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-20079_2/ukb-d-20079_2.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-20079_2/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 16:42:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20079_2/ukb-d-20079_2.vcf.gz ...
Read summary statistics for 12940819 SNPs.
Dropped 11791 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, 1283373 SNPs remain.
After merging with regression SNP LD, 1283373 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0067 (0.008)
Lambda GC: 0.9925
Mean Chi^2: 0.9956
Intercept: 1.0025 (0.0053)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 16:45:25 2019
Total time elapsed: 2.0m:38.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9511,
    "inflation_factor": 0.9966,
    "mean_EFFECT": 0,
    "n": 51427,
    "n_snps": 12940819,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1226552,
    "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": 418286,
    "n_est": 51637.6638,
    "ratio_se_n": 1.002,
    "mean_diff": 0,
    "ratio_diff": 21.5331,
    "sd_y_est1": 0.3687,
    "sd_y_est2": 0.3695,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0006,
    "r2_sum3": 0.0006,
    "r2_sum4": 0.0006,
    "ldsc_nsnp_merge_refpanel_ld": 1283373,
    "ldsc_nsnp_merge_regression_ld": 1283373,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0025,
    "ldsc_intercept_se": 0.0053,
    "ldsc_lambda_gc": 0.9925,
    "ldsc_mean_chisq": 0.9956,
    "ldsc_ratio": -0.5682
}

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 1.000000 3 94 0 12929679 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 55687 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 32916 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.058834e+00 6.185694e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.897622e+07 5.594088e+07 3.02000e+02 3.283362e+07 7.004708e+07 1.148231e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 2.870000e-05 1.143800e-02 -1.33177e-01 -3.338800e-03 -2.370000e-05 3.309800e-03 1.505880e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 8.434300e-03 7.691100e-03 1.89300e-03 2.705300e-03 4.680900e-03 1.194730e-02 4.270780e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 5.005841e-01 2.888174e-01 0.00000e+00 2.503842e-01 5.007304e-01 7.509050e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 5.005810e-01 2.888192e-01 0.00000e+00 2.503787e-01 5.007280e-01 7.509034e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 1.998285e-01 2.565186e-01 1.50860e-03 9.965600e-03 7.183000e-02 3.131860e-01 9.984910e-01 ▇▂▁▁▁
numeric AF_reference 418286 0.967677 NA NA NA NA NA 2.033018e-01 2.486010e-01 0.00000e+00 7.388200e-03 9.404950e-02 3.210860e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 5.142700e+04 0.000000e+00 5.14270e+04 5.142700e+04 5.142700e+04 5.142700e+04 5.142700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0007923 0.0040031 0.8431070 0.8431058 0.1121000 0.1894970 51427
1 693731 rs12238997 A G 0.0004897 0.0038041 0.8975790 0.8975789 0.1168090 0.1417730 51427
1 707522 rs371890604 G C -0.0033433 0.0042665 0.4332714 0.4332676 0.0982930 0.1293930 51427
1 717587 rs144155419 G A 0.0127806 0.0103143 0.2153069 0.2153031 0.0154808 0.0045926 51427
1 723329 rs189787166 A T 0.0049874 0.0293150 0.8649070 0.8649060 0.0017973 0.0003994 51427
1 730087 rs148120343 T C -0.0025242 0.0052976 0.6337325 0.6337306 0.0570822 0.0127796 51427
1 731718 rs142557973 T C 0.0003448 0.0036150 0.9240160 0.9240154 0.1225210 0.1543530 51427
1 732032 rs61770163 A C -0.0017385 0.0038535 0.6518805 0.6518777 0.1216510 0.1555510 51427
1 734349 rs141242758 T C 0.0004252 0.0036169 0.9064240 0.9064240 0.1217650 0.1525560 51427
1 740284 rs61770167 C T -0.0045197 0.0158068 0.7749292 0.7749278 0.0062329 0.0023962 51427
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0029977 0.0042529 0.4809002 0.4808972 0.0542488 0.0309934 51427
23 154923374 rs111332691 T A 0.0072875 0.0046068 0.1136821 0.1136756 0.0445389 0.0116556 51427
23 154925045 rs509981 C T -0.0011333 0.0022147 0.6088412 0.6088394 0.2434190 0.3634440 51427
23 154925895 rs538470 C T -0.0018988 0.0022623 0.4013026 0.4012994 0.2401390 0.3634440 51427
23 154927581 rs644138 G A -0.0018381 0.0020832 0.3775852 0.3775788 0.2981050 0.4635760 51427
23 154929412 rs557132 C T -0.0011637 0.0022155 0.5994031 0.5994018 0.2432580 0.3568210 51427
23 154929637 rs35185538 CT C -0.0012042 0.0023084 0.6019051 0.6019012 0.2278210 0.3011920 51427
23 154929952 rs4012982 CAA C -0.0020280 0.0023310 0.3842749 0.3842715 0.2374290 0.3165560 51427
23 154930230 rs781880 A G -0.0013958 0.0022145 0.5284854 0.5284834 0.2438260 0.3618540 51427
23 154930487 rs781879 T A 0.0011721 0.0077005 0.8790191 0.8790190 0.0189843 0.1263580 51427

