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-30010_irnt/ukb-d-30010_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-30010_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 14:51:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30010_irnt/ukb-d-30010_irnt.vcf.gz ...
Read summary statistics for 13586288 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: 0.1959 (0.0155)
Lambda GC: 1.681
Mean Chi^2: 2.6055
Intercept: 1.2222 (0.0202)
Ratio: 0.1384 (0.0126)
Analysis finished at Mon Nov 25 14:53:37 2019
Total time elapsed: 2.0m:19.04s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.4224,
    "mean_EFFECT": 0,
    "n": 350475,
    "n_snps": 13586288,
    "n_clumped_hits": 360,
    "n_p_sig": 77623,
    "n_mono": 0,
    "n_ns": 1251793,
    "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": 569192,
    "n_est": 351810.6859,
    "ratio_se_n": 1.0019,
    "mean_diff": 3.2982e-06,
    "ratio_diff": 3.399,
    "sd_y_est1": 0.8561,
    "sd_y_est2": 0.8577,
    "r2_sum1": 0.0755,
    "r2_sum2": 0.103,
    "r2_sum3": 0.1026,
    "r2_sum4": 0.1025,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1959,
    "ldsc_observed_scale_h2_se": 0.0155,
    "ldsc_intercept_beta": 1.2222,
    "ldsc_intercept_se": 0.0202,
    "ldsc_lambda_gc": 1.681,
    "ldsc_mean_chisq": 2.6055,
    "ldsc_ratio": 0.1384
}

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 13574242 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 9.051336e+00 6.184983e+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 7.902521e+07 5.591483e+07 3.02000e+02 3.293109e+07 7.013886e+07 1.148590e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.400000e-05 1.290220e-02 -2.41252e-01 -4.000700e-03 -2.200000e-06 4.003000e-03 3.824950e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.592900e-03 8.289000e-03 1.68070e-03 2.446400e-03 4.508100e-03 1.234890e-02 4.202310e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.407020e-01 3.052859e-01 0.00000e+00 1.610549e-01 4.211526e-01 7.044384e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.407016e-01 3.052861e-01 0.00000e+00 1.610542e-01 4.211516e-01 7.044387e-01 1.000000e+00 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908060e-01 2.544034e-01 1.00000e-03 7.430500e-03 6.003400e-02 2.953170e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569192 0.9581054 NA NA NA NA NA 1.963356e-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 3.504750e+05 0.000000e+00 3.50475e+05 3.504750e+05 3.504750e+05 3.504750e+05 3.504750e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0047859 0.0035798 0.1812500 0.1812487 0.1106770 0.1894970 350475
1 693731 rs12238997 A G -0.0037769 0.0033825 0.2641648 0.2641628 0.1158570 0.1417730 350475
1 707522 rs371890604 G C -0.0043910 0.0038039 0.2483562 0.2483563 0.0972836 0.1293930 350475
1 717587 rs144155419 G A -0.0044143 0.0090664 0.6263383 0.6263379 0.0157160 0.0045926 350475
1 723329 rs189787166 A T 0.0279235 0.0268676 0.2986661 0.2986652 0.0017252 0.0003994 350475
1 730087 rs148120343 T C -0.0041482 0.0047108 0.3785533 0.3785533 0.0564937 0.0127796 350475
1 731718 rs142557973 T C -0.0043947 0.0032079 0.1706990 0.1706974 0.1217790 0.1543530 350475
1 732032 rs61770163 A C -0.0037345 0.0034223 0.2751801 0.2751791 0.1211750 0.1555510 350475
1 734349 rs141242758 T C -0.0044332 0.0032096 0.1672030 0.1672023 0.1210090 0.1525560 350475
1 740284 rs61770167 C T 0.0241520 0.0146842 0.1000200 0.1000191 0.0057871 0.0023962 350475
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0025658 0.0037053 0.4886400 0.4886399 0.0561530 0.0309934 350475
23 154923374 rs111332691 T A -0.0062569 0.0040732 0.1245111 0.1245100 0.0447906 0.0116556 350475
23 154925045 rs509981 C T -0.0058953 0.0019601 0.0026328 0.0026326 0.2454620 0.3634440 350475
23 154925895 rs538470 C T -0.0057282 0.0020049 0.0042757 0.0042754 0.2418080 0.3634440 350475
23 154927581 rs644138 G A -0.0045349 0.0018432 0.0138794 0.0138791 0.3020100 0.4635760 350475
23 154929412 rs557132 C T -0.0059525 0.0019607 0.0023981 0.0023979 0.2453160 0.3568210 350475
23 154929637 rs35185538 CT C -0.0063535 0.0020465 0.0019060 0.0019059 0.2295380 0.3011920 350475
23 154929952 rs4012982 CAA C -0.0062042 0.0020622 0.0026254 0.0026253 0.2392710 0.3165560 350475
23 154930230 rs781880 A G -0.0058277 0.0019603 0.0029511 0.0029510 0.2457270 0.3618540 350475
23 154930487 rs781879 T A -0.0086090 0.0067274 0.2006522 0.2006518 0.0195298 0.1263580 350475

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110677 ES:SE:LP:AF:SS:ID   -0.00478592:0.00357981:0.741722:0.110677:350475:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115857 ES:SE:LP:AF:SS:ID   -0.00377692:0.0033825:0.578125:0.115857:350475:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972836    ES:SE:LP:AF:SS:ID   -0.00439099:0.00380386:0.604925:0.0972836:350475:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015716 ES:SE:LP:AF:SS:ID   -0.0044143:0.00906636:0.203191:0.015716:350475:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00172518   ES:SE:LP:AF:SS:ID   0.0279235:0.0268676:0.524814:0.00172518:350475:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564937    ES:SE:LP:AF:SS:ID   -0.00414821:0.00471085:0.421873:0.0564937:350475:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121779 ES:SE:LP:AF:SS:ID   -0.00439466:0.00320786:0.767769:0.121779:350475:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121175 ES:SE:LP:AF:SS:ID   -0.00373447:0.00342231:0.560383:0.121175:350475:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121009 ES:SE:LP:AF:SS:ID   -0.00443323:0.00320958:0.776756:0.121009:350475:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578709   ES:SE:LP:AF:SS:ID   0.024152:0.0146842:0.999913:0.00578709:350475:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00188408   ES:SE:LP:AF:SS:ID   0.0303825:0.0277144:0.563899:0.00188408:350475:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869715 ES:SE:LP:AF:SS:ID   0.00309795:0.00316443:0.484677:0.869715:350475:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00153227   ES:SE:LP:AF:SS:ID   0.0674135:0.0286266:1.7322:0.00153227:350475:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122936 ES:SE:LP:AF:SS:ID   -0.00390644:0.00313376:0.672523:0.122936:350475:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142738 ES:SE:LP:AF:SS:ID   -0.00239662:0.00309776:0.357406:0.142738:350475:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123053 ES:SE:LP:AF:SS:ID   -0.00384897:0.00312938:0.660117:0.123053:350475:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870851 ES:SE:LP:AF:SS:ID   0.00263846:0.00304946:0.412381:0.870851:350475:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87545  ES:SE:LP:AF:SS:ID   0.00346609:0.00310003:0.579167:0.87545:350475:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12867  ES:SE:LP:AF:SS:ID   -0.00329282:0.0030571:0.550623:0.12867:350475:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363378    ES:SE:LP:AF:SS:ID   0.00379832:0.00555041:0.306478:0.0363378:350475:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870444 ES:SE:LP:AF:SS:ID   0.0028517:0.00304626:0.45692:0.870444:350475:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870545 ES:SE:LP:AF:SS:ID   0.00282336:0.0030476:0.450717:0.870545:350475:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870439 ES:SE:LP:AF:SS:ID   0.00288685:0.00304613:0.464354:0.870439:350475:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504294   ES:SE:LP:AF:SS:ID   -0.00191437:0.0156485:0.0444888:0.00504294:350475:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500982   ES:SE:LP:AF:SS:ID   -0.00177525:0.0156902:0.0409982:0.00500982:350475:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558054   ES:SE:LP:AF:SS:ID   0.0111367:0.0151566:0.334908:0.00558054:350475:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870524 ES:SE:LP:AF:SS:ID   0.00258972:0.0030408:0.404058:0.870524:350475:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126014 ES:SE:LP:AF:SS:ID   -0.00344851:0.00310297:0.57444:0.126014:350475:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870086 ES:SE:LP:AF:SS:ID   0.00281176:0.00303347:0.451031:0.870086:350475:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869365 ES:SE:LP:AF:SS:ID   0.00281436:0.00303059:0.452138:0.869365:350475:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87024  ES:SE:LP:AF:SS:ID   0.00271991:0.00303609:0.431415:0.87024:350475:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870246 ES:SE:LP:AF:SS:ID   0.00272663:0.0030363:0.432759:0.870246:350475:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870255 ES:SE:LP:AF:SS:ID   0.00271075:0.0030364:0.429468:0.870255:350475:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870697 ES:SE:LP:AF:SS:ID   0.00279841:0.00304413:0.446179:0.870697:350475:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098838 ES:SE:LP:AF:SS:ID   -0.00479476:0.00353834:0.755993:0.098838:350475:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647154   ES:SE:LP:AF:SS:ID   0.00268193:0.0136931:0.0732872:0.00647154:350475:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874606 ES:SE:LP:AF:SS:ID   0.00359787:0.00308957:0.612229:0.874606:350475:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863994 ES:SE:LP:AF:SS:ID   0.00248942:0.00302977:0.385868:0.863994:350475:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869378 ES:SE:LP:AF:SS:ID   0.00256099:0.00305916:0.395227:0.869378:350475:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866337 ES:SE:LP:AF:SS:ID   0.0034181:0.00305987:0.578457:0.866337:350475:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098749 ES:SE:LP:AF:SS:ID   -0.0041628:0.00366432:0.591858:0.098749:350475:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87152  ES:SE:LP:AF:SS:ID   0.00369874:0.00309468:0.63449:0.87152:350475:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87152  ES:SE:LP:AF:SS:ID   0.00369844:0.00309468:0.634418:0.87152:350475:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871519 ES:SE:LP:AF:SS:ID   0.00369944:0.00309474:0.634637:0.871519:350475:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871891 ES:SE:LP:AF:SS:ID   0.00368511:0.00309649:0.630766:0.871891:350475:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125595 ES:SE:LP:AF:SS:ID   -0.00378822:0.00309895:0.65453:0.125595:350475:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105424 ES:SE:LP:AF:SS:ID   -0.00437085:0.00337418:0.709542:0.105424:350475:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855336 ES:SE:LP:AF:SS:ID   0.00293307:0.00302897:0.477718:0.855336:350475:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00164751   ES:SE:LP:AF:SS:ID   0.0281726:0.0269141:0.529866:0.00164751:350475:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838288 ES:SE:LP:AF:SS:ID   -0.00132177:0.00298361:0.181933:0.838288:350475:rs376645387