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-22611_0/ukb-d-22611_0.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-22611_0/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 16:34:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22611_0/ukb-d-22611_0.vcf.gz ...
Read summary statistics for 13566863 SNPs.
Dropped 12681 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0119 (0.0046)
Lambda GC: 1.0244
Mean Chi^2: 1.0288
Intercept: 1.0079 (0.0057)
Ratio: 0.2733 (0.1966)
Analysis finished at Mon Nov 25 16:36:57 2019
Total time elapsed: 2.0m:44.64s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0168,
    "mean_EFFECT": -3.7189e-06,
    "n": 89714,
    "n_snps": 13566863,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1251230,
    "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": 563191,
    "n_est": 90036.2474,
    "ratio_se_n": 1.0018,
    "mean_diff": -9.4984e-06,
    "ratio_diff": 3.5294,
    "sd_y_est1": 0.3527,
    "sd_y_est2": 0.3533,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.0119,
    "ldsc_observed_scale_h2_se": 0.0046,
    "ldsc_intercept_beta": 1.0079,
    "ldsc_intercept_se": 0.0057,
    "ldsc_lambda_gc": 1.0244,
    "ldsc_mean_chisq": 1.0288,
    "ldsc_ratio": 0.2743
}

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 13554846 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57044 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33332 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051329e+00 6.184968e+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 7.902489e+07 5.591644e+07 3.02000e+02 3.292812e+07 7.013467e+07 1.148620e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.700000e-06 9.685200e-03 -1.23795e-01 -2.555900e-03 1.710000e-05 2.612200e-03 1.025320e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 6.968400e-03 6.715600e-03 1.37360e-03 1.991000e-03 3.662200e-03 1.000610e-02 3.383630e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.969576e-01 2.898275e-01 0.00000e+00 2.446628e-01 4.964151e-01 7.484176e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.969558e-01 2.898285e-01 0.00000e+00 2.446595e-01 4.964124e-01 7.484177e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910684e-01 2.544751e-01 1.00000e-03 7.499400e-03 6.030120e-02 2.957645e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563191 0.9584878 NA NA NA NA NA 1.965245e-01 2.471463e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 8.971400e+04 0.000000e+00 8.97140e+04 8.971400e+04 8.971400e+04 8.971400e+04 8.971400e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0020187 0.0029046 0.4870584 0.4870560 0.1116230 0.1894970 89714
1 693731 rs12238997 A G 0.0027915 0.0027513 0.3103002 0.3102982 0.1166320 0.1417730 89714
1 707522 rs371890604 G C 0.0030644 0.0030927 0.3217548 0.3217513 0.0980012 0.1293930 89714
1 717587 rs144155419 G A -0.0017244 0.0073603 0.8147711 0.8147703 0.0158424 0.0045926 89714
1 723329 rs189787166 A T -0.0479839 0.0216444 0.0266312 0.0266286 0.0017596 0.0003994 89714
1 730087 rs148120343 T C 0.0057075 0.0038150 0.1346421 0.1346386 0.0570389 0.0127796 89714
1 731718 rs142557973 T C 0.0028308 0.0026108 0.2782403 0.2782365 0.1225270 0.1543530 89714
1 732032 rs61770163 A C 0.0017954 0.0027840 0.5190008 0.5189999 0.1221950 0.1555510 89714
1 734349 rs141242758 T C 0.0028898 0.0026127 0.2687089 0.2687062 0.1217590 0.1525560 89714
1 740284 rs61770167 C T 0.0161706 0.0120280 0.1788191 0.1788149 0.0057274 0.0023962 89714
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0048942 0.0030569 0.1093810 0.1093777 0.0552893 0.0309934 89714
23 154923374 rs111332691 T A -0.0021648 0.0033244 0.5149286 0.5149262 0.0448982 0.0116556 89714
23 154925045 rs509981 C T 0.0008731 0.0016026 0.5858872 0.5858849 0.2447410 0.3634440 89714
23 154925895 rs538470 C T 0.0012593 0.0016382 0.4420862 0.4420858 0.2412510 0.3634440 89714
23 154927581 rs644138 G A 0.0020163 0.0015074 0.1810369 0.1810330 0.3004360 0.4635760 89714
23 154929412 rs557132 C T 0.0008961 0.0016030 0.5761745 0.5761729 0.2446020 0.3568210 89714
23 154929637 rs35185538 CT C 0.0010365 0.0016737 0.5357288 0.5357281 0.2289830 0.3011920 89714
23 154929952 rs4012982 CAA C 0.0007643 0.0016872 0.6505355 0.6505360 0.2384720 0.3165560 89714
23 154930230 rs781880 A G 0.0008541 0.0016025 0.5940664 0.5940666 0.2450560 0.3618540 89714
23 154930487 rs781879 T A -0.0025545 0.0054316 0.6381430 0.6381422 0.0196698 0.1263580 89714

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111623 ES:SE:LP:AF:SS:ID   0.00201868:0.00290458:0.312419:0.111623:89714:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116632 ES:SE:LP:AF:SS:ID   0.00279149:0.00275133:0.508218:0.116632:89714:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0980012    ES:SE:LP:AF:SS:ID   0.00306442:0.00309267:0.492475:0.0980012:89714:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158424    ES:SE:LP:AF:SS:ID   -0.00172435:0.00736032:0.0889644:0.0158424:89714:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00175956   ES:SE:LP:AF:SS:ID   -0.0479839:0.0216444:1.57461:0.00175956:89714:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570389    ES:SE:LP:AF:SS:ID   0.00570749:0.00381502:0.870819:0.0570389:89714:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122527 ES:SE:LP:AF:SS:ID   0.00283083:0.00261077:0.55558:0.122527:89714:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122195 ES:SE:LP:AF:SS:ID   