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-30710_raw/ukb-d-30710_raw.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-30710_raw/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 14:55:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30710_raw/ukb-d-30710_raw.vcf.gz ...
Read summary statistics for 13586003 SNPs.
Dropped 12710 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0526 (0.0064)
Lambda GC: 1.2431
Mean Chi^2: 1.3914
Intercept: 1.0419 (0.0105)
Ratio: 0.107 (0.0268)
Analysis finished at Mon Nov 25 14:57:50 2019
Total time elapsed: 2.0m:21.86s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1559,
    "mean_EFFECT": 0.0003,
    "n": 343524,
    "n_snps": 13586003,
    "n_clumped_hits": 52,
    "n_p_sig": 9130,
    "n_mono": 0,
    "n_ns": 1251783,
    "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": 569171,
    "n_est": 344857.9633,
    "ratio_se_n": 1.0019,
    "mean_diff": -0.0002,
    "ratio_diff": 115.0737,
    "sd_y_est1": 4.3917,
    "sd_y_est2": 4.4002,
    "r2_sum1": 0.3958,
    "r2_sum2": 0.0205,
    "r2_sum3": 0.0204,
    "r2_sum4": 0.0203,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0526,
    "ldsc_observed_scale_h2_se": 0.0064,
    "ldsc_intercept_beta": 1.0419,
    "ldsc_intercept_se": 0.0105,
    "ldsc_lambda_gc": 1.2431,
    "ldsc_mean_chisq": 1.3914,
    "ldsc_ratio": 0.1071
}

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 TRUE
n_p_sig TRUE
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 13573957 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051260e+00 6.184973e+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 7.902562e+07 5.591505e+07 3.02000e+02 3.293113e+07 7.013954e+07 1.148598e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.673000e-04 6.312010e-02 -1.44080e+00 -1.799500e-02 -8.960000e-05 1.785500e-02 1.006000e+00 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.452270e-02 4.294730e-02 8.71130e-03 1.267600e-02 2.335900e-02 6.398100e-02 2.167900e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.762689e-01 2.959922e-01 0.00000e+00 2.139302e-01 4.683602e-01 7.329798e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.762684e-01 2.959925e-01 0.00000e+00 2.139310e-01 4.683599e-01 7.329811e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908097e-01 2.544045e-01 1.00000e-03 7.431400e-03 6.004100e-02 2.953200e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569171 0.9581061 NA NA NA NA NA 1.963392e-01 2.471026e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.435240e+05 0.000000e+00 3.43524e+05 3.435240e+05 3.435240e+05 3.435240e+05 3.435240e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.026820 0.018558 0.1483901 0.1484020 0.1105200 0.1894970 343524
1 693731 rs12238997 A G -0.012940 0.017527 0.4603498 0.4603385 0.1158100 0.1417730 343524
1 707522 rs371890604 G C -0.013553 0.019716 0.4918096 0.4918236 0.0972460 0.1293930 343524
1 717587 rs144155419 G A -0.019090 0.047049 0.6849297 0.6849284 0.0156700 0.0045926 343524
1 723329 rs189787166 A T -0.276000 0.138420 0.0461647 0.0461595 0.0017408 0.0003994 343524
1 730087 rs148120343 T C -0.048039 0.024429 0.0492425 0.0492439 0.0564200 0.0127796 343524
1 731718 rs142557973 T C -0.015293 0.016624 0.3576004 0.3576067 0.1217000 0.1543530 343524
1 732032 rs61770163 A C -0.013702 0.017739 0.4398697 0.4398643 0.1211100 0.1555510 343524
1 734349 rs141242758 T C -0.014609 0.016633 0.3797799 0.3797732 0.1209300 0.1525560 343524
1 740284 rs61770167 C T 0.206090 0.076252 0.0068759 0.0068769 0.0057617 0.0023962 343524
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0018397 0.0192130 0.9237199 0.9237168 0.056186 0.0309934 343524
23 154923374 rs111332691 T A -0.0128410 0.0210850 0.5425203 0.5425171 0.044872 0.0116556 343524
23 154925045 rs509981 C T 0.0112460 0.0101590 0.2682897 0.2682945 0.245620 0.3634440 343524
23 154925895 rs538470 C T 0.0119460 0.0103920 0.2503399 0.2503342 0.241950 0.3634440 343524
23 154927581 rs644138 G A 0.0094993 0.0095542 0.3201002 0.3200993 0.302190 0.4635760 343524
23 154929412 rs557132 C T 0.0114450 0.0101620 0.2600603 0.2600577 0.245480 0.3568210 343524
23 154929637 rs35185538 CT C 0.0126150 0.0106060 0.2342998 0.2342740 0.229730 0.3011920 343524
23 154929952 rs4012982 CAA C 0.0088412 0.0106870 0.4081004 0.4080753 0.239450 0.3165560 343524
23 154930230 rs781880 A G 0.0128730 0.0101600 0.2051601 0.2051454 0.245870 0.3618540 343524
23 154930487 rs781879 T A 0.0447070 0.0348330 0.1993201 0.1993286 0.019560 0.1263580 343524

