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-30897_irnt/ukb-d-30897_irnt.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-30897_irnt/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 14:53:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30897_irnt/ukb-d-30897_irnt.vcf.gz ...
Read summary statistics for 13585995 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: 0.0021 (0.0014)
Lambda GC: 1.075
Mean Chi^2: 1.077
Intercept: 1.0627 (0.0067)
Ratio: 0.8146 (0.0867)
Analysis finished at Mon Nov 25 14:56:16 2019
Total time elapsed: 2.0m:17.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0726,
    "mean_EFFECT": 0,
    "n": 342418,
    "n_snps": 13585995,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "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": 569148,
    "n_est": 343745.3093,
    "ratio_se_n": 1.0019,
    "mean_diff": -6.1425e-07,
    "ratio_diff": 0.8503,
    "sd_y_est1": 0.9952,
    "sd_y_est2": 0.9971,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0021,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0627,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.075,
    "ldsc_mean_chisq": 1.077,
    "ldsc_ratio": 0.8143
}

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 1.0000000 3 94 0 13573949 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 9.051245e+00 6.184971e+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 7.902581e+07 5.591526e+07 3.02000e+02 3.293102e+07 7.013951e+07 1.148605e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.770000e-05 1.451450e-02 -1.90820e-01 -3.822800e-03 -9.700000e-06 3.838700e-03 1.891400e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.010560e-02 9.747900e-03 1.97710e-03 2.877200e-03 5.301900e-03 1.452300e-02 4.926500e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.888762e-01 2.913867e-01 0.00000e+00 2.339101e-01 4.848295e-01 7.412795e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.888757e-01 2.913869e-01 0.00000e+00 2.339119e-01 4.848252e-01 7.412758e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908101e-01 2.544046e-01 1.00000e-03 7.431500e-03 6.004100e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569148 0.9581077 NA NA NA NA NA 1.963392e-01 2.471028e-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 3.424180e+05 0.000000e+00 3.42418e+05 3.424180e+05 3.424180e+05 3.424180e+05 3.424180e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0025005 0.0042125 0.5527898 0.5527860 0.1105500 0.1894970 342418
1 693731 rs12238997 A G 0.0038511 0.0039784 0.3330397 0.3330433 0.1158300 0.1417730 342418
1 707522 rs371890604 G C 0.0043143 0.0044746 0.3349600 0.3349579 0.0972630 0.1293930 342418
1 717587 rs144155419 G A 0.0132900 0.0106880 0.2137002 0.2137018 0.0156470 0.0045926 342418
1 723329 rs189787166 A T -0.0368430 0.0314870 0.2419502 0.2419599 0.0017343 0.0003994 342418
1 730087 rs148120343 T C -0.0017739 0.0055436 0.7489693 0.7489754 0.0564530 0.0127796 342418
1 731718 rs142557973 T C 0.0042197 0.0037732 0.2634202 0.2634241 0.1217300 0.1543530 342418
1 732032 rs61770163 A C 0.0050167 0.0040265 0.2127899 0.2127935 0.1211100 0.1555510 342418
1 734349 rs141242758 T C 0.0038239 0.0037751 0.3111000 0.3110951 0.1209500 0.1525560 342418
1 740284 rs61770167 C T 0.0174930 0.0173160 0.3124000 0.3123891 0.0057562 0.0023962 342418
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0047703 0.0043591 0.2738098 0.2738097 0.056211 0.0309934 342418
23 154923374 rs111332691 T A 0.0044646 0.0047872 0.3510201 0.3510204 0.044859 0.0116556 342418
23 154925045 rs509981 C T 0.0010146 0.0023052 0.6598497 0.6598391 0.245660 0.3634440 342418
23 154925895 rs538470 C T 0.0004972 0.0023581 0.8330199 0.8330226 0.242000 0.3634440 342418
23 154927581 rs644138 G A -0.0003493 0.0021679 0.8720000 0.8719960 0.302260 0.4635760 342418
23 154929412 rs557132 C T 0.0009196 0.0023058 0.6900507 0.6900415 0.245520 0.3568210 342418
23 154929637 rs35185538 CT C 0.0009994 0.0024066 0.6779505 0.6779500 0.229770 0.3011920 342418
23 154929952 rs4012982 CAA C 0.0007156 0.0024251 0.7679395 0.7679417 0.239500 0.3165560 342418
23 154930230 rs781880 A G 0.0006235 0.0023055 0.7868102 0.7868116 0.245920 0.3618540 342418
23 154930487 rs781879 T A -0.0087989 0.0079109 0.2660302 0.2660306 0.019529 0.1263580 342418

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11055  ES:SE:LP:AF:SS:ID   0.0025005:0.0042125:0.25744:0.11055:342418:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11583  ES:SE:LP:AF:SS:ID   0.0038511:0.0039784:0.477504:0.11583:342418:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097263 ES:SE:LP:AF:SS:ID   0.0043143:0.0044746:0.475007:0.097263:342418:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015647 ES:SE:LP:AF:SS:ID   0.01329:0.010688:0.670195:0.015647:342418:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017343    ES:SE:LP:AF:SS:ID   -0.036843:0.031487:0.616274:0.0017343:342418:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056453 ES:SE:LP:AF:SS:ID   -0.0017739:0.0055436:0.125536:0.056453:342418:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12173  ES:SE:LP:AF:SS:ID   0.0042197:0.0037732:0.579351:0.12173:342418:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12111  