -0.00307794:0.0013544:1.63723:0.0996592:119729:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00632851   ES:SE:LP:AF:SS:ID   0.00407602:0.00529338:0.355277:0.00632851:119729:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873917 ES:SE:LP:AF:SS:ID   0.0032327:0.00118551:2.19415:0.873917:119729:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863265 ES:SE:LP:AF:SS:ID   0.00267933:0.00116247:1.67414:0.863265:119729:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868699 ES:SE:LP:AF:SS:ID   0.00301745:0.00117362:1.99397:0.868699:119729:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86547  ES:SE:LP:AF:SS:ID   0.00305974:0.0011736:2.03947:0.86547:119729:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993084    ES:SE:LP:AF:SS:ID   -0.00430078:0.00140719:2.64947:0.0993084:119729:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870718 ES:SE:LP:AF:SS:ID   0.00294104:0.00118714:1.87827:0.870718:119729:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870718 ES:SE:LP:AF:SS:ID   0.00294107:0.00118714:1.8783:0.870718:119729:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87072  ES:SE:LP:AF:SS:ID   0.00294066:0.0011872:1.87772:0.87072:119729:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871104 ES:SE:LP:AF:SS:ID   0.00305935:0.00118785:1.99957:0.871104:119729:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126358 ES:SE:LP:AF:SS:ID   -0.00314902:0.00118861:2.09333:0.126358:119729:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106134 ES:SE:LP:AF:SS:ID   -0.00269639:0.00129289:1.43155:0.106134:119729:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854643 ES:SE:LP:AF:SS:ID   0.00299399:0.00116246:1.9996:0.854643:119729:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837928 ES:SE:LP:AF:SS:ID   6.55339e-05:0.00114308:0.0203233:0.837928:119729:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762386 ES:SE:LP:AF:SS:ID   0.00162534:0.000919735:1.11238:0.762386:119729:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106123 ES:SE:LP:AF:SS:ID   0.000348264:0.00126414:0.106273:0.106123:119729:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00757064   ES:SE:LP:AF:SS:ID   -0.00176074:0.00476853:0.147551:0.00757064:119729:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129673 ES:SE:LP:AF:SS:ID   -0.00299954:0.00117185:1.9797:0.129673:119729:rs762168062