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-22612_0/ukb-d-22612_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-22612_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 16:34:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22612_0/ukb-d-22612_0.vcf.gz ...
Read summary statistics for 13563135 SNPs.
Dropped 12678 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: 0.0121 (0.0059)
Lambda GC: 1.0179
Mean Chi^2: 1.0151
Intercept: 0.9967 (0.0059)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:36:16 2019
Total time elapsed: 2.0m:6.62s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0161,
    "mean_EFFECT": -0,
    "n": 76334,
    "n_snps": 13563135,
    "n_clumped_hits": 0,
    "n_p_sig": 10,
    "n_mono": 0,
    "n_ns": 1251094,
    "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": 561979,
    "n_est": 76619.1643,
    "ratio_se_n": 1.0019,
    "mean_diff": -0,
    "ratio_diff": 21.1777,
    "sd_y_est1": 0.1646,
    "sd_y_est2": 0.1649,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0121,
    "ldsc_observed_scale_h2_se": 0.0059,
    "ldsc_intercept_beta": 0.9967,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0179,
    "ldsc_mean_chisq": 1.0151,
    "ldsc_ratio": -0.2185
}

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 13551121 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57041 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33327 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051407e+00 6.184887e+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 7.902503e+07 5.591709e+07 3.02000e+02 3.292828e+07 7.013418e+07 1.148629e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.000000e-05 4.912400e-03 -7.19551e-02 -1.265400e-03 2.590000e-05 1.344600e-03 6.487760e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.522100e-03 3.393700e-03 6.92600e-04 1.007000e-03 1.851700e-03 5.057500e-03 1.756980e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.974132e-01 2.891415e-01 0.00000e+00 2.460532e-01 4.965752e-01 7.478646e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.974111e-01 2.891428e-01 0.00000e+00 2.460488e-01 4.965732e-01 7.478637e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911160e-01 2.544860e-01 1.00000e-03 7.512700e-03 6.036090e-02 2.958520e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561979 0.9585657 NA NA NA NA NA 1.965598e-01 2.471529e-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 7.633400e+04 0.000000e+00 7.63340e+04 7.633400e+04 7.633400e+04 7.633400e+04 7.633400e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0003681 0.0014717 0.8024960 0.8024957 0.1114070 0.1894970 76334
1 693731 rs12238997 A G -0.0006668 0.0013939 0.6323929 0.6323907 0.1164820 0.1417730 76334
1 707522 rs371890604 G C -0.0000358 0.0015644 0.9817590 0.9817586 0.0981206 0.1293930 76334
1 717587 rs144155419 G A 0.0014209 0.0037554 0.7051589 0.7051581 0.0156164 0.0045926 76334
1 723329 rs189787166 A T -0.0062868 0.0106548 0.5551662 0.5551637 0.0018478 0.0003994 76334
1 730087 rs148120343 T C 0.0003580 0.0019324 0.8530151 0.8530148 0.0570106 0.0127796 76334
1 731718 rs142557973 T C -0.0000553 0.0013224 0.9666550 0.9666553 0.1223470 0.1543530 76334
1 732032 rs61770163 A C 0.0004385 0.0014105 0.7559151 0.7559147 0.1219760 0.1555510 76334
1 734349 rs141242758 T C -0.0000983 0.0013235 0.9407679 0.9407677 0.1215500 0.1525560 76334
1 740284 rs61770167 C T 0.0045130 0.0060596 0.4564098 0.4564076 0.0057764 0.0023962 76334
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0012571 0.0015480 0.4167552 0.4167531 0.0547925 0.0309934 76334
23 154923374 rs111332691 T A 0.0007536 0.0016750 0.6527712 0.6527694 0.0450848 0.0116556 76334
23 154925045 rs509981 C T -0.0003624 0.0008093 0.6542866 0.6542844 0.2446590 0.3634440 76334
23 154925895 rs538470 C T -0.0001266 0.0008274 0.8784339 0.8784332 0.2411030 0.3634440 76334
23 154927581 rs644138 G A -0.0000994 0.0007611 0.8961180 0.8961178 0.2998360 0.4635760 76334
23 154929412 rs557132 C T -0.0003066 0.0008095 0.7048878 0.7048873 0.2445300 0.3568210 76334
23 154929637 rs35185538 CT C 0.0002002 0.0008448 0.8126699 0.8126690 0.2290470 0.3011920 76334
23 154929952 rs4012982 CAA C -0.0002286 0.0008521 0.7884624 0.7884613 0.2384840 0.3165560 76334
23 154930230 rs781880 A G -0.0002141 0.0008092 0.7912979 0.7912968 0.2450070 0.3618540 76334
23 154930487 rs781879 T A 0.0018922 0.0027179 0.4863154 0.4863135 0.0200009 0.1263580 76334

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111407 ES:SE:LP:AF:SS:ID   0.000368097:0.00147169:0.0955571:0.111407:76334:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116482 ES:SE:LP:AF:SS:ID   -0.000666802:0.00139392:0.199013:0.116482:76334:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981206    ES:SE:LP:AF:SS:ID   -3.57698e-05:0.00156445:0.00799511:0.0981206:76334:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156164    ES:SE:LP:AF:SS:ID   0.00142093:0.00375543:0.151713:0.0156164:76334:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00184776   ES:SE:LP:AF:SS:ID   -0.00628676:0.0106548:0.255577:0.00184776:76334:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570106    ES:SE:LP:AF:SS:ID   0.000358031:0.00193245:0.0690433:0.0570106:76334:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122347 ES:SE:LP:AF:SS:ID   -5.52789e-05:0.00132235:0.0147285:0.122347:76334:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121976 ES:SE:LP:AF:SS:ID   