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.1121   ES:SE:LP:AF:SS:ID   -0.000792301:0.00400309:0.0741173:0.1121:51427:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116809 ES:SE:LP:AF:SS:ID   0.000489664:0.00380409:0.0469273:0.116809:51427:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098293 ES:SE:LP:AF:SS:ID   -0.00334329:0.00426651:0.36324:0.098293:51427:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154808    ES:SE:LP:AF:SS:ID   0.0127806:0.0103143:0.666942:0.0154808:51427:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00179726   ES:SE:LP:AF:SS:ID   0.00498743:0.029315:0.0630306:0.00179726:51427:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570822    ES:SE:LP:AF:SS:ID   -0.0025242:0.00529757:0.198094:0.0570822:51427:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122521 ES:SE:LP:AF:SS:ID   0.000344783:0.00361495:0.0343205:0.122521:51427:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121651 ES:SE:LP:AF:SS:ID   -0.00173854:0.00385353:0.185832:0.121651:51427:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121765 ES:SE:LP:AF:SS:ID   0.000425169:0.00361691:0.0426686:0.121765:51427:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0062329    ES:SE:LP:AF:SS:ID   -0.00451972:0.0158068:0.110738:0.0062329:51427:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00176649   ES:SE:LP:AF:SS:ID   -0.0106545:0.0328465:0.12746:0.00176649:51427:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868613 ES:SE:LP:AF:SS:ID   0.00146854:0.00356052:0.167483:0.868613:51427:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00158492   ES:SE:LP:AF:SS:ID   -0.0298128:0.0319473:0.45503:0.00158492:51427:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123957 ES:SE:LP:AF:SS:ID   -0.000404603:0.0035272:0.0415909:0.123957:51427:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143385 ES:SE:LP:AF:SS:ID   0.000230646:0.00349952:0.0234432:0.143385:51427:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124126 ES:SE:LP:AF:SS:ID   -0.00019844:0.00352134:0.0199693:0.124126:51427:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869933 ES:SE:LP:AF:SS:ID   -6.01579e-05:0.00343188:0.00611648:0.869933:51427:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874426 ES:SE:LP:AF:SS:ID   -0.000240542:0.00348644:0.0245705:0.874426:51427:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129659 ES:SE:LP:AF:SS:ID   0.000520186:0.00344034:0.0556077:0.129659:51427:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0369164    ES:SE:LP:AF:SS:ID   -0.00779056:0.00619641:0.680557:0.0369164:51427:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869554 ES:SE:LP:AF:SS:ID   -0.000365982:0.00342868:0.0385818:0.869554:51427:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869648 ES:SE:LP:AF:SS:ID   -0.000399119:0.00343046:0.0422113:0.869648:51427:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   -0.000398262:0.00342867:0.0421395:0.86957:51427:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00531261   ES:SE:LP:AF:SS:ID   0.00769822:0.0171846:0.184306:0.00531261:51427:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00527727   ES:SE:LP:AF:SS:ID   0.00806317:0.0172298:0.193955:0.00527727:51427:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0057746    ES:SE:LP:AF:SS:ID   -0.0337763:0.0168038:1.3523:0.0057746:51427:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869706 ES:SE:LP:AF:SS:ID   -1.26718e-05:0.0034235:0.00128437:0.869706:51427:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12702  ES:SE:LP:AF:SS:ID   -0.00017286:0.00349159:0.0174958:0.12702:51427:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   0.000369941:0.0034145:0.0391854:0.869213:51427:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868449 ES:SE:LP:AF:SS:ID   -0.000259458:0.0034112:0.0271629:0.868449:51427:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   0.000174431:0.00341827:0.0180442:0.869419:51427:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869426 ES:SE:LP:AF:SS:ID   0.000179594:0.00341849:0.0185883:0.869426:51427:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   0.000165535:0.00341865:0.0171045:0.869437:51427:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869848 ES:SE:LP:AF:SS:ID   7.58287e-05:0.00342663:0.00773596:0.869848:51427:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0999077    ES:SE:LP:AF:SS:ID   -0.00368769:0.00397369:0.451736:0.0999077:51427:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00659027   ES:SE:LP:AF:SS:ID   -0.0405338:0.0152622:2.10161:0.00659027:51427:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87358  ES:SE:LP:AF:SS:ID   -0.00015797:0.00347613:0.0160343:0.87358:51427:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86295  ES:SE:LP:AF:SS:ID   0.000509682:0.00341027:0.054928:0.86295:51427:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868667 ES:SE:LP:AF:SS:ID   2.80901e-05:0.00344372:0.00283563:0.868667:51427:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.8652   ES:SE:LP:AF:SS:ID   7.68188e-05:0.0034422:0.00780228:0.8652:51427:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0992889    ES:SE:LP:AF:SS:ID   0.000373239:0.00413122:0.0324459:0.0992889:51427:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   -0.000289284:0.00348089:0.0297615:0.870459:51427:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   -0.00028888:0.00348089:0.0297182:0.870459:51427:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870456 ES:SE:LP:AF:SS:ID   -0.000287762:0.0034809:0.0295997:0.870456:51427:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870829 ES:SE:LP:AF:SS:ID   -0.00040954:0.00348288:0.042682:0.870829:51427:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126636 ES:SE:LP:AF:SS:ID   0.000319798:0.00348677:0.0329563:0.126636:51427:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106247 ES:SE:LP:AF:SS:ID   -0.00320642:0.00379712:0.399648:0.106247:51427:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854084 ES:SE:LP:AF:SS:ID   -0.000404057:0.00340992:0.0430271:0.854084:51427:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00168817   ES:SE:LP:AF:SS:ID   0.0126387:0.0295735:0.174499:0.00168817:51427:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836377 ES:SE:LP:AF:SS:ID   -0.0031223:0.00333943:0.456178:0.836377:51427:rs376645387