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-30220_irnt/ukb-d-30220_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-30220_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 14:54:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30220_irnt/ukb-d-30220_irnt.vcf.gz ...
Read summary statistics for 13586282 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: 0.0448 (0.0046)
Lambda GC: 1.1721
Mean Chi^2: 1.3641
Intercept: 1.0543 (0.0103)
Ratio: 0.149 (0.0282)
Analysis finished at Mon Nov 25 14:57:16 2019
Total time elapsed: 2.0m:22.65s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1144,
    "mean_EFFECT": 0,
    "n": 349861,
    "n_snps": 13586282,
    "n_clumped_hits": 109,
    "n_p_sig": 12613,
    "n_mono": 0,
    "n_ns": 1251790,
    "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": 569186,
    "n_est": 351190.7542,
    "ratio_se_n": 1.0019,
    "mean_diff": -5.3896e-07,
    "ratio_diff": 1.2592,
    "sd_y_est1": 1.003,
    "sd_y_est2": 1.0049,
    "r2_sum1": 0.0282,
    "r2_sum2": 0.0281,
    "r2_sum3": 0.028,
    "r2_sum4": 0.028,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0448,
    "ldsc_observed_scale_h2_se": 0.0046,
    "ldsc_intercept_beta": 1.0543,
    "ldsc_intercept_se": 0.0103,
    "ldsc_lambda_gc": 1.1721,
    "ldsc_mean_chisq": 1.3641,
    "ldsc_ratio": 0.1491
}
 

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 TRUE
n_p_sig TRUE
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 13574236 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 9.051329e+00 6.184984e+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 7.902513e+07 5.591486e+07 3.02000e+02 3.293100e+07 7.013871e+07 1.148589e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.250000e-05 1.428920e-02 -2.63462e-01 -3.980800e-03 8.100000e-06 3.967000e-03 2.386860e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.007650e-02 9.720100e-03 1.97090e-03 2.868800e-03 5.286500e-03 1.448060e-02 4.933820e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.819028e-01 2.946865e-01 0.00000e+00 2.222798e-01 4.764425e-01 7.376783e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.819023e-01 2.946868e-01 0.00000e+00 2.222795e-01 4.764419e-01 7.376787e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.908059e-01 2.544033e-01 1.00000e-03 7.430400e-03 6.003370e-02 2.953180e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569186 0.9581058 NA NA NA NA NA 1.963355e-01 2.471013e-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 3.498610e+05 0.000000e+00 3.49861e+05 3.498610e+05 3.498610e+05 3.498610e+05 3.498610e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0021225 0.0041983 0.6131603 0.6131593 0.1106490 0.1894970 349861
1 693731 rs12238997 A G 0.0044995 0.0039671 0.2567078 0.2567072 0.1158220 0.1417730 349861
1 707522 rs371890604 G C 0.0028805 0.0044614 0.5185146 0.5185146 0.0972503 0.1293930 349861
1 717587 rs144155419 G A -0.0012651 0.0106308 0.9052731 0.9052735 0.0157178 0.0045926 349861
1 723329 rs189787166 A T 0.0459074 0.0315573 0.1457451 0.1457436 0.0017201 0.0003994 349861
1 730087 rs148120343 T C 0.0068113 0.0055244 0.2175981 0.2175972 0.0564796 0.0127796 349861
1 731718 rs142557973 T C 0.0027096 0.0037622 0.4713972 0.4713959 0.1217450 0.1543530 349861
1 732032 rs61770163 A C 0.0036490 0.0040137 0.3632829 0.3632831 0.1211440 0.1555510 349861
1 734349 rs141242758 T C 0.0026136 0.0037642 0.4874870 0.4874866 0.1209740 0.1525560 349861
1 740284 rs61770167 C T -0.0029404 0.0172208 0.8644250 0.8644245 0.0057855 0.0023962 349861
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0091888 0.0043446 0.0344326 0.0344324 0.0561652 0.0309934 349861
23 154923374 rs111332691 T A -0.0026452 0.0047764 0.5797049 0.5797043 0.0447935 0.0116556 349861
23 154925045 rs509981 C T -0.0007799 0.0022986 0.7343938 0.7343944 0.2454440 0.3634440 349861
23 154925895 rs538470 C T -0.0014124 0.0023512 0.5480132 0.5480120 0.2417890 0.3634440 349861
23 154927581 rs644138 G A -0.0031267 0.0021614 0.1480079 0.1480066 0.3020040 0.4635760 349861
23 154929412 rs557132 C T -0.0007434 0.0022993 0.7464436 0.7464440 0.2452990 0.3568210 349861
23 154929637 rs35185538 CT C -0.0005170 0.0023999 0.8294320 0.8294317 0.2295300 0.3011920 349861
23 154929952 rs4012982 CAA C -0.0014519 0.0024183 0.5482694 0.5482676 0.2392530 0.3165560 349861
23 154930230 rs781880 A G -0.0008333 0.0022989 0.7169981 0.7169975 0.2457090 0.3618540 349861
23 154930487 rs781879 T A -0.0268481 0.0078915 0.0006686 0.0006685 0.0195209 0.1263580 349861

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110649 ES:SE:LP:AF:SS:ID   0.00212252:0.00419828:0.212426:0.110649:349861:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115822 ES:SE:LP:AF:SS:ID   0.00449954:0.00396712:0.590561:0.115822:349861:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972503    ES:SE:LP:AF:SS:ID   0.00288047:0.00446144:0.285239:0.0972503:349861:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157178    ES:SE:LP:AF:SS:ID   -0.00126509:0.0106308:0.0432204:0.0157178:349861:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00172013   ES:SE:LP:AF:SS:ID   0.0459074:0.0315573:0.836406:0.00172013:349861:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564796    ES:SE:LP:AF:SS:ID   0.00681133:0.00552445:0.662345:0.0564796:349861:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121745 ES:SE:LP:AF:SS:ID   0.00270958:0.00376221:0.326613:0.121745:349861:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121144 