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-3160_irnt/ukb-d-3160_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-3160_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 16:35:42 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-3160_irnt/ukb-d-3160_irnt.vcf.gz ...
Read summary statistics for 13424768 SNPs.
Dropped 12490 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, 1283475 SNPs remain.
After merging with regression SNP LD, 1283475 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1377 (0.0933)
Lambda GC: 1.0227
Mean Chi^2: 1.0237
Intercept: 1.0095 (0.0063)
Ratio: 0.4012 (0.2647)
Analysis finished at Mon Nov 25 16:37:59 2019
Total time elapsed: 2.0m:16.51s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9517,
    "inflation_factor": 1.0096,
    "mean_EFFECT": 0.0001,
    "n": 5278,
    "n_snps": 13424768,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1245418,
    "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": 532485,
    "n_est": 5332.3051,
    "ratio_se_n": 1.0051,
    "mean_diff": 6.6686e-06,
    "ratio_diff": 1.1492,
    "sd_y_est1": 0.8978,
    "sd_y_est2": 0.9024,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283475,
    "ldsc_nsnp_merge_regression_ld": 1283475,
    "ldsc_observed_scale_h2_beta": 0.1377,
    "ldsc_observed_scale_h2_se": 0.0933,
    "ldsc_intercept_beta": 1.0095,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0227,
    "ldsc_mean_chisq": 1.0237,
    "ldsc_ratio": 0.4008
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 13412938 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56758 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33247 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.052048e+00 6.183781e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.901405e+07 5.592339e+07 302.0000000 3.290727e+07 7.011455e+07 1.148502e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.153000e-04 9.879560e-02 -1.1987100 -2.681490e-02 -1.385000e-04 2.661420e-02 1.355870e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.125600e-02 6.839700e-02 0.0140915 2.082150e-02 3.775770e-02 1.015860e-01 4.496000e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.983031e-01 2.891874e-01 0.0000001 2.469471e-01 4.979595e-01 7.489193e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.982727e-01 2.892056e-01 0.0000001 2.468948e-01 4.979299e-01 7.489063e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.929764e-01 2.549591e-01 0.0010001 7.987300e-03 6.280380e-02 2.997710e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 532485 0.9603356 NA NA NA NA NA 1.980186e-01 2.474861e-01 0.0000000 5.990400e-03 8.646170e-02 3.113020e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.278000e+03 0.000000e+00 5278.0000000 5.278000e+03 5.278000e+03 5.278000e+03 5.278000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0512682 0.0302023 0.0896623 0.0896034 0.1124790 0.1894970 5278
1 693731 rs12238997 A G 0.0260688 0.0283511 0.3578764 0.3578348 0.1198960 0.1417730 5278
1 707522 rs371890604 G C 0.0269717 0.0320433 0.3999779 0.3999410 0.1000350 0.1293930 5278
1 717587 rs144155419 G A 0.0274922 0.0765783 0.7196047 0.7195893 0.0161009 0.0045926 5278
1 723329 rs189787166 A T 0.1069650 0.2287600 0.6400988 0.6400806 0.0017197 0.0003994 5278
1 730087 rs148120343 T C -0.0062559 0.0396137 0.8745229 0.8745170 0.0580501 0.0127796 5278
1 731718 rs142557973 T C 0.0214172 0.0268836 0.4256827 0.4256461 0.1256070 0.1543530 5278
1 732032 rs61770163 A C 0.0260273 0.0287906 0.3660252 0.3659844 0.1244390 0.1555510 5278
1 734349 rs141242758 T C 0.0215529 0.0268920 0.4229013 0.4228646 0.1250260 0.1525560 5278
1 740284 rs61770167 C T -0.0246979 0.1316150 0.8511561 0.8511490 0.0054666 0.0023962 5278
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0518169 0.0317783 0.1030400 0.1029800 0.0558578 0.0309934 5278
23 154923374 rs111332691 T A 0.0492392 0.0354544 0.1649510 0.1648925 0.0429140 0.0116556 5278
23 154925045 rs509981 C T -0.0042855 0.0164462 0.7944279 0.7944179 0.2498910 0.3634440 5278
23 154925895 rs538470 C T -0.0054544 0.0168452 0.7461068 0.7460942 0.2450600 0.3634440 5278
23 154927581 rs644138 G A -0.0155408 0.0155360 0.3172072 0.3171610 0.3062680 0.4635760 5278
23 154929412 rs557132 C T -0.0042220 0.0164480 0.7974280 0.7974175 0.2498290 0.3568210 5278
23 154929637 rs35185538 CT C -0.0047464 0.0172642 0.7833827 0.7833721 0.2314410 0.3011920 5278
23 154929952 rs4012982 CAA C -0.0046960 0.0173345 0.7864751 0.7864647 0.2423710 0.3165560 5278
23 154930230 rs781880 A G -0.0033880 0.0164524 0.8368550 0.8368471 0.2500200 0.3618540 5278
23 154930487 rs781879 T A 0.0871401 0.0581363 0.1339609 0.1339014 0.0194280 0.1263580 5278

