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-30610_irnt/ukb-d-30610_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-30610_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 15:35:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30610_irnt/ukb-d-30610_irnt.vcf.gz ...
Read summary statistics for 13586005 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: 0.2473 (0.0495)
Lambda GC: 1.5571
Mean Chi^2: 2.8282
Intercept: 1.1616 (0.0212)
Ratio: 0.0884 (0.0116)
Analysis finished at Mon Nov 25 15:37:48 2019
Total time elapsed: 2.0m:17.25s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3508,
    "mean_EFFECT": 0.0001,
    "n": 344292,
    "n_snps": 13586005,
    "n_clumped_hits": 316,
    "n_p_sig": 74112,
    "n_mono": 0,
    "n_ns": 1251780,
    "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": 569170,
    "n_est": 345627.5148,
    "ratio_se_n": 1.0019,
    "mean_diff": -6.4896e-07,
    "ratio_diff": 0.2641,
    "sd_y_est1": 0.9687,
    "sd_y_est2": 0.9706,
    "r2_sum1": 0.1169,
    "r2_sum2": 0.1245,
    "r2_sum3": 0.1241,
    "r2_sum4": 0.124,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.2473,
    "ldsc_observed_scale_h2_se": 0.0495,
    "ldsc_intercept_beta": 1.1616,
    "ldsc_intercept_se": 0.0212,
    "ldsc_lambda_gc": 1.5571,
    "ldsc_mean_chisq": 2.8282,
    "ldsc_ratio": 0.0884
}

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 13573959 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57081 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 9.051218e+00 6.184966e+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 7.902588e+07 5.591529e+07 3.02000e+02 3.293109e+07 7.013966e+07 1.148605e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.960000e-05 1.483190e-02 -9.08960e-01 -4.358500e-03 2.540000e-05 4.420100e-03 1.105200e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.809500e-03 9.462400e-03 1.91930e-03 2.792900e-03 5.146600e-03 1.409700e-02 4.779900e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.499070e-01 3.037350e-01 0.00000e+00 1.739498e-01 4.330799e-01 7.138698e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.499065e-01 3.037352e-01 0.00000e+00 1.739498e-01 4.330753e-01 7.138663e-01 1.000000e+00 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908098e-01 2.544045e-01 1.00000e-03 7.431300e-03 6.004000e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569170 0.9581062 NA NA NA NA NA 1.963392e-01 2.471027e-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 3.442920e+05 0.000000e+00 3.44292e+05 3.442920e+05 3.442920e+05 3.442920e+05 3.442920e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0021941 0.0040889 0.5915398 0.5915446 0.1105200 0.1894970 344292
1 693731 rs12238997 A G 0.0011516 0.0038618 0.7655402 0.7655483 0.1158000 0.1417730 344292
1 707522 rs371890604 G C -0.0005641 0.0043438 0.8966699 0.8966673 0.0972390 0.1293930 344292
1 717587 rs144155419 G A -0.0157190 0.0103690 0.1295299 0.1295292 0.0156620 0.0045926 344292
1 723329 rs189787166 A T -0.0072696 0.0305310 0.8117999 0.8117992 0.0017376 0.0003994 344292
1 730087 rs148120343 T C -0.0008613 0.0053821 0.8728500 0.8728512 0.0564260 0.0127796 344292
1 731718 rs142557973 T C -0.0001651 0.0036627 0.9640401 0.9640380 0.1216900 0.1543530 344292
1 732032 rs61770163 A C -0.0011110 0.0039084 0.7762096 0.7762115 0.1211000 0.1555510 344292
1 734349 rs141242758 T C -0.0000533 0.0036647 0.9883900 0.9883900 0.1209200 0.1525560 344292
1 740284 rs61770167 C T 0.0243160 0.0168110 0.1480601 0.1480555 0.0057552 0.0023962 344292
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0063332 0.0042331 0.1346300 0.1346240 0.056174 0.0309934 344292
23 154923374 rs111332691 T A -0.0002445 0.0046454 0.9580201 0.9580177 0.044882 0.0116556 344292
23 154925045 rs509981 C T -0.0058296 0.0022379 0.0091895 0.0091890 0.245660 0.3634440 344292
23 154925895 rs538470 C T -0.0054552 0.0022893 0.0171759 0.0171763 0.241990 0.3634440 344292
23 154927581 rs644138 G A -0.0066455 0.0021047 0.0015917 0.0015915 0.302220 0.4635760 344292
23 154929412 rs557132 C T -0.0057205 0.0022385 0.0106050 0.0106034 0.245520 0.3568210 344292
23 154929637 rs35185538 CT C -0.0049939 0.0023364 0.0325657 0.0325627 0.229770 0.3011920 344292
23 154929952 rs4012982 CAA C -0.0060524 0.0023543 0.0101471 0.0101468 0.239490 0.3165560 344292
23 154930230 rs781880 A G -0.0055480 0.0022382 0.0131859 0.0131833 0.245920 0.3618540 344292
23 154930487 rs781879 T A -0.0145570 0.0076723 0.0577817 0.0577824 0.019563 0.1263580 344292