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11052  ES:SE:LP:AF:SS:ID   -0.02682:0.018558:0.828595:0.11052:343524:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   -0.01294:0.017527:0.336912:0.11581:343524:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097246 ES:SE:LP:AF:SS:ID   -0.013553:0.019716:0.308203:0.097246:343524:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.01567  ES:SE:LP:AF:SS:ID   -0.01909:0.047049:0.164354:0.01567:343524:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017408    ES:SE:LP:AF:SS:ID   -0.276:0.13842:1.33569:0.0017408:343524:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.05642  ES:SE:LP:AF:SS:ID   -0.048039:0.024429:1.30766:0.05642:343524:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1217   ES:SE:LP:AF:SS:ID   -0.015293:0.016624:0.446602:0.1217:343524:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12111  ES:SE:LP:AF:SS:ID   -0.013702:0.017739:0.356676:0.12111:343524:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12093  ES:SE:LP:AF:SS:ID   -0.014609:0.016633:0.420468:0.12093:343524:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057617    ES:SE:LP:AF:SS:ID   0.20609:0.076252:2.16267:0.0057617:343524:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018616    ES:SE:LP:AF:SS:ID   0.0081827:0.14463:0.0200512:0.0018616:343524:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   0.016991:0.016399:0.522662:0.8698:343524:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015218    ES:SE:LP:AF:SS:ID   0.042062:0.1489:0.109261:0.0015218:343524:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12288  ES:SE:LP:AF:SS:ID   -0.017906:0.01624:0.568299:0.12288:343524:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1427   ES:SE:LP:AF:SS:ID   -0.017724:0.01605:0.569522:0.1427:343524:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   -0.018137:0.016217:0.579351:0.12299:343524:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87097  ES:SE:LP:AF:SS:ID   0.015706:0.015806:0.494348:0.87097:343524:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87553  ES:SE:LP:AF:SS:ID   0.014518:0.016066:0.436294:0.87553:343524:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12857  ES:SE:LP:AF:SS:ID   -0.015588:0.015845:0.487823:0.12857:343524:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036306 ES:SE:LP:AF:SS:ID   -0.0024163:0.028772:0.0300858:0.036306:343524:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.015073:0.015789:0.468841:0.87056:343524:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   0.014678:0.015797:0.452471:0.87066:343524:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.014922:0.015789:0.462672:0.87056:343524:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050488    ES:SE:LP:AF:SS:ID   -0.099316:0.080981:0.657479:0.0050488:343524:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050158    ES:SE:LP:AF:SS:ID   -0.10413:0.081196:0.699644:0.0050158:343524:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055461    ES:SE:LP:AF:SS:ID   0.098589:0.078804:0.675903:0.0055461:343524:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   0.015236:0.015761:0.476657:0.87064:343524:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   -0.016165:0.016081:0.501965:0.12592:343524:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   0.015056:0.015724:0.470711:0.87021:343524:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   0.014688:0.015709:0.45618:0.86949:343524:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   0.015219:0.015737:0.476917:0.87036:343524:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.015203:0.015738:0.476202:0.87037:343524:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   0.015256:0.015739:0.478378:0.87038:343524:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87082  ES:SE:LP:AF:SS:ID   0.015524:0.015778:0.487876:0.87082:343524:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098777 ES:SE:LP:AF:SS:ID   -0.01215:0.018339:0.294444:0.098777:343524:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064311    ES:SE:LP:AF:SS:ID   0.071966:0.071201:0.505651:0.0064311:343524:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87471  ES:SE:LP:AF:SS:ID   0.01437:0.016013:0.432386:0.87471:343524:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86411  ES:SE:LP:AF:SS:ID   0.015595:0.015705:0.493887:0.86411:343524:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.015615:0.015855:0.488531:0.8695:343524:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.015373:0.015858:0.478391:0.86644:343524:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098735 ES:SE:LP:AF:SS:ID   -0.022824:0.018984:0.639672:0.098735:343524:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.014459:0.01604:0.43492:0.87162:343524:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.014458:0.01604:0.434884:0.87162:343524:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.014463:0.01604:0.435038:0.87162:343524:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87199  ES:SE:LP:AF:SS:ID   0.013975:0.016049:0.415805:0.87199:343524:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12551  ES:SE:LP:AF:SS:ID   -0.014802:0.01606:0.447673:0.12551:343524:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   -0.012057:0.017488:0.309343:0.10539:343524:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85546  ES:SE:LP:AF:SS:ID   0.0083639:0.015699:0.226067:0.85546:343524:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016595    ES:SE:LP:AF:SS:ID   -0.25965:0.13877:1.21224:0.0016595:343524:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83824  ES:SE:LP:AF:SS:ID   -0.029715:0.015457:1.26322:0.83824:343524:rs376645387