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-30280_irnt/ukb-d-30280_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-30280_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 14:55:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30280_irnt/ukb-d-30280_irnt.vcf.gz ...
Read summary statistics for 13586216 SNPs.
Dropped 12711 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: 0.1296 (0.0101)
Lambda GC: 1.4667
Mean Chi^2: 2.0013
Intercept: 1.1106 (0.0165)
Ratio: 0.1105 (0.0165)
Analysis finished at Mon Nov 25 14:57:15 2019
Total time elapsed: 1.0m:55.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3051,
    "mean_EFFECT": -4.394e-06,
    "n": 344728,
    "n_snps": 13586216,
    "n_clumped_hits": 226,
    "n_p_sig": 45487,
    "n_mono": 0,
    "n_ns": 1251786,
    "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": 569217,
    "n_est": 346032.072,
    "ratio_se_n": 1.0019,
    "mean_diff": 1.0783e-06,
    "ratio_diff": 1.0104,
    "sd_y_est1": 1.0006,
    "sd_y_est2": 1.0025,
    "r2_sum1": 0.0779,
    "r2_sum2": 0.0778,
    "r2_sum3": 0.0775,
    "r2_sum4": 0.0769,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1296,
    "ldsc_observed_scale_h2_se": 0.0101,
    "ldsc_intercept_beta": 1.1106,
    "ldsc_intercept_se": 0.0165,
    "ldsc_lambda_gc": 1.4667,
    "ldsc_mean_chisq": 2.0013,
    "ldsc_ratio": 0.1105
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
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 13574169 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57082 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 9.051358e+00 6.184962e+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 7.902498e+07 5.591474e+07 3.02000e+02 3.293100e+07 7.013848e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -4.400000e-06 1.488410e-02 -2.42448e-01 -4.421700e-03 6.300000e-06 4.438300e-03 2.794100e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.012680e-02 9.768800e-03 1.98060e-03 2.883000e-03 5.312900e-03 1.455220e-02 4.968220e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.555829e-01 3.014950e-01 0.00000e+00 1.830898e-01 4.409750e-01 7.168792e-01 1.000000e+00 ▇▆▆▆▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.555824e-01 3.014953e-01 0.00000e+00 1.830889e-01 4.409744e-01 7.168795e-01 9.999999e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908069e-01 2.544041e-01 1.00000e-03 7.430300e-03 6.003430e-02 2.953250e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569217 0.9581033 NA NA NA NA NA 1.963367e-01 2.471015e-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 3.447280e+05 0.000000e+00 3.44728e+05 3.447280e+05 3.447280e+05 3.447280e+05 3.447280e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0046074 0.0042203 0.2749578 0.2749578 0.1106300 0.1894970 344728
1 693731 rs12238997 A G -0.0019410 0.0039878 0.6264335 0.6264341 0.1158140 0.1417730 344728
1 707522 rs371890604 G C -0.0028506 0.0044852 0.5250661 0.5250656 0.0972244 0.1293930 344728
1 717587 rs144155419 G A -0.0099327 0.0106799 0.3523514 0.3523506 0.0157293 0.0045926 344728
1 723329 rs189787166 A T -0.0063070 0.0317305 0.8424439 0.8424439 0.0017197 0.0003994 344728
1 730087 rs148120343 T C -0.0066125 0.0055512 0.2335780 0.2335772 0.0564851 0.0127796 344728
1 731718 rs142557973 T C -0.0030625 0.0037819 0.4180633 0.4180622 0.1217310 0.1543530 344728
1 732032 rs61770163 A C -0.0024304 0.0040348 0.5469215 0.5469227 0.1211220 0.1555510 344728
1 734349 rs141242758 T C -0.0030110 0.0037839 0.4261809 0.4261811 0.1209620 0.1525560 344728
1 740284 rs61770167 C T 0.0197179 0.0173250 0.2550698 0.2550711 0.0057743 0.0023962 344728
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0143397 0.0043665 0.0010235 0.0010234 0.0561572 0.0309934 344728
23 154923374 rs111332691 T A 0.0028456 0.0047989 0.5532074 0.5532062 0.0447962 0.0116556 344728
23 154925045 rs509981 C T -0.0072551 0.0023094 0.0016804 0.0016802 0.2456230 0.3634440 344728
23 154925895 rs538470 C T -0.0072489 0.0023622 0.0021498 0.0021496 0.2419540 0.3634440 344728
23 154927581 rs644138 G A -0.0029544 0.0021718 0.1737341 0.1737341 0.3021780 0.4635760 344728
23 154929412 rs557132 C T -0.0071892 0.0023100 0.0018574 0.0018573 0.2454770 0.3568210 344728
23 154929637 rs35185538 CT C -0.0055006 0.0024109 0.0225170 0.0225167 0.2297050 0.3011920 344728
23 154929952 rs4012982 CAA C -0.0073863 0.0024297 0.0023660 0.0023659 0.2394410 0.3165560 344728
23 154930230 rs781880 A G -0.0072516 0.0023096 0.0016910 0.0016909 0.2458870 0.3618540 344728
23 154930487 rs781879 T A -0.0042045 0.0079284 0.5958967 0.5958965 0.0195263 0.1263580 344728

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11063  ES:SE:LP:AF:SS:ID   -0.00460736:0.00422029:0.560734:0.11063:344728:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115814 ES:SE:LP:AF:SS:ID   -0.00194105:0.00398776:0.203125:0.115814:344728:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972244    ES:SE:LP:AF:SS:ID   -0.00285061:0.00448522:0.279786:0.0972244:344728:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157293    ES:SE:LP:AF:SS:ID   -0.00993273:0.0106799:0.453024:0.0157293:344728:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00171967   ES:SE:LP:AF:SS:ID   -0.00630702:0.0317305:0.074459:0.00171967:344728:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564851    ES:SE:LP:AF:SS:ID   -0.0066125:0.00555115:0.631568:0.0564851:344728:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121731 ES:SE:LP:AF:SS:ID   -0.00306252:0.00378188:0.378758:0.121731:344728:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121122 ES:SE:LP:AF:SS:ID   -0.00243045:0.00403476:0.262075:0.121122:344728:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120962 ES:SE:LP:AF:SS:ID   -0.00301099:0.00378387:0.370406:0.120962:344728:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00577433   ES:SE:LP:AF:SS:ID   0.0197179:0.017325:0.593341:0.00577433:344728:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187951   ES:SE:LP:AF:SS:ID   0.0175113:0.0327203:0.227293:0.00187951:344728:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869781 ES:SE:LP:AF:SS:ID   0.00384827:0.00373078:0.519546:0.869781:344728:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153602   ES:SE:LP:AF:SS:ID   -0.0218457:0.033702:0.286632:0.00153602:344728:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122887 ES:SE:LP:AF:SS:ID   -0.00302918:0.00369429:0.384852:0.122887:344728:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142713 ES:SE:LP:AF:SS:ID   -0.00130145:0.00365162:0.14174:0.142713:344728:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123004 ES:SE:LP:AF:SS:ID   -0.00308815:0.00368913:0.395191:0.123004:344728:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870907 ES:SE:LP:AF:SS:ID   0.00196525:0.00359512:0.233123:0.870907:344728:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875493 ES:SE:LP:AF:SS:ID   0.00195047:0.00365453:0.22655:0.875493:344728:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128618 ES:SE:LP:AF:SS:ID   -0.00308581:0.00360405:0.40684:0.128618:344728:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363562    ES:SE:LP:AF:SS:ID   -0.0104878:0.0065397:0.963459:0.0363562:344728:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8705   ES:SE:LP:AF:SS:ID   0.00227637:0.00359133:0.278867:0.8705:344728:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870603 ES:SE:LP:AF:SS:ID   0.00221677:0.00359293:0.269825:0.870603:344728:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870495 ES:SE:LP:AF:SS:ID   0.00225674:0.00359118:0.275942:0.870495:344728:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050587    ES:SE:LP:AF:SS:ID   -0.00245041:0.018406:0.0486192:0.0050587:344728:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00502543   ES:SE:LP:AF:SS:ID   -0.00295188:0.0184553:0.0590246:0.00502543:344728:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558653   ES:SE:LP:AF:SS:ID   0.00497377:0.0178504:0.107614:0.00558653:344728:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870578 ES:SE:LP:AF:SS:ID   0.00189456:0.00358488:0.223909:0.870578:344728:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125958 ES:SE:LP:AF:SS:ID   -0.00259791:0.00365811:0.320941:0.125958:344728:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870143 ES:SE:LP:AF:SS:ID   0.00185129:0.00357623:0.218466:0.870143:344728:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869424 ES:SE:LP:AF:SS:ID   0.00188733:0.00357289:0.223781:0.869424:344728:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870297 ES:SE:LP:AF:SS:ID   0.00180619:0.00357933:0.211953:0.870297:344728:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870302 ES:SE:LP:AF:SS:ID   0.00180319:0.00357959:0.211519:0.870302:344728:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870311 ES:SE:LP:AF:SS:ID   0.00182038:0.0035797:0.213899:0.870311:344728:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870753 ES:SE:LP:AF:SS:ID   0.00192441:0.00358881:0.227822:0.870753:344728:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0987466    ES:SE:LP:AF:SS:ID   -0.00212154:0.00417236:0.213873:0.0987466:344728:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00648114   ES:SE:LP:AF:SS:ID   0.00505003:0.0161224:0.122568:0.00648114:344728:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874657 ES:SE:LP:AF:SS:ID   0.00191496:0.0036423:0.222531:0.874657:344728:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864055 ES:SE:LP:AF:SS:ID   0.00257689:0.00357187:0.327312:0.864055:344728:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   0.00168203:0.00360651:0.193183:0.869437:344728:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866397 ES:SE:LP:AF:SS:ID   0.00193447:0.00360747:0.22783:0.866397:344728:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987146    ES:SE:LP:AF:SS:ID   -0.000625416:0.00431995:0.0531112:0.0987146:344728:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   0.00245387:0.00364839:0.299981:0.871574:344728:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871574 ES:SE:LP:AF:SS:ID   0.00245421:0.00364839:0.300032:0.871574:344728:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871573 ES:SE:LP:AF:SS:ID   0.00244436:0.00364846:0.298537:0.871573:344728:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871944 ES:SE:LP:AF:SS:ID   0.0026912:0.00365054:0.336302:0.871944:344728:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125545 ES:SE:LP:AF:SS:ID   -0.00284507:0.00365331:0.360396:0.125545:344728:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105344 ES:SE:LP:AF:SS:ID   -0.0017116:0.00397837:0.175854:0.105344:344728:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855408 ES:SE:LP:AF:SS:ID   0.00125685:0.00357104:0.139739:0.855408:344728:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164172   ES:SE:LP:AF:SS:ID   -0.0114096:0.0317868:0.142885:0.00164172:344728:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838259 ES:SE:LP:AF:SS:ID   -0.00221226:0.00351541:0.276421:0.838259:344728:rs376645387