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112479 ES:SE:LP:AF:SS:ID   0.0512682:0.0302023:1.04739:0.112479:5278:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.119896 ES:SE:LP:AF:SS:ID   0.0260688:0.0283511:0.446267:0.119896:5278:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.100035 ES:SE:LP:AF:SS:ID   0.0269717:0.0320433:0.397964:0.100035:5278:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0161009    ES:SE:LP:AF:SS:ID   0.0274922:0.0765783:0.142906:0.0161009:5278:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00171968   ES:SE:LP:AF:SS:ID   0.106965:0.22876:0.193753:0.00171968:5278:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0580501    ES:SE:LP:AF:SS:ID   -0.00625594:0.0396137:0.0582288:0.0580501:5278:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.125607 ES:SE:LP:AF:SS:ID   0.0214172:0.0268836:0.370914:0.125607:5278:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124439 ES:SE:LP:AF:SS:ID   0.0260273:0.0287906:0.436489:0.124439:5278:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.125026 ES:SE:LP:AF:SS:ID   0.0215529:0.026892:0.373761:0.125026:5278:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00546664   ES:SE:LP:AF:SS:ID   -0.0246979:0.131615:0.0699908:0.00546664:5278:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00144143   ES:SE:LP:AF:SS:ID   0.0929193:0.259435:0.142524:0.00144143:5278:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867628 ES:SE:LP:AF:SS:ID   -0.0218745:0.0268034:0.382503:0.867628:5278:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00103983   ES:SE:LP:AF:SS:ID   0.42494:0.312056:0.761109:0.00103983:5278:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.125943 ES:SE:LP:AF:SS:ID   0.027653:0.0264462:0.529031:0.125943:5278:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14539  ES:SE:LP:AF:SS:ID   0.0234023:0.0262106:0.429486:0.14539:5278:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125965 ES:SE:LP:AF:SS:ID   0.0281742:0.026424:0.543079:0.125965:5278:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.86859  ES:SE:LP:AF:SS:ID   -0.0316899:0.0257938:0.658997:0.86859:5278:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872642 ES:SE:LP:AF:SS:ID   -0.0335579:0.0262316:0.697128:0.872642:5278:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131359 ES:SE:LP:AF:SS:ID   0.0308646:0.0258041:0.635063:0.131359:5278:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0385563    ES:SE:LP:AF:SS:ID   -0.0256255:0.046213:0.23713:0.0385563:5278:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868071 ES:SE:LP:AF:SS:ID   -0.0328107:0.0257742:0.692348:0.868071:5278:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868162 ES:SE:LP:AF:SS:ID   -0.0334051:0.0257801:0.709718:0.868162:5278:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86806  ES:SE:LP:AF:SS:ID   -0.0328263:0.0257731:0.692849:0.86806:5278:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0043774    ES:SE:LP:AF:SS:ID   0.22563:0.146481:0.908196:0.0043774:5278:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0043592    ES:SE:LP:AF:SS:ID   0.225409:0.146794:0.904102:0.0043592:5278:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0058987    ES:SE:LP:AF:SS:ID   -0.0357892:0.126244:0.109685:0.0058987:5278:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.868434 ES:SE:LP:AF:SS:ID   -0.0299703:0.0257376:0.612091:0.868434:5278:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128545 ES:SE:LP:AF:SS:ID   0.0302486:0.0262066:0.604752:0.128545:5278:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867753 ES:SE:LP:AF:SS:ID   -0.0309581:0.0256346:0.643538:0.867753:5278:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867244 ES:SE:LP:AF:SS:ID   -0.0332175:0.0256391:0.709571:0.867244:5278:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868122 ES:SE:LP:AF:SS:ID   -0.0300182:0.0256906:0.61497:0.868122:5278:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868127 ES:SE:LP:AF:SS:ID   -0.0300451:0.0256924:0.615666:0.868127:5278:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868169 ES:SE:LP:AF:SS:ID   -0.0296808:0.025697:0.605321:0.868169:5278:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868548 ES:SE:LP:AF:SS:ID   -0.0302162:0.0257604:0.618234:0.868548:5278:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.102256 ES:SE:LP:AF:SS:ID   0.0213637:0.0298411:0.324153:0.102256:5278:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00655254   ES:SE:LP:AF:SS:ID   -0.0592376:0.116135:0.214655:0.00655254:5278:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87259  ES:SE:LP:AF:SS:ID   -0.0300727:0.0261964:0.600269:0.87259:5278:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860862 ES:SE:LP:AF:SS:ID   -0.0296492:0.0256318:0.606542:0.860862:5278:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.867403 ES:SE:LP:AF:SS:ID   -0.0269114:0.0258956:0.524696:0.867403:5278:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864633 ES:SE:LP:AF:SS:ID   -0.0294324:0.0259413:0.590735:0.864633:5278:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0990842    ES:SE:LP:AF:SS:ID   0.0161417:0.0313745:0.216858:0.0990842:5278:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.869503 ES:SE:LP:AF:SS:ID   -0.0306917:0.026226:0.616289:0.869503:5278:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.869503 ES:SE:LP:AF:SS:ID   -0.0306917:0.026226:0.616289:0.869503:5278:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   -0.0306941:0.0262261:0.61635:0.8695:5278:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869768 ES:SE:LP:AF:SS:ID   -0.0301785:0.0262313:0.602062:0.869768:5278:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128053 ES:SE:LP:AF:SS:ID   0.0259693:0.0262031:0.492557:0.128053:5278:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.109356 ES:SE:LP:AF:SS:ID   0.0177265:0.0283091:0.274722:0.109356:5278:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852836 ES:SE:LP:AF:SS:ID   -0.0268207:0.0255568:0.531628:0.852836:5278:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00172897   ES:SE:LP:AF:SS:ID   0.151323:0.223077:0.303134:0.00172897:5278:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837416 ES:SE:LP:AF:SS:ID   0.0144555:0.0255454:0.242982:0.837416:5278:rs376645387