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-680_1/ukb-d-680_1.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-680_1/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 17:18:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-680_1/ukb-d-680_1.vcf.gz ...
Read summary statistics for 13586422 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: 0.0326 (0.0018)
Lambda GC: 1.2065
Mean Chi^2: 1.2317
Intercept: 1.0067 (0.0073)
Ratio: 0.029 (0.0315)
Analysis finished at Mon Nov 25 17:20:31 2019
Total time elapsed: 2.0m:19.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1243,
    "mean_EFFECT": -0,
    "n": 356340,
    "n_snps": 13586422,
    "n_clumped_hits": 3,
    "n_p_sig": 12,
    "n_mono": 0,
    "n_ns": 1251804,
    "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": 569270,
    "n_est": 357695.6015,
    "ratio_se_n": 1.0019,
    "mean_diff": -0,
    "ratio_diff": 135.2716,
    "sd_y_est1": 0.4313,
    "sd_y_est2": 0.4321,
    "r2_sum1": 0,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0326,
    "ldsc_observed_scale_h2_se": 0.0018,
    "ldsc_intercept_beta": 1.0067,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.2065,
    "ldsc_mean_chisq": 1.2317,
    "ldsc_ratio": 0.0289
}

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 13574376 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57082 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33338 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051366e+00 6.184982e+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 7.902493e+07 5.591491e+07 3.02000e+02 3.293086e+07 7.013794e+07 1.148588e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.510000e-05 6.048600e-03 -7.14134e-02 -1.715100e-03 -2.080000e-05 1.680400e-03 8.667640e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 4.293100e-03 4.141200e-03 8.40100e-04 1.222200e-03 2.252400e-03 6.169800e-03 2.079770e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.806989e-01 2.937534e-01 0.00000e+00 2.217773e-01 4.744910e-01 7.346018e-01 1.000000e+00 ▇▇▇▇▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.806984e-01 2.937537e-01 0.00000e+00 2.217759e-01 4.744905e-01 7.346013e-01 1.000000e+00 ▇▇▇▇▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908044e-01 2.544032e-01 1.00000e-03 7.429700e-03 6.003140e-02 2.953050e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569270 0.9581001 NA NA NA NA NA 1.963353e-01 2.471016e-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 3.563400e+05 0.000000e+00 3.56340e+05 3.563400e+05 3.563400e+05 3.563400e+05 3.563400e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0028384 0.0017892 0.1126510 0.1126504 0.1106480 0.1894970 356340
1 693731 rs12238997 A G 0.0024431 0.0016910 0.1485330 0.1485331 0.1157970 0.1417730 356340
1 707522 rs371890604 G C 0.0007378 0.0019010 0.6979077 0.6979080 0.0972849 0.1293930 356340
1 717587 rs144155419 G A 0.0119563 0.0045358 0.0083902 0.0083899 0.0156800 0.0045926 356340
1 723329 rs189787166 A T 0.0080416 0.0133297 0.5463224 0.5463220 0.0017455 0.0003994 356340
1 730087 rs148120343 T C -0.0002278 0.0023555 0.9229541 0.9229544 0.0564590 0.0127796 356340
1 731718 rs142557973 T C 0.0013865 0.0016036 0.3872380 0.3872362 0.1217310 0.1543530 356340
1 732032 rs61770163 A C 0.0007207 0.0017106 0.6735332 0.6735334 0.1211470 0.1555510 356340
1 734349 rs141242758 T C 0.0013996 0.0016045 0.3830240 0.3830241 0.1209580 0.1525560 356340
1 740284 rs61770167 C T -0.0023886 0.0073251 0.7443668 0.7443658 0.0058056 0.0023962 356340
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0021319 0.0018515 0.2495520 0.2495509 0.0562156 0.0309934 356340
23 154923374 rs111332691 T A -0.0015441 0.0020358 0.4481558 0.4481580 0.0448027 0.0116556 356340
23 154925045 rs509981 C T 0.0006349 0.0009798 0.5169886 0.5169889 0.2454610 0.3634440 356340
23 154925895 rs538470 C T 0.0005918 0.0010023 0.5549349 0.5549330 0.2417790 0.3634440 356340
23 154927581 rs644138 G A 0.0010229 0.0009214 0.2668990 0.2668975 0.3020610 0.4635760 356340
23 154929412 rs557132 C T 0.0005988 0.0009801 0.5412202 0.5412197 0.2453120 0.3568210 356340
23 154929637 rs35185538 CT C -0.0000999 0.0010229 0.9221690 0.9221686 0.2295890 0.3011920 356340
23 154929952 rs4012982 CAA C 0.0006090 0.0010308 0.5546832 0.5546820 0.2392680 0.3165560 356340
23 154930230 rs781880 A G 0.0006118 0.0009800 0.5324330 0.5324329 0.2457230 0.3618540 356340
23 154930487 rs781879 T A -0.0002440 0.0033633 0.9421690 0.9421686 0.0195351 0.1263580 356340

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110648 ES:SE:LP:AF:SS:ID   0.00283842:0.00178923:0.948265:0.110648:356340:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115797 ES:SE:LP:AF:SS:ID   0.0024431:0.00169104:0.828177:0.115797:356340:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972849    ES:SE:LP:AF:SS:ID   0.00073785:0.00190096:0.156202:0.0972849:356340:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.01568  ES:SE:LP:AF:SS:ID   0.0119563:0.00453584:2.07623:0.01568:356340:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00174548   ES:SE:LP:AF:SS:ID   0.00804155:0.0133297:0.262551:0.00174548:356340:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056459 ES:SE:LP:AF:SS:ID   -0.00022781:0.00235553:0.0348199:0.056459:356340:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121731 ES:SE:LP:AF:SS:ID   0.00138652:0.00160358:0.412022:0.121731:356340:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121147 