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-22640_1/ukb-d-22640_1.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-22640_1/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 16:36:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22640_1/ukb-d-22640_1.vcf.gz ...
Read summary statistics for 13531002 SNPs.
Dropped 12637 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, 1283494 SNPs remain.
After merging with regression SNP LD, 1283494 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.036 (0.0147)
Lambda GC: 1.004
Mean Chi^2: 0.9998
Intercept: 1.018 (0.0055)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 16:38:21 2019
Total time elapsed: 2.0m:3.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 0.9969,
    "mean_EFFECT": 0,
    "n": 25697,
    "n_snps": 13531002,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1249835,
    "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": 555297,
    "n_est": 25875.9475,
    "ratio_se_n": 1.0035,
    "mean_diff": 0,
    "ratio_diff": 66.5812,
    "sd_y_est1": 0.5012,
    "sd_y_est2": 0.5029,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283494,
    "ldsc_nsnp_merge_regression_ld": 1283494,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.018,
    "ldsc_intercept_se": 0.0055,
    "ldsc_lambda_gc": 1.004,
    "ldsc_mean_chisq": 0.9998,
    "ldsc_ratio": -90
}

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 13519028 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56985 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33309 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051469e+00 6.184688e+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 7.902182e+07 5.591791e+07 3.02000e+02 3.292010e+07 7.013031e+07 1.148571e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.070000e-05 2.551190e-02 -3.09447e-01 -6.742500e-03 -9.300000e-06 6.753200e-03 3.173160e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.838440e-02 1.770260e-02 3.54000e-03 5.283200e-03 9.680600e-03 2.633620e-02 1.025820e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.006147e-01 2.885027e-01 1.00000e-07 2.508511e-01 5.006555e-01 7.504763e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.006085e-01 2.885064e-01 1.00000e-07 2.508405e-01 5.006501e-01 7.504737e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.915411e-01 2.545891e-01 1.00000e-03 7.623900e-03 6.088630e-02 2.968220e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 555297 0.9589611 NA NA NA NA NA 1.968893e-01 2.472270e-01 0.00000e+00 5.790700e-03 8.506390e-02 3.091390e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.569700e+04 0.000000e+00 2.56970e+04 2.569700e+04 2.569700e+04 2.569700e+04 2.569700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0000909 0.0076909 0.9905710 0.9905705 0.1121430 0.1894970 25697
1 693731 rs12238997 A G 0.0036270 0.0073446 0.6214311 0.6214266 0.1165660 0.1417730 25697
1 707522 rs371890604 G C 0.0046121 0.0082682 0.5769763 0.5769708 0.0975760 0.1293930 25697
1 717587 rs144155419 G A -0.0081052 0.0194864 0.6774543 0.6774522 0.0160183 0.0045926 25697
1 723329 rs189787166 A T -0.0241019 0.0539967 0.6553420 0.6553381 0.0019672 0.0003994 25697
1 730087 rs148120343 T C 0.0035554 0.0100876 0.7245027 0.7245012 0.0579332 0.0127796 25697
1 731718 rs142557973 T C 0.0019573 0.0069605 0.7785545 0.7785535 0.1229090 0.1543530 25697
1 732032 rs61770163 A C 0.0043974 0.0074156 0.5531934 0.5531881 0.1227700 0.1555510 25697
1 734349 rs141242758 T C 0.0022936 0.0069646 0.7419113 0.7419090 0.1221900 0.1525560 25697
1 740284 rs61770167 C T 0.0341253 0.0330035 0.3011508 0.3011407 0.0054168 0.0023962 25697
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0098884 0.0077670 0.2029860 0.2029745 0.0569276 0.0309934 25697
23 154923374 rs111332691 T A -0.0012586 0.0086033 0.8836960 0.8836946 0.0445188 0.0116556 25697
23 154925045 rs509981 C T 0.0023828 0.0041699 0.5677054 0.5677001 0.2412010 0.3634440 25697
23 154925895 rs538470 C T 0.0028518 0.0042613 0.5033615 0.5033547 0.2377450 0.3634440 25697
23 154927581 rs644138 G A -0.0002499 0.0039070 0.9490109 0.9490101 0.2986200 0.4635760 25697
23 154929412 rs557132 C T 0.0023873 0.0041718 0.5671527 0.5671470 0.2409870 0.3568210 25697
23 154929637 rs35185538 CT C 0.0022003 0.0043469 0.6127340 0.6127293 0.2268160 0.3011920 25697
23 154929952 rs4012982 CAA C 0.0028672 0.0043914 0.5138117 0.5138059 0.2348550 0.3165560 25697
23 154930230 rs781880 A G 0.0027189 0.0041690 0.5143041 0.5142972 0.2415200 0.3618540 25697
23 154930487 rs781879 T A 0.0017086 0.0144671 0.9059860 0.9059848 0.0189835 0.1263580 25697

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112143 ES:SE:LP:AF:SS:ID   -9.08934e-05:0.00769086:0.00411439:0.112143:25697:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116566 ES:SE:LP:AF:SS:ID   0.00362696:0.00734456:0.206607:0.116566:25697:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097576 ES:SE:LP:AF:SS:ID   0.00461212:0.00826819:0.238842:0.097576:25697:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0160183    ES:SE:LP:AF:SS:ID   -0.00810522:0.0194864:0.16912:0.0160183:25697:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00196719   ES:SE:LP:AF:SS:ID   -0.0241019:0.0539967:0.183532:0.00196719:25697:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0579332    ES:SE:LP:AF:SS:ID   0.00355537:0.0100876:0.13996:0.0579332:25697:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122909 ES:SE:LP:AF:SS:ID   