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-20419/ukb-d-20419.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-20419/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 17:19:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20419/ukb-d-20419.vcf.gz ...
Read summary statistics for 13541980 SNPs.
Dropped 12658 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, 1283495 SNPs remain.
After merging with regression SNP LD, 1283495 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0269 (0.0133)
Lambda GC: 1.0248
Mean Chi^2: 1.0211
Intercept: 1.0024 (0.006)
Ratio: 0.1116 (0.2827)
Analysis finished at Mon Nov 25 17:22:11 2019
Total time elapsed: 2.0m:18.59s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.016,
    "mean_EFFECT": -0,
    "n": 34879,
    "n_snps": 13541980,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250247,
    "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": 557627,
    "n_est": 34997.1495,
    "ratio_se_n": 1.0017,
    "mean_diff": -0,
    "ratio_diff": 25.6583,
    "sd_y_est1": 0.4273,
    "sd_y_est2": 0.428,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283495,
    "ldsc_nsnp_merge_regression_ld": 1283495,
    "ldsc_observed_scale_h2_beta": 0.0269,
    "ldsc_observed_scale_h2_se": 0.0133,
    "ldsc_intercept_beta": 1.0024,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0248,
    "ldsc_mean_chisq": 1.0211,
    "ldsc_ratio": 0.1137
}

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 13529986 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57006 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33315 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051502e+00 6.185053e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.902371e+07 5.591531e+07 302.000000 3.292523e+07 7.014082e+07 1.148561e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.240000e-05 1.874100e-02 -0.242286 -4.972800e-03 1.200000e-05 5.043700e-03 2.265300e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.348200e-02 1.297780e-02 0.002746 3.865400e-03 7.091500e-03 1.934010e-02 7.035980e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.973261e-01 2.892039e-01 0.000000 2.461019e-01 4.965889e-01 7.476735e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.973215e-01 2.892066e-01 0.000000 2.460942e-01 4.965849e-01 7.476709e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.913929e-01 2.545462e-01 0.001000 7.585500e-03 6.071490e-02 2.965280e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 557627 0.9588223 NA NA NA NA NA 1.967642e-01 2.471949e-01 0.000000 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.487900e+04 0.000000e+00 34879.000000 3.487900e+04 3.487900e+04 3.487900e+04 3.487900e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0003400 0.0056406 0.9519370 0.9519371 0.1121280 0.1894970 34879
1 693731 rs12238997 A G 0.0037012 0.0053231 0.4868621 0.4868571 0.1173920 0.1417730 34879
1 707522 rs371890604 G C 0.0057012 0.0059754 0.3400314 0.3400244 0.0989940 0.1293930 34879
1 717587 rs144155419 G A -0.0215828 0.0140439 0.1243489 0.1243399 0.0163864 0.0045926 34879
1 723329 rs189787166 A T -0.0077853 0.0411424 0.8499150 0.8499140 0.0018364 0.0003994 34879
1 730087 rs148120343 T C 0.0026009 0.0073829 0.7246228 0.7246192 0.0572683 0.0127796 34879
1 731718 rs142557973 T C 0.0037316 0.0050460 0.4595936 0.4595890 0.1239450 0.1543530 34879
1 732032 rs61770163 A C 0.0038847 0.0053816 0.4703910 0.4703865 0.1233630 0.1555510 34879
1 734349 rs141242758 T C 0.0035238 0.0050500 0.4853176 0.4853142 0.1231410 0.1525560 34879
1 740284 rs61770167 C T 0.0208358 0.0235254 0.3757976 0.3757940 0.0056672 0.0023962 34879
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0055942 0.0060343 0.3539012 0.3538942 0.0567134 0.0309934 34879
23 154923374 rs111332691 T A 0.0054709 0.0067404 0.4169894 0.4169838 0.0439089 0.0116556 34879
23 154925045 rs509981 C T 0.0009014 0.0032171 0.7793472 0.7793459 0.2432830 0.3634440 34879
23 154925895 rs538470 C T 0.0013656 0.0032898 0.6780832 0.6780804 0.2396290 0.3634440 34879
23 154927581 rs644138 G A -0.0005311 0.0030170 0.8602671 0.8602661 0.3004760 0.4635760 34879
23 154929412 rs557132 C T 0.0010142 0.0032182 0.7526568 0.7526548 0.2431150 0.3568210 34879
23 154929637 rs35185538 CT C 0.0045822 0.0033595 0.1725941 0.1725849 0.2277230 0.3011920 34879
23 154929952 rs4012982 CAA C 0.0000083 0.0033887 0.9980510 0.9980510 0.2375460 0.3165560 34879
23 154930230 rs781880 A G 0.0011894 0.0032177 0.7116509 0.7116498 0.2434030 0.3618540 34879
23 154930487 rs781879 T A -0.0198988 0.0106859 0.0625893 0.0625813 0.0202229 0.1263580 34879

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112128 ES:SE:LP:AF:SS:ID   0.000339986:0.00564064:0.0213918:0.112128:34879:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117392 ES:SE:LP:AF:SS:ID   0.00370121:0.00532306:0.312594:0.117392:34879:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098994 ES:SE:LP:AF:SS:ID   0.00570124:0.00597541:0.468481:0.098994:34879:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0163864    ES:SE:LP:AF:SS:ID   -0.0215828:0.0140439:0.905358:0.0163864:34879:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00183643   ES:SE:LP:AF:SS:ID   -0.0077853:0.0411424:0.0706245:0.00183643:34879:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0572683    ES:SE:LP:AF:SS:ID   0.00260093:0.00738288:0.139888:0.0572683:34879:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123945 ES:SE:LP:AF:SS:ID   