ES:SE:LP:AF:SS:ID   0.00364899:0.00401373:0.439755:0.121144:349861:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120974 ES:SE:LP:AF:SS:ID   0.00261355:0.00376423:0.312037:0.120974:349861:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578551   ES:SE:LP:AF:SS:ID   -0.00294036:0.0172208:0.0632727:0.00578551:349861:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188271   ES:SE:LP:AF:SS:ID   -0.00288883:0.0325222:0.0318815:0.00188271:349861:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869759 ES:SE:LP:AF:SS:ID   -0.0033218:0.00371133:0.430901:0.869759:349861:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153174   ES:SE:LP:AF:SS:ID   0.00193494:0.0335773:0.0204307:0.00153174:349861:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122895 ES:SE:LP:AF:SS:ID   0.00302647:0.00367531:0.386955:0.122895:349861:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142708 ES:SE:LP:AF:SS:ID   0.00371737:0.00363292:0.514005:0.142708:349861:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123012 ES:SE:LP:AF:SS:ID   0.00306101:0.00367017:0.393331:0.123012:349861:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870893 ES:SE:LP:AF:SS:ID   -0.00170812:0.00357641:0.198645:0.870893:349861:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875492 ES:SE:LP:AF:SS:ID   -0.00234776:0.00363579:0.285291:0.875492:349861:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   0.00241362:0.00358532:0.300315:0.128631:349861:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363487    ES:SE:LP:AF:SS:ID   0.00298608:0.00650784:0.189535:0.0363487:349861:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870486 ES:SE:LP:AF:SS:ID   -0.001846:0.00357265:0.217984:0.870486:349861:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870587 ES:SE:LP:AF:SS:ID   -0.00176562:0.00357422:0.206687:0.870587:349861:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870481 ES:SE:LP:AF:SS:ID   -0.00184734:0.0035725:0.218183:0.870481:349861:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504546   ES:SE:LP:AF:SS:ID   0.000436122:0.0183438:0.00831683:0.00504546:349861:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501229   ES:SE:LP:AF:SS:ID   0.00129064:0.0183927:0.0250018:0.00501229:349861:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558051   ES:SE:LP:AF:SS:ID   0.00205228:0.0177734:0.0418792:0.00558051:349861:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870566 ES:SE:LP:AF:SS:ID   -0.00143967:0.00356624:0.163399:0.870566:349861:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125972 ES:SE:LP:AF:SS:ID   0.00250519:0.00363915:0.308739:0.125972:349861:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87013  ES:SE:LP:AF:SS:ID   -0.00162822:0.00355765:0.188967:0.87013:349861:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869408 ES:SE:LP:AF:SS:ID   -0.00171125:0.00355427:0.20053:0.869408:349861:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870284 ES:SE:LP:AF:SS:ID   -0.00159199:0.00356073:0.183887:0.870284:349861:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87029  ES:SE:LP:AF:SS:ID   -0.00159465:0.00356099:0.18423:0.87029:349861:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870299 ES:SE:LP:AF:SS:ID   -0.00159058:0.0035611:0.183676:0.870299:349861:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87074  ES:SE:LP:AF:SS:ID   -0.00152259:0.00357016:0.174081:0.87074:349861:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098799 ES:SE:LP:AF:SS:ID   0.00350608:0.00415:0.399897:0.098799:349861:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647255   ES:SE:LP:AF:SS:ID   0.00960488:0.0160567:0.259861:0.00647255:349861:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874649 ES:SE:LP:AF:SS:ID   -0.00233215:0.00362351:0.284144:0.874649:349861:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864035 ES:SE:LP:AF:SS:ID   -0.00249715:0.00355327:0.316776:0.864035:349861:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   -0.00183043:0.00358779:0.214724:0.869419:349861:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866376 ES:SE:LP:AF:SS:ID   -0.0021756:0.0035886:0.264123:0.866376:349861:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987125    ES:SE:LP:AF:SS:ID   0.00204591:0.00429772:0.197881:0.0987125:349861:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871561 ES:SE:LP:AF:SS:ID   -0.00269955:0.00362948:0.340077:0.871561:349861:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871561 ES:SE:LP:AF:SS:ID   -0.00269947:0.00362947:0.340066:0.871561:349861:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   -0.00267681:0.00362955:0.336472:0.87156:349861:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871932 ES:SE:LP:AF:SS:ID   -0.00259679:0.00363161:0.323692:0.871932:349861:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125555 ES:SE:LP:AF:SS:ID   0.0030756:0.00363444:0.400749:0.125555:349861:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105385 ES:SE:LP:AF:SS:ID   0.00363882:0.00395743:0.446311:0.105385:349861:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855372 ES:SE:LP:AF:SS:ID   -0.0015221:0.00355228:0.17503:0.855372:349861:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164253   ES:SE:LP:AF:SS:ID   0.0454406:0.0316121:0.822192:0.00164253:349861:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838283 ES:SE:LP:AF:SS:ID   -0.00422725:0.00349881:0.644026:0.838283:349861:rs376645387