ES:SE:LP:AF:SS:ID   0.0050167:0.0040265:0.672049:0.12111:342418:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12095  ES:SE:LP:AF:SS:ID   0.0038239:0.0037751:0.5071:0.12095:342418:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057562    ES:SE:LP:AF:SS:ID   0.017493:0.017316:0.505289:0.0057562:342418:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018597    ES:SE:LP:AF:SS:ID   -0.056446:0.03286:1.06633:0.0018597:342418:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86979  ES:SE:LP:AF:SS:ID   -0.0037171:0.0037222:0.4976:0.86979:342418:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015191    ES:SE:LP:AF:SS:ID   0.020954:0.033831:0.271103:0.0015191:342418:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12289  ES:SE:LP:AF:SS:ID   0.0034818:0.0036861:0.462345:0.12289:342418:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14271  ES:SE:LP:AF:SS:ID   0.0027058:0.0036431:0.339457:0.14271:342418:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123    ES:SE:LP:AF:SS:ID   0.0035748:0.003681:0.479556:0.123:342418:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87095  ES:SE:LP:AF:SS:ID   -0.0029498:0.0035874:0.386243:0.87095:342418:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87551  ES:SE:LP:AF:SS:ID   -0.0030115:0.0036465:0.388394:0.87551:342418:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12859  ES:SE:LP:AF:SS:ID   0.0034221:0.0035963:0.466851:0.12859:342418:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036339 ES:SE:LP:AF:SS:ID   0.0013565:0.0065275:0.0781211:0.036339:342418:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   -0.0028181:0.0035837:0.364868:0.87054:342418:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   -0.0027696:0.0035853:0.356715:0.87064:342418:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   -0.0028268:0.0035835:0.366309:0.87054:342418:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050456    ES:SE:LP:AF:SS:ID   -0.0051441:0.018384:0.108117:0.0050456:342418:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050124    ES:SE:LP:AF:SS:ID   -0.0046773:0.018434:0.0970729:0.0050124:342418:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055382    ES:SE:LP:AF:SS:ID   -0.0054948:0.0179:0.119838:0.0055382:342418:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87062  ES:SE:LP:AF:SS:ID   -0.0028954:0.0035773:0.378502:0.87062:342418:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12593  ES:SE:LP:AF:SS:ID   0.0035978:0.00365:0.489066:0.12593:342418:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87019  ES:SE:LP:AF:SS:ID   -0.0027464:0.0035688:0.355:0.87019:342418:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86947  ES:SE:LP:AF:SS:ID   -0.0028228:0.0035656:0.367999:0.86947:342418:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87034  ES:SE:LP:AF:SS:ID   -0.0028039:0.0035718:0.364064:0.87034:342418:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   -0.0028005:0.0035721:0.363472:0.87035:342418:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   -0.0028195:0.0035722:0.366592:0.87036:342418:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8708   ES:SE:LP:AF:SS:ID   -0.0027575:0.0035812:0.355266:0.8708:342418:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098824 ES:SE:LP:AF:SS:ID   0.0034824:0.0041616:0.394997:0.098824:342418:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.006419 ES:SE:LP:AF:SS:ID   -0.0025539:0.016177:0.0582104:0.006419:342418:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87469  ES:SE:LP:AF:SS:ID   -0.00333:0.0036344:0.444265:0.87469:342418:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86409  ES:SE:LP:AF:SS:ID   -0.0028087:0.0035648:0.365775:0.86409:342418:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   -0.0028211:0.0035987:0.363432:0.86948:342418:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86642  ES:SE:LP:AF:SS:ID   -0.0036105:0.0035995:0.500547:0.86642:342418:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098747 ES:SE:LP:AF:SS:ID   0.0049202:0.0043089:0.596005:0.098747:342418:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   -0.0032485:0.0036407:0.429189:0.87161:342418:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   -0.0032486:0.0036407:0.429189:0.87161:342418:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   -0.003238:0.0036407:0.427361:0.87161:342418:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87198  ES:SE:LP:AF:SS:ID   -0.0032573:0.0036427:0.430369:0.87198:342418:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12552  ES:SE:LP:AF:SS:ID   0.0037111:0.0036453:0.51052:0.12552:342418:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10543  ES:SE:LP:AF:SS:ID   0.0026693:0.0039688:0.299963:0.10543:342418:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85543  ES:SE:LP:AF:SS:ID   -0.0020181:0.0035631:0.243257:0.85543:342418:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.001653 ES:SE:LP:AF:SS:ID   -0.047164:0.031566:0.869216:0.001653:342418:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83831  ES:SE:LP:AF:SS:ID   -0.0036806:0.0035092:0.531284:0.83831:342418:rs376645387