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11052  ES:SE:LP:AF:SS:ID   -0.0021941:0.0040889:0.228016:0.11052:344292:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.1158   ES:SE:LP:AF:SS:ID   0.0011516:0.0038618:0.116032:0.1158:344292:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097239 ES:SE:LP:AF:SS:ID   -0.00056414:0.0043438:0.0473674:0.097239:344292:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015662 ES:SE:LP:AF:SS:ID   -0.015719:0.010369:0.88763:0.015662:344292:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017376    ES:SE:LP:AF:SS:ID   -0.0072696:0.030531:0.090551:0.0017376:344292:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056426 ES:SE:LP:AF:SS:ID   -0.00086134:0.0053821:0.0590604:0.056426:344292:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12169  ES:SE:LP:AF:SS:ID   -0.00016514:0.0036627:0.0159049:0.12169:344292:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.1211   ES:SE:LP:AF:SS:ID   -0.001111:0.0039084:0.110021:0.1211:344292:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12092  ES:SE:LP:AF:SS:ID   -5.3327e-05:0.0036647:0.00507166:0.12092:344292:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057552    ES:SE:LP:AF:SS:ID   0.024316:0.016811:0.829562:0.0057552:344292:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018601    ES:SE:LP:AF:SS:ID   0.0033093:0.031881:0.0374744:0.0018601:344292:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86981  ES:SE:LP:AF:SS:ID   0.0011818:0.0036131:0.128655:0.86981:344292:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015207    ES:SE:LP:AF:SS:ID   -0.04385:0.032826:0.74086:0.0015207:344292:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12287  ES:SE:LP:AF:SS:ID   -0.00012376:0.003578:0.0121506:0.12287:344292:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14269  ES:SE:LP:AF:SS:ID   -0.00082074:0.0035362:0.0880651:0.14269:344292:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   -3.9739e-05:0.0035729:0.00386938:0.12299:344292:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87097  ES:SE:LP:AF:SS:ID   0.00058111:0.0034823:0.0617455:0.87097:344292:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87553  ES:SE:LP:AF:SS:ID   0.00031657:0.0035396:0.0321105:0.87553:344292:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12857  ES:SE:LP:AF:SS:ID   -0.00042242:0.0034908:0.0439805:0.12857:344292:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036312 ES:SE:LP:AF:SS:ID   -0.0018291:0.0063384:0.111871:0.036312:344292:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.00040054:0.0034786:0.0417563:0.87056:344292:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   0.00038364:0.0034803:0.0398956:0.87066:344292:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.00040491:0.0034785:0.0422347:0.87056:344292:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050514    ES:SE:LP:AF:SS:ID   -0.013231:0.017837:0.338916:0.0050514:344292:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050184    ES:SE:LP:AF:SS:ID   -0.012789:0.017885:0.323727:0.0050184:344292:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.005546 ES:SE:LP:AF:SS:ID   -0.023485:0.017362:0.754093:0.005546:344292:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   0.00085607:0.0034725:0.0940585:0.87064:344292:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   -0.00058864:0.003543:0.0614603:0.12592:344292:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   0.00113:0.0034643:0.128264:0.87021:344292:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   0.00081931:0.0034611:0.0899789:0.86949:344292:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   0.0010101:0.0034671:0.113053:0.87036:344292:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.0010098:0.0034674:0.113019:0.87037:344292:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   0.00098238:0.0034675:0.109613:0.87038:344292:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87082  ES:SE:LP:AF:SS:ID   0.00082843:0.0034763:0.0906366:0.87082:344292:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098782 ES:SE:LP:AF:SS:ID   0.00015125:0.0040403:0.0131656:0.098782:344292:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064315    ES:SE:LP:AF:SS:ID   -0.01767:0.015686:0.58506:0.0064315:344292:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.8747   ES:SE:LP:AF:SS:ID   0.00029294:0.0035278:0.0297368:0.8747:344292:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86411  ES:SE:LP:AF:SS:ID   0.000687:0.0034603:0.0743682:0.86411:344292:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.00096238:0.0034932:0.106277:0.8695:344292:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.00060918:0.0034939:0.0646994:0.86644:344292:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098737 ES:SE:LP:AF:SS:ID   -0.00010784:0.0041826:0.0090266:0.098737:344292:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   -3.6283e-05:0.0035339:0.00357152:0.87162:344292:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   -3.6168e-05:0.0035339:0.00356276:0.87162:344292:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   -3.2761e-05:0.003534:0.00322573:0.87162:344292:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87199  ES:SE:LP:AF:SS:ID   2.6394e-05:0.0035359:0.00259614:0.87199:344292:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12551  ES:SE:LP:AF:SS:ID   -0.00034631:0.0035384:0.0352549:0.12551:344292:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   0.0018304:0.0038529:0.197411:0.10539:344292:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85546  ES:SE:LP:AF:SS:ID   5.156e-05:0.0034588:0.00519471:0.85546:344292:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016564    ES:SE:LP:AF:SS:ID   -0.0053686:0.030608:0.0651129:0.0016564:344292:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83827  ES:SE:LP:AF:SS:ID   -0.0031352:0.0034059:0.446955:0.83827:344292:rs376645387