0.00195733:0.00696052:0.108711:0.122909:25697:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12277  ES:SE:LP:AF:SS:ID   0.00439738:0.00741561:0.257123:0.12277:25697:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12219  ES:SE:LP:AF:SS:ID   0.00229362:0.00696458:0.129648:0.12219:25697:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00541682   ES:SE:LP:AF:SS:ID   0.0341253:0.0330035:0.521216:0.00541682:25697:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00179627   ES:SE:LP:AF:SS:ID   -0.0434249:0.0616279:0.317813:0.00179627:25697:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867932 ES:SE:LP:AF:SS:ID   -0.00534357:0.0068366:0.36206:0.867932:25697:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0017537    ES:SE:LP:AF:SS:ID   -0.0379479:0.0571914:0.294992:0.0017537:25697:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12446  ES:SE:LP:AF:SS:ID   0.00821183:0.00678146:0.646016:0.12446:25697:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143673 ES:SE:LP:AF:SS:ID   0.00678298:0.00672308:0.504417:0.143673:25697:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124586 ES:SE:LP:AF:SS:ID   0.00810403:0.00677293:0.635449:0.124586:25697:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869298 ES:SE:LP:AF:SS:ID   -0.00478853:0.00660769:0.329152:0.869298:25697:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873888 ES:SE:LP:AF:SS:ID   -0.00757555:0.00670995:0.586855:0.873888:25697:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.130223 ES:SE:LP:AF:SS:ID   0.00436658:0.00662803:0.292408:0.130223:25697:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0356073    ES:SE:LP:AF:SS:ID   -0.014982:0.0121194:0.664751:0.0356073:25697:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86893  ES:SE:LP:AF:SS:ID   -0.00422522:0.0066029:0.282129:0.86893:25697:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869072 ES:SE:LP:AF:SS:ID   -0.00411613:0.00660668:0.27305:0.869072:25697:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.868931 ES:SE:LP:AF:SS:ID   -0.00422496:0.00660268:0.28212:0.868931:25697:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0049226    ES:SE:LP:AF:SS:ID   0.0186735:0.034591:0.229653:0.0049226:25697:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00489216   ES:SE:LP:AF:SS:ID   0.0197959:0.0346725:0.245616:0.00489216:25697:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00561735   ES:SE:LP:AF:SS:ID   -0.00725632:0.032389:0.0847421:0.00561735:25697:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868988 ES:SE:LP:AF:SS:ID   -0.00466453:0.00658971:0.319624:0.868988:25697:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127576 ES:SE:LP:AF:SS:ID   0.00541518:0.0067204:0.376363:0.127576:25697:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868487 ES:SE:LP:AF:SS:ID   -0.00482351:0.00657258:0.334395:0.868487:25697:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867984 ES:SE:LP:AF:SS:ID   -0.00406548:0.00657217:0.27068:0.867984:25697:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868672 ES:SE:LP:AF:SS:ID   -0.00480837:0.00657774:0.332751:0.868672:25697:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868677 ES:SE:LP:AF:SS:ID   -0.00480533:0.00657812:0.332462:0.868677:25697:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868677 ES:SE:LP:AF:SS:ID   -0.00479917:0.00657814:0.331928:0.868677:25697:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86918  ES:SE:LP:AF:SS:ID   -0.00481599:0.00659769:0.332148:0.86918:25697:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.09951  ES:SE:LP:AF:SS:ID   0.00949007:0.0076878:0.663434:0.09951:25697:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00646211   ES:SE:LP:AF:SS:ID   0.0153836:0.0294597:0.220735:0.00646211:25697:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873078 ES:SE:LP:AF:SS:ID   -0.00563997:0.00669009:0.398791:0.873078:25697:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862503 ES:SE:LP:AF:SS:ID   -0.0029007:0.00656422:0.181399:0.862503:25697:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867879 ES:SE:LP:AF:SS:ID   -0.00410562:0.00662787:0.271138:0.867879:25697:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86493  ES:SE:LP:AF:SS:ID   -0.00598041:0.00663512:0.434834:0.86493:25697:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994497    ES:SE:LP:AF:SS:ID   0.00864193:0.00794917:0.55755:0.0994497:25697:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870274 ES:SE:LP:AF:SS:ID   -0.00716969:0.00671073:0.544616:0.870274:25697:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870274 ES:SE:LP:AF:SS:ID   -0.0071704:0.00671073:0.544689:0.870274:25697:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870271 ES:SE:LP:AF:SS:ID   -0.0071713:0.00671075:0.544779:0.870271:25697:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870593 ES:SE:LP:AF:SS:ID   -0.00688441:0.00671215:0.515615:0.870593:25697:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12718  ES:SE:LP:AF:SS:ID   0.0053673:0.00671364:0.372603:0.12718:25697:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106621 ES:SE:LP:AF:SS:ID   0.00511986:0.00729825:0.316065:0.106621:25697:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.853855 ES:SE:LP:AF:SS:ID   -0.00281768:0.00654403:0.176016:0.853855:25697:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00184915   ES:SE:LP:AF:SS:ID   -0.0264633:0.05433:0.203285:0.00184915:25697:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838998 ES:SE:LP:AF:SS:ID   0.000338614:0.00648584:0.01847:0.838998:25697:rs376645387