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-30800_irnt/ukb-d-30800_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-30800_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 15:34:00 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30800_irnt/ukb-d-30800_irnt.vcf.gz ...
Read summary statistics for 13556362 SNPs.
Dropped 12672 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, 1283499 SNPs remain.
After merging with regression SNP LD, 1283499 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0204 (0.0092)
Lambda GC: 1.0248
Mean Chi^2: 1.028
Intercept: 1.0058 (0.0068)
Ratio: 0.2069 (0.244)
Analysis finished at Mon Nov 25 15:36:22 2019
Total time elapsed: 2.0m:21.97s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0202,
    "mean_EFFECT": 0,
    "n": 54498,
    "n_snps": 13556362,
    "n_clumped_hits": 1,
    "n_p_sig": 11,
    "n_mono": 0,
    "n_ns": 1250750,
    "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": 561679,
    "n_est": 54527.1571,
    "ratio_se_n": 1.0003,
    "mean_diff": 9.5342e-06,
    "ratio_diff": 5.8105,
    "sd_y_est1": 0.8319,
    "sd_y_est2": 0.8321,
    "r2_sum1": 0.0005,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0007,
    "ldsc_nsnp_merge_refpanel_ld": 1283499,
    "ldsc_nsnp_merge_regression_ld": 1283499,
    "ldsc_observed_scale_h2_beta": 0.0204,
    "ldsc_observed_scale_h2_se": 0.0092,
    "ldsc_intercept_beta": 1.0058,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0248,
    "ldsc_mean_chisq": 1.028,
    "ldsc_ratio": 0.2071
}

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 13544354 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57020 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33317 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051387e+00 6.185053e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902496e+07 5.591648e+07 3.0200e+02 3.292666e+07 7.014060e+07 1.148561e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.910000e-05 2.919300e-02 -3.6099e-01 -7.779300e-03 2.690000e-05 7.887100e-03 3.738800e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.105990e-02 2.027870e-02 4.4684e-03 6.022500e-03 1.106800e-02 3.024300e-02 1.060200e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.970620e-01 2.894738e-01 0.0000e+00 2.457599e-01 4.957104e-01 7.480593e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.970590e-01 2.894756e-01 0.0000e+00 2.457514e-01 4.957024e-01 7.480632e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911939e-01 2.544914e-01 1.0000e-03 7.528800e-03 6.054400e-02 2.961100e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561679 0.9585671 NA NA NA NA NA 1.966247e-01 2.471618e-01 0.0000e+00 5.790700e-03 8.466450e-02 3.087060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.449800e+04 0.000000e+00 5.4498e+04 5.449800e+04 5.449800e+04 5.449800e+04 5.449800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0014976 0.0087987 0.8648500 0.8648474 0.1101600 0.1894970 54498
1 693731 rs12238997 A G 0.0007226 0.0083252 0.9308301 0.9308341 0.1153700 0.1417730 54498
1 707522 rs371890604 G C -0.0024317 0.0093668 0.7951700 0.7951659 0.0969370 0.1293930 54498
1 717587 rs144155419 G A 0.0192740 0.0222160 0.3856097 0.3856282 0.0158320 0.0045926 54498
1 723329 rs189787166 A T 0.0225140 0.0699130 0.7474308 0.7474309 0.0015382 0.0003994 54498
1 730087 rs148120343 T C 0.0005622 0.0116700 0.9615800 0.9615797 0.0560090 0.0127796 54498
1 731718 rs142557973 T C -0.0016100 0.0079000 0.8385200 0.8385118 0.1213900 0.1543530 54498
1 732032 rs61770163 A C -0.0024094 0.0084125 0.7745706 0.7745663 0.1210800 0.1555510 54498
1 734349 rs141242758 T C -0.0014724 0.0079036 0.8522200 0.8522135 0.1205700 0.1525560 54498
1 740284 rs61770167 C T -0.0167820 0.0361160 0.6421700 0.6421682 0.0057529 0.0023962 54498
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0010303 0.0098561 0.9167500 0.9167454 0.056393 0.0309934 54498
23 154923374 rs111332691 T A 0.0019718 0.0109170 0.8566600 0.8566679 0.044424 0.0116556 54498
23 154925045 rs509981 C T -0.0029432 0.0052060 0.5718406 0.5718373 0.246130 0.3634440 54498
23 154925895 rs538470 C T -0.0030733 0.0053262 0.5639297 0.5639290 0.242350 0.3634440 54498
23 154927581 rs644138 G A -0.0028664 0.0049047 0.5589398 0.5589384 0.302980 0.4635760 54498
23 154929412 rs557132 C T -0.0029687 0.0052075 0.5686198 0.5686223 0.245980 0.3568210 54498
23 154929637 rs35185538 CT C -0.0023457 0.0054456 0.6666594 0.6666491 0.229630 0.3011920 54498
23 154929952 rs4012982 CAA C -0.0010094 0.0054832 0.8539401 0.8539432 0.240120 0.3165560 54498
23 154930230 rs781880 A G -0.0030686 0.0052078 0.5557097 0.5557060 0.246320 0.3618540 54498
23 154930487 rs781879 T A -0.0061553 0.0174800 0.7247496 0.7247379 0.020255 0.1263580 54498