0.0017954:0.00278405:0.284832:0.122195:89714:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121759 ES:SE:LP:AF:SS:ID   0.00288978:0.00261271:0.570718:0.121759:89714:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00572742   ES:SE:LP:AF:SS:ID   0.0161706:0.012028:0.747586:0.00572742:89714:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00183221   ES:SE:LP:AF:SS:ID   -0.0181797:0.0229046:0.369204:0.00183221:89714:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868769 ES:SE:LP:AF:SS:ID   -0.00199002:0.00257039:0.357725:0.868769:89714:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00162108   ES:SE:LP:AF:SS:ID   0.00533221:0.022573:0.0897695:0.00162108:89714:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123875 ES:SE:LP:AF:SS:ID   0.00181851:0.00254806:0.322918:0.123875:89714:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143391 ES:SE:LP:AF:SS:ID   0.00241736:0.0025229:0.471106:0.143391:89714:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124012 ES:SE:LP:AF:SS:ID   0.0018562:0.00254436:0.331916:0.124012:89714:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869705 ES:SE:LP:AF:SS:ID   -0.00164997:0.00247916:0.296098:0.869705:89714:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874365 ES:SE:LP:AF:SS:ID   -0.00204303:0.00251947:0.379419:0.874365:89714:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129721 ES:SE:LP:AF:SS:ID   0.00178967:0.0024869:0.326289:0.129721:89714:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.035825 ES:SE:LP:AF:SS:ID   -0.00930288:0.00454711:1.38966:0.035825:89714:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869349 ES:SE:LP:AF:SS:ID   -0.00169612:0.0024771:0.306693:0.869349:89714:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869427 ES:SE:LP:AF:SS:ID   -0.00173222:0.0024782:0.314649:0.869427:89714:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869345 ES:SE:LP:AF:SS:ID   -0.0016929:0.002477:0.305987:0.869345:89714:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00533064   ES:SE:LP:AF:SS:ID   -0.0107387:0.0123674:0.414283:0.00533064:89714:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00529572   ES:SE:LP:AF:SS:ID   -0.0108233:0.0123982:0.417162:0.00529572:89714:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00567704   ES:SE:LP:AF:SS:ID   -0.031813:0.012191:2.0425:0.00567704:89714:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869328 ES:SE:LP:AF:SS:ID   -0.00184333:0.00247186:0.341191:0.869328:89714:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127114 ES:SE:LP:AF:SS:ID   0.00186276:0.00252319:0.336903:0.127114:89714:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86885  ES:SE:LP:AF:SS:ID   -0.00172139:0.00246541:0.314218:0.86885:89714:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868235 ES:SE:LP:AF:SS:ID   -0.00197106:0.00246384:0.372926:0.868235:89714:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869004 ES:SE:LP:AF:SS:ID   -0.00169718:0.00246767:0.308387:0.869004:89714:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86901  ES:SE:LP:AF:SS:ID   -0.00169658:0.00246784:0.308225:0.86901:89714:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869012 ES:SE:LP:AF:SS:ID   -0.00169467:0.00246786:0.307792:0.869012:89714:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869497 ES:SE:LP:AF:SS:ID   -0.00177977:0.0024745:0.326064:0.869497:89714:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0992799    ES:SE:LP:AF:SS:ID   0.00274427:0.00288055:0.467564:0.0992799:89714:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00652131   ES:SE:LP:AF:SS:ID   -0.0237302:0.0110996:1.48778:0.00652131:89714:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873488 ES:SE:LP:AF:SS:ID   -0.00171809:0.00251114:0.306396:0.873488:89714:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862845 ES:SE:LP:AF:SS:ID   -0.00153244:0.00246314:0.272586:0.862845:89714:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86828  ES:SE:LP:AF:SS:ID   -0.00169843:0.00248758:0.305608:0.86828:89714:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865153 ES:SE:LP:AF:SS:ID   -0.00158686:0.002488:0.280997:0.865153:89714:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0996835    ES:SE:LP:AF:SS:ID   0.000993256:0.00297825:0.1315:0.0996835:89714:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870449 ES:SE:LP:AF:SS:ID   -0.00132462:0.00251642:0.222849:0.870449:89714:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870449 ES:SE:LP:AF:SS:ID   -0.00132456:0.00251642:0.222838:0.870449:89714:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870446 ES:SE:LP:AF:SS:ID   -0.00132485:0.00251643:0.222894:0.870446:89714:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870814 ES:SE:LP:AF:SS:ID   -0.00132075:0.00251762:0.22195:0.870814:89714:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12671  ES:SE:LP:AF:SS:ID   0.00171085:0.0025204:0.303412:0.12671:89714:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106163 ES:SE:LP:AF:SS:ID   0.00333753:0.00274014:0.651265:0.106163:89714:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854165 ES:SE:LP:AF:SS:ID   -0.00156787:0.00246228:0.280433:0.854165:89714:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00167172   ES:SE:LP:AF:SS:ID   -0.0451346:0.0217114:1.42442:0.00167172:89714:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839232 ES:SE:LP:AF:SS:ID   0.00440387:0.00243524:1.15151:0.839232:89714:rs376645387