0.00373163:0.00504599:0.337626:0.123945:34879:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123363 ES:SE:LP:AF:SS:ID   0.00388471:0.0053816:0.327541:0.123363:34879:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123141 ES:SE:LP:AF:SS:ID   0.00352378:0.00504998:0.313974:0.123141:34879:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00566716   ES:SE:LP:AF:SS:ID   0.0208358:0.0235254:0.425046:0.00566716:34879:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00200441   ES:SE:LP:AF:SS:ID   0.00715707:0.041995:0.0631466:0.00200441:34879:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867329 ES:SE:LP:AF:SS:ID   -0.00257158:0.00495984:0.218872:0.867329:34879:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00145748   ES:SE:LP:AF:SS:ID   0.0639482:0.0465885:0.769858:0.00145748:34879:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.125169 ES:SE:LP:AF:SS:ID   0.00433263:0.00491944:0.421959:0.125169:34879:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145054 ES:SE:LP:AF:SS:ID   0.00390385:0.00486744:0.374133:0.145054:34879:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125244 ES:SE:LP:AF:SS:ID   0.00436459:0.00491295:0.426733:0.125244:34879:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868081 ES:SE:LP:AF:SS:ID   -0.00354639:0.00479025:0.338092:0.868081:34879:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873103 ES:SE:LP:AF:SS:ID   -0.00404577:0.00486476:0.391888:0.873103:34879:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131361 ES:SE:LP:AF:SS:ID   0.0037549:0.00480156:0.3623:0.131361:34879:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363543    ES:SE:LP:AF:SS:ID   0.00471299:0.00877455:0.228274:0.0363543:34879:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867621 ES:SE:LP:AF:SS:ID   -0.00360275:0.00478346:0.345483:0.867621:34879:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867696 ES:SE:LP:AF:SS:ID   -0.00359717:0.00478452:0.344712:0.867696:34879:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867613 ES:SE:LP:AF:SS:ID   -0.00359435:0.00478322:0.34449:0.867613:34879:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00545943   ES:SE:LP:AF:SS:ID   0.0153166:0.0237007:0.285569:0.00545943:34879:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00543357   ES:SE:LP:AF:SS:ID   0.015923:0.0237494:0.298804:0.00543357:34879:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00583198   ES:SE:LP:AF:SS:ID   0.00571739:0.0232824:0.0936547:0.00583198:34879:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.867728 ES:SE:LP:AF:SS:ID   -0.00351593:0.00477666:0.335643:0.867728:34879:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.128624 ES:SE:LP:AF:SS:ID   0.00367913:0.00487179:0.346652:0.128624:34879:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.867212 ES:SE:LP:AF:SS:ID   -0.00350344:0.00476429:0.335237:0.867212:34879:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866649 ES:SE:LP:AF:SS:ID   -0.00300232:0.00476122:0.277102:0.866649:34879:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86741  ES:SE:LP:AF:SS:ID   -0.00330867:0.00476921:0.311723:0.86741:34879:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867417 ES:SE:LP:AF:SS:ID   -0.00330086:0.00476952:0.310784:0.867417:34879:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867419 ES:SE:LP:AF:SS:ID   -0.00330026:0.00476954:0.310712:0.867419:34879:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867866 ES:SE:LP:AF:SS:ID   -0.00350858:0.00478104:0.334379:0.867866:34879:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100609 ES:SE:LP:AF:SS:ID   0.00458971:0.00554902:0.389155:0.100609:34879:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00679132   ES:SE:LP:AF:SS:ID   0.00310065:0.0210551:0.0540762:0.00679132:34879:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872186 ES:SE:LP:AF:SS:ID   -0.00317692:0.0048523:0.29018:0.872186:34879:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.861062 ES:SE:LP:AF:SS:ID   -0.00423853:0.00475503:0.428602:0.861062:34879:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866794 ES:SE:LP:AF:SS:ID   -0.00366393:0.00480906:0.350533:0.866794:34879:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.863806 ES:SE:LP:AF:SS:ID   -0.00334517:0.00480707:0.312913:0.863806:34879:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100895 ES:SE:LP:AF:SS:ID   0.000466686:0.00573755:0.029108:0.100895:34879:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.86902  ES:SE:LP:AF:SS:ID   -0.00297059:0.00485805:0.266893:0.86902:34879:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.86902  ES:SE:LP:AF:SS:ID   -0.00297118:0.00485805:0.266959:0.86902:34879:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.869016 ES:SE:LP:AF:SS:ID   -0.00297154:0.00485805:0.266997:0.869016:34879:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869412 ES:SE:LP:AF:SS:ID   -0.00309205:0.00486123:0.280057:0.869412:34879:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128037 ES:SE:LP:AF:SS:ID   0.00328493:0.00486863:0.30115:0.128037:34879:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106992 ES:SE:LP:AF:SS:ID   0.0053284:0.00530445:0.501501:0.106992:34879:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852743 ES:SE:LP:AF:SS:ID   -0.00361295:0.00475215:0.349601:0.852743:34879:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00175762   ES:SE:LP:AF:SS:ID   -0.0131778:0.0413221:0.125054:0.00175762:34879:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837773 ES:SE:LP:AF:SS:ID   -0.00112316:0.00472239:0.0904392:0.837773:34879:rs376645387