ES:SE:LP:AF:SS:ID   0.000720682:0.0017106:0.171641:0.121147:356340:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120958 ES:SE:LP:AF:SS:ID   0.00139964:0.00160447:0.416774:0.120958:356340:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0058056    ES:SE:LP:AF:SS:ID   -0.00238855:0.0073251:0.128213:0.0058056:356340:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187615   ES:SE:LP:AF:SS:ID   0.00590476:0.0138675:0.17376:0.00187615:356340:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869751 ES:SE:LP:AF:SS:ID   -0.00105102:0.00158181:0.295499:0.869751:356340:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152269   ES:SE:LP:AF:SS:ID   0.0219153:0.0143561:0.896631:0.00152269:356340:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122921 ES:SE:LP:AF:SS:ID   0.00049765:0.00156645:0.124523:0.122921:356340:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142704 ES:SE:LP:AF:SS:ID   0.000644243:0.00154838:0.169183:0.142704:356340:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123036 ES:SE:LP:AF:SS:ID   0.000540785:0.00156427:0.136938:0.123036:356340:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870892 ES:SE:LP:AF:SS:ID   -0.000532613:0.00152432:0.138596:0.870892:356340:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875468 ES:SE:LP:AF:SS:ID   -0.000445981:0.00154961:0.111541:0.875468:356340:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   0.000597843:0.00152812:0.157622:0.128631:356340:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363599    ES:SE:LP:AF:SS:ID   -1.57935e-05:0.00277205:0.0019788:0.0363599:356340:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870484 ES:SE:LP:AF:SS:ID   -0.000558173:0.00152273:0.146335:0.870484:356340:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870586 ES:SE:LP:AF:SS:ID   -0.000535685:0.0015234:0.139596:0.870586:356340:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870482 ES:SE:LP:AF:SS:ID   -0.000542613:0.00152267:0.141719:0.870482:356340:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504061   ES:SE:LP:AF:SS:ID   -0.00537896:0.00781925:0.308469:0.00504061:356340:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500754   ES:SE:LP:AF:SS:ID   -0.00525685:0.0078402:0.298829:0.00500754:356340:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00555675   ES:SE:LP:AF:SS:ID   0.00151623:0.00759169:0.0748437:0.00555675:356340:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870565 ES:SE:LP:AF:SS:ID   -0.00052325:0.00151999:0.136283:0.870565:356340:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125983 ES:SE:LP:AF:SS:ID   0.0006605:0.00155099:0.173788:0.125983:356340:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870131 ES:SE:LP:AF:SS:ID   -0.000462677:0.00151635:0.119032:0.870131:356340:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869417 ES:SE:LP:AF:SS:ID   -0.000545646:0.00151495:0.143442:0.869417:356340:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   -0.000537771:0.00151767:0.140811:0.870287:356340:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870293 ES:SE:LP:AF:SS:ID   -0.000536352:0.00151778:0.14038:0.870293:356340:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870301 ES:SE:LP:AF:SS:ID   -0.000538398:0.00151782:0.140981:0.870301:356340:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870742 ES:SE:LP:AF:SS:ID   -0.000601949:0.00152167:0.159636:0.870742:356340:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988331    ES:SE:LP:AF:SS:ID   0.000277487:0.00176843:0.0578356:0.0988331:356340:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00645051   ES:SE:LP:AF:SS:ID   0.0106933:0.0068538:0.925494:0.00645051:356340:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87464  ES:SE:LP:AF:SS:ID   -0.000918785:0.0015444:0.258138:0.87464:356340:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864041 ES:SE:LP:AF:SS:ID   -0.000865157:0.00151449:0.245782:0.864041:356340:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869434 ES:SE:LP:AF:SS:ID   -0.000569012:0.00152923:0.148848:0.869434:356340:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866374 ES:SE:LP:AF:SS:ID   -0.0003549:0.0015295:0.0880385:0.866374:356340:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098777 ES:SE:LP:AF:SS:ID   0.00186425:0.00183128:0.510494:0.098777:356340:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   -0.000726757:0.00154696:0.194838:0.87156:356340:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   -0.000726798:0.00154696:0.194851:0.87156:356340:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   -0.000732354:0.00154699:0.196595:0.87156:356340:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871936 ES:SE:LP:AF:SS:ID   -0.000729136:0.00154787:0.195451:0.871936:356340:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12556  ES:SE:LP:AF:SS:ID   0.000832296:0.00154906:0.228363:0.12556:356340:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10543  ES:SE:LP:AF:SS:ID   -0.000473512:0.00168634:0.108536:0.10543:356340:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855374 ES:SE:LP:AF:SS:ID   -0.000948856:0.00151387:0.275064:0.855374:356340:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00166613   ES:SE:LP:AF:SS:ID   0.00345075:0.0133582:0.0990013:0.00166613:356340:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838431 ES:SE:LP:AF:SS:ID   -4.1572e-05:0.00149174:0.00976462:0.838431:356340:rs376645387