0.000438457:0.00141051:0.121527:0.121976:76334:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12155  ES:SE:LP:AF:SS:ID   -9.83441e-05:0.00132352:0.0265175:0.12155:76334:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00577637   ES:SE:LP:AF:SS:ID   0.00451304:0.0060596:0.340645:0.00577637:76334:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00185131   ES:SE:LP:AF:SS:ID   -0.00970595:0.0114939:0.399656:0.00185131:76334:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869001 ES:SE:LP:AF:SS:ID   0.000111861:0.00130141:0.0308157:0.869001:76334:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.001592 ES:SE:LP:AF:SS:ID   0.0169682:0.011527:0.850744:0.001592:76334:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123648 ES:SE:LP:AF:SS:ID   0.000153223:0.00129042:0.0431202:0.123648:76334:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14313  ES:SE:LP:AF:SS:ID   -0.000124933:0.00127684:0.0352432:0.14313:76334:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123792 ES:SE:LP:AF:SS:ID   0.000182054:0.00128848:0.0517641:0.123792:76334:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869996 ES:SE:LP:AF:SS:ID   -0.000340883:0.00125585:0.104546:0.869996:76334:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87462  ES:SE:LP:AF:SS:ID   -0.000292338:0.00127586:0.0868391:0.87462:76334:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129439 ES:SE:LP:AF:SS:ID   0.000363117:0.00125982:0.111723:0.129439:76334:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0355805    ES:SE:LP:AF:SS:ID   -0.00316026:0.00230732:0.767522:0.0355805:76334:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869628 ES:SE:LP:AF:SS:ID   -0.000348924:0.00125473:0.107378:0.869628:76334:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869694 ES:SE:LP:AF:SS:ID   -0.000327496:0.00125522:0.100089:0.869694:76334:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869624 ES:SE:LP:AF:SS:ID   -0.000340658:0.00125468:0.104577:0.869624:76334:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00528577   ES:SE:LP:AF:SS:ID   0.00834315:0.00628586:0.734197:0.00528577:76334:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00525169   ES:SE:LP:AF:SS:ID   0.0082569:0.00630184:0.720972:0.00525169:76334:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00556743   ES:SE:LP:AF:SS:ID   -0.0105354:0.00623141:1.04143:0.00556743:76334:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869624 ES:SE:LP:AF:SS:ID   -0.000371486:0.00125228:0.115354:0.869624:76334:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126842 ES:SE:LP:AF:SS:ID   0.000238031:0.0012781:0.0694289:0.126842:76334:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869147 ES:SE:LP:AF:SS:ID   -0.000389741:0.00124907:0.12204:0.869147:76334:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868488 ES:SE:LP:AF:SS:ID   -0.00049901:0.00124801:0.161609:0.868488:76334:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869307 ES:SE:LP:AF:SS:ID   -0.000391548:0.00125022:0.122547:0.869307:76334:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869312 ES:SE:LP:AF:SS:ID   -0.000391024:0.0012503:0.122355:0.869312:76334:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869315 ES:SE:LP:AF:SS:ID   -0.000388991:0.00125031:0.121643:0.869315:76334:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869774 ES:SE:LP:AF:SS:ID   -0.000343641:0.00125353:0.105696:0.869774:76334:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0993775    ES:SE:LP:AF:SS:ID   0.000173709:0.00145697:0.0433054:0.0993775:76334:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00643986   ES:SE:LP:AF:SS:ID   -0.0115587:0.00565583:1.38733:0.00643986:76334:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873729 ES:SE:LP:AF:SS:ID   -0.00015576:0.00127162:0.044547:0.873729:76334:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863146 ES:SE:LP:AF:SS:ID   -0.00024838:0.00124768:0.0745822:0.863146:76334:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868565 ES:SE:LP:AF:SS:ID   -0.000307509:0.00126006:0.0930194:0.868565:76334:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865447 ES:SE:LP:AF:SS:ID   -0.000145523:0.00126017:0.0418831:0.865447:76334:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993259    ES:SE:LP:AF:SS:ID   0.000406133:0.00151038:0.103467:0.0993259:76334:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870674 ES:SE:LP:AF:SS:ID   2.93491e-05:0.0012741:0.00805572:0.870674:76334:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870674 ES:SE:LP:AF:SS:ID   2.9333e-05:0.0012741:0.00805129:0.870674:76334:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870671 ES:SE:LP:AF:SS:ID   2.93277e-05:0.00127411:0.00804952:0.870671:76334:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871043 ES:SE:LP:AF:SS:ID   7.57968e-05:0.00127477:0.0210954:0.871043:76334:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126455 ES:SE:LP:AF:SS:ID   0.000181956:0.0012764:0.0522512:0.126455:76334:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106136 ES:SE:LP:AF:SS:ID   -0.000216905:0.00138769:0.0575995:0.106136:76334:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854487 ES:SE:LP:AF:SS:ID   -0.000501961:0.00124736:0.162804:0.854487:76334:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00176068   ES:SE:LP:AF:SS:ID   -0.00586892:0.0106748:0.234732:0.00176068:76334:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839351 ES:SE:LP:AF:SS:ID   -0.000317947:0.00123183:0.0989102:0.839351:76334:rs376645387