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-30750_irnt/ukb-d-30750_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-30750_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 14:54:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30750_irnt/ukb-d-30750_irnt.vcf.gz ...
Read summary statistics for 13586179 SNPs.
Dropped 12713 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: 0.1876 (0.0161)
Lambda GC: 1.6219
Mean Chi^2: 2.4938
Intercept: 1.1777 (0.0198)
Ratio: 0.119 (0.0132)
Analysis finished at Mon Nov 25 14:57:05 2019
Total time elapsed: 2.0m:54.97s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3963,
    "mean_EFFECT": 0.0001,
    "n": 344182,
    "n_snps": 13586179,
    "n_clumped_hits": 321,
    "n_p_sig": 79337,
    "n_mono": 0,
    "n_ns": 1251783,
    "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": 569193,
    "n_est": 345493.1417,
    "ratio_se_n": 1.0019,
    "mean_diff": 4.6196e-06,
    "ratio_diff": 12.1874,
    "sd_y_est1": 0.957,
    "sd_y_est2": 0.9589,
    "r2_sum1": 0.1008,
    "r2_sum2": 0.11,
    "r2_sum3": 0.1096,
    "r2_sum4": 0.1093,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1876,
    "ldsc_observed_scale_h2_se": 0.0161,
    "ldsc_intercept_beta": 1.1777,
    "ldsc_intercept_se": 0.0198,
    "ldsc_lambda_gc": 1.6219,
    "ldsc_mean_chisq": 2.4938,
    "ldsc_ratio": 0.119
}
 

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 1.000000 3 94 0 13574130 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 57081 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.051361e+00 6.184991e+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 7.902488e+07 5.591481e+07 3.02000e+02 3.293102e+07 7.013812e+07 1.148586e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 1.165000e-04 1.449310e-02 -5.49810e-01 -4.386000e-03 3.480000e-05 4.506500e-03 2.099900e-01 ▁▁▁▇▁
numeric SE 0 1.000000 NA NA NA NA NA 9.693300e-03 9.350500e-03 1.89640e-03 2.759800e-03 5.085600e-03 1.393000e-02 4.731200e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.446068e-01 3.047122e-01 0.00000e+00 1.662501e-01 4.254397e-01 7.087793e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.446063e-01 3.047125e-01 0.00000e+00 1.662480e-01 4.254417e-01 7.087844e-01 9.999999e-01 ▇▆▅▅▅
numeric AF 0 1.000000 NA NA NA NA NA 1.908070e-01 2.544038e-01 1.00000e-03 7.430800e-03 6.004000e-02 2.953300e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569193 0.958105 NA NA NA NA NA 1.963368e-01 2.471017e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 3.441820e+05 0.000000e+00 3.44182e+05 3.441820e+05 3.441820e+05 3.441820e+05 3.441820e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0089662 0.0040430 0.0265748 0.0265746 0.1104400 0.1894970 344182
1 693731 rs12238997 A G -0.0043466 0.0038196 0.2551197 0.2551319 0.1156900 0.1417730 344182
1 707522 rs371890604 G C -0.0092753 0.0042946 0.0307943 0.0307913 0.0971900 0.1293930 344182
1 717587 rs144155419 G A 0.0169670 0.0102480 0.0978048 0.0977947 0.0156590 0.0045926 344182
1 723329 rs189787166 A T -0.0080245 0.0303020 0.7911503 0.7911501 0.0017229 0.0003994 344182
1 730087 rs148120343 T C -0.0115290 0.0053233 0.0303333 0.0303294 0.0563600 0.0127796 344182
1 731718 rs142557973 T C -0.0050137 0.0036221 0.1662999 0.1662981 0.1216100 0.1543530 344182
1 732032 rs61770163 A C -0.0050187 0.0038640 0.1940001 0.1940004 0.1210600 0.1555510 344182
1 734349 rs141242758 T C -0.0048791 0.0036241 0.1782100 0.1782081 0.1208300 0.1525560 344182
1 740284 rs61770167 C T 0.0001144 0.0166280 0.9945100 0.9945125 0.0057445 0.0023962 344182
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0002950 0.0041811 0.9437501 0.9437457 0.056197 0.0309934 344182
23 154923374 rs111332691 T A 0.0055405 0.0045913 0.2275302 0.2275327 0.044889 0.0116556 344182
23 154925045 rs509981 C T -0.0059495 0.0022119 0.0071497 0.0071501 0.245480 0.3634440 344182
23 154925895 rs538470 C T -0.0063564 0.0022627 0.0049656 0.0049663 0.241790 0.3634440 344182
23 154927581 rs644138 G A -0.0052375 0.0020800 0.0118021 0.0118014 0.302060 0.4635760 344182
23 154929412 rs557132 C T -0.0058877 0.0022126 0.0077900 0.0077912 0.245330 0.3568210 344182
23 154929637 rs35185538 CT C -0.0047916 0.0023095 0.0380137 0.0380111 0.229580 0.3011920 344182
23 154929952 rs4012982 CAA C -0.0056622 0.0023270 0.0149630 0.0149635 0.239300 0.3165560 344182
23 154930230 rs781880 A G -0.0057878 0.0022122 0.0088891 0.0088886 0.245720 0.3618540 344182
23 154930487 rs781879 T A 0.0064524 0.0075818 0.3947499 0.3947482 0.019594 0.1263580 344182

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11044  ES:SE:LP:AF:SS:ID   -0.0089662:0.004043:1.57553:0.11044:344182:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11569  ES:SE:LP:AF:SS:ID   -0.0043466:0.0038196:0.593256:0.11569:344182:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.09719  ES:SE:LP:AF:SS:ID   -0.0092753:0.0042946:1.51153:0.09719:344182:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015659 ES:SE:LP:AF:SS:ID   0.016967:0.010248:1.00964:0.015659:344182:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017229    ES:SE:LP:AF:SS:ID   -0.0080245:0.030302:0.101741:0.0017229:344182:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.05636  ES:SE:LP:AF:SS:ID   -0.011529:0.0053233:1.51808:0.05636:344182:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12161  ES:SE:LP:AF:SS:ID   -0.0050137:0.0036221:0.779108:0.12161:344182:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12106  ES:SE:LP:AF:SS:ID   -0.0050187:0.003864:0.712198:0.12106:344182:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12083  ES:SE:LP:AF:SS:ID   -0.0048791:0.0036241:0.749068:0.12083:344182:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057445    ES:SE:LP:AF:SS:ID   0.00011436:0.016628:0.00239085:0.0057445:344182:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.001891 ES:SE:LP:AF:SS:ID   -0.017654:0.031174:0.243235:0.001891:344182:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86988  ES:SE:LP:AF:SS:ID   0.0056644:0.0035728:0.947383:0.86988:344182:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015301    ES:SE:LP:AF:SS:ID   0.0076243:0.03234:0.089573:0.0015301:344182:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12278  ES:SE:LP:AF:SS:ID   -0.0055017:0.0035384:0.920855:0.12278:344182:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14261  ES:SE:LP:AF:SS:ID   -0.0040776:0.0034969:0.613323:0.14261:344182:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12289  ES:SE:LP:AF:SS:ID   -0.0054814:0.0035335:0.917789:0.12289:344182:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87101  ES:SE:LP:AF:SS:ID   0.0052477:0.0034426:0.894762:0.87101:344182:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.8756   ES:SE:LP:AF:SS:ID   0.0052842:0.0035001:0.882331:0.8756:344182:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.1285   ES:SE:LP:AF:SS:ID   -0.0052801:0.0034514:0.899457:0.1285:344182:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036395 ES:SE:LP:AF:SS:ID   -0.010777:0.0062568:1.07058:0.036395:344182:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8706   ES:SE:LP:AF:SS:ID   0.0053288:0.003439:0.916282:0.8706:344182:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8707   ES:SE:LP:AF:SS:ID   0.005389:0.0034405:0.930813:0.8707:344182:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8706   ES:SE:LP:AF:SS:ID   0.0052897:0.0034389:0.906578:0.8706:344182:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050345    ES:SE:LP:AF:SS:ID   0.011011:0.017661:0.273281:0.0050345:344182:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050014    ES:SE:LP:AF:SS:ID   0.010258:0.017709:0.249932:0.0050014:344182:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0056138    ES:SE:LP:AF:SS:ID   -0.006274:0.017046:0.147014:0.0056138:344182:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87067  ES:SE:LP:AF:SS:ID   0.0051896:0.0034328:0.88409:0.87067:344182:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12585  ES:SE:LP:AF:SS:ID   -0.005077:0.0035032:0.831886:0.12585:344182:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87024  ES:SE:LP:AF:SS:ID   0.0052037:0.0034245:0.890692:0.87024:344182:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86953  ES:SE:LP:AF:SS:ID   0.0049763:0.0034214:0.836183:0.86953:344182:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87039  ES:SE:LP:AF:SS:ID   0.0051675:0.0034274:0.880645:0.87039:344182:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8704   ES:SE:LP:AF:SS:ID   0.0051751:0.0034277:0.882397:0.8704:344182:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8704   ES:SE:LP:AF:SS:ID   0.005181:0.0034278:0.883824:0.8704:344182:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87085  ES:SE:LP:AF:SS:ID   0.0051674:0.0034366:0.877227:0.87085:344182:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098736 ES:SE:LP:AF:SS:ID   -0.010092:0.0039945:1.9384:0.098736:344182:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0065064    ES:SE:LP:AF:SS:ID   -0.0040179:0.015399:0.100097:0.0065064:344182:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87476  ES:SE:LP:AF:SS:ID   0.0053982:0.0034882:0.914602:0.87476:344182:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86414  ES:SE:LP:AF:SS:ID   0.0064452:0.0034201:1.2255:0.86414:344182:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86955  ES:SE:LP:AF:SS:ID   0.0055698:0.0034537:0.971388:0.86955:344182:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86649  ES:SE:LP:AF:SS:ID   0.0060781:0.0034543:1.10522:0.86649:344182:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098689 ES:SE:LP:AF:SS:ID   -0.0059323:0.0041351:0.819874:0.098689:344182:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87168  ES:SE:LP:AF:SS:ID   0.0056528:0.003494:0.975925:0.87168:344182:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87168  ES:SE:LP:AF:SS:ID   0.0056531:0.003494:0.976007:0.87168:344182:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87168  ES:SE:LP:AF:SS:ID   0.0056547:0.0034941:0.976377:0.87168:344182:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87206  ES:SE:LP:AF:SS:ID   0.0055624:0.0034962:0.952297:0.87206:344182:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12543  ES:SE:LP:AF:SS:ID   -0.0054412:0.0034989:0.921108:0.12543:344182:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10533  ES:SE:LP:AF:SS:ID   -0.008724:0.0038099:1.65693:0.10533:344182:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85548  ES:SE:LP:AF:SS:ID   0.0068517:0.0034189:1.34617:0.85548:344182:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016444    ES:SE:LP:AF:SS:ID   -0.019924:0.030367:0.290934:0.0016444:344182:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83838  ES:SE:LP:AF:SS:ID   -0.0013694:0.003367:0.164798:0.83838:344182:rs376645387