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11016  ES:SE:LP:AF:SS:ID   0.0014976:0.0087987:0.0630592:0.11016:54498:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11537  ES:SE:LP:AF:SS:ID   0.00072259:0.0083252:0.0311296:0.11537:54498:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.096937 ES:SE:LP:AF:SS:ID   -0.0024317:0.0093668:0.09954:0.096937:54498:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015832 ES:SE:LP:AF:SS:ID   0.019274:0.022216:0.413852:0.015832:54498:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0015382    ES:SE:LP:AF:SS:ID   0.022514:0.069913:0.126429:0.0015382:54498:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056009 ES:SE:LP:AF:SS:ID   0.00056216:0.01167:0.0170146:0.056009:54498:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12139  ES:SE:LP:AF:SS:ID   -0.00161:0.0079:0.0764866:0.12139:54498:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12108  ES:SE:LP:AF:SS:ID   -0.0024094:0.0084125:0.110939:0.12108:54498:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12057  ES:SE:LP:AF:SS:ID   -0.0014724:0.0079036:0.0694483:0.12057:54498:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057529    ES:SE:LP:AF:SS:ID   -0.016782:0.036116:0.19235:0.0057529:54498:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018829    ES:SE:LP:AF:SS:ID   -0.17498:0.068406:1.97757:0.0018829:54498:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   0.0038246:0.0077699:0.205819:0.8698:54498:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0016268    ES:SE:LP:AF:SS:ID   0.05008:0.068323:0.333885:0.0016268:54498:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12282  ES:SE:LP:AF:SS:ID   -0.0032638:0.0076984:0.172889:0.12282:54498:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14265  ES:SE:LP:AF:SS:ID   -1.9021e-05:0.0076:0.000869459:0.14265:54498:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12296  ES:SE:LP:AF:SS:ID   -0.0034944:0.0076867:0.187488:0.12296:54498:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87105  ES:SE:LP:AF:SS:ID   0.0030308:0.0075004:0.163581:0.87105:54498:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87549  ES:SE:LP:AF:SS:ID   0.0043786:0.007621:0.247491:0.87549:54498:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12853  ES:SE:LP:AF:SS:ID   -0.0016868:0.007514:0.0849275:0.12853:54498:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036001 ES:SE:LP:AF:SS:ID   -0.020244:0.01371:0.854524:0.036001:54498:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   0.0032121:0.0074922:0.175146:0.87066:54498:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87074  ES:SE:LP:AF:SS:ID   0.0032768:0.0074952:0.179155:0.87074:54498:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   0.0031625:0.0074919:0.172024:0.87066:54498:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0052711    ES:SE:LP:AF:SS:ID   0.008294:0.037714:0.0830568:0.0052711:54498:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0052421    ES:SE:LP:AF:SS:ID   0.0083407:0.037802:0.0833513:0.0052421:54498:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0057236    ES:SE:LP:AF:SS:ID   0.0020936:0.036924:0.0200967:0.0057236:54498:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87078  ES:SE:LP:AF:SS:ID   0.0023113:0.0074786:0.120744:0.87078:54498:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12591  ES:SE:LP:AF:SS:ID   -0.0014253:0.0076237:0.0697134:0.12591:54498:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87034  ES:SE:LP:AF:SS:ID   0.0019533:0.0074613:0.100464:0.87034:54498:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86967  ES:SE:LP:AF:SS:ID   0.0024576:0.007455:0.129795:0.86967:54498:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87051  ES:SE:LP:AF:SS:ID   0.0022687:0.0074685:0.118444:0.87051:54498:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87052  ES:SE:LP:AF:SS:ID   0.0022655:0.0074691:0.118245:0.87052:54498:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87052  ES:SE:LP:AF:SS:ID   0.0022791:0.0074691:0.119038:0.87052:54498:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87101  ES:SE:LP:AF:SS:ID   0.0024406:0.007488:0.128147:0.87101:54498:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098766 ES:SE:LP:AF:SS:ID   -0.0045695:0.0086836:0.222762:0.098766:54498:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0066973    ES:SE:LP:AF:SS:ID   -0.0077592:0.033044:0.0891836:0.0066973:54498:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87471  ES:SE:LP:AF:SS:ID   0.0031685:0.007596:0.169674:0.87471:54498:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.8644   ES:SE:LP:AF:SS:ID   0.0043866:0.0074549:0.25473:0.8644:54498:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8696   ES:SE:LP:AF:SS:ID   0.002157:0.0075242:0.111051:0.8696:54498:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86638  ES:SE:LP:AF:SS:ID   0.0018973:0.0075201:0.0964705:0.86638:54498:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0988   ES:SE:LP:AF:SS:ID   -0.00066222:0.0090014:0.0262489:0.0988:54498:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.0024797:0.0076098:0.128112:0.87161:54498:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.0024799:0.0076098:0.128124:0.8716:54498:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.0024798:0.0076098:0.128118:0.8716:54498:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87197  ES:SE:LP:AF:SS:ID   0.002168:0.0076137:0.110233:0.87197:54498:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12552  ES:SE:LP:AF:SS:ID   -0.0014508:0.0076147:0.0711435:0.12552:54498:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10496  ES:SE:LP:AF:SS:ID   -0.0041655:0.0082923:0.210821:0.10496:54498:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85549  ES:SE:LP:AF:SS:ID   0.0031949:0.0074481:0.17525:0.85549:54498:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0014459    ES:SE:LP:AF:SS:ID   0.037404:0.070813:0.223764:0.0014459:54498:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83798  ES:SE:LP:AF:SS:ID   -0.014938:0.0073253:1.3827:0.83798:54498:rs376645387