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-30850_irnt/ukb-d-30850_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-30850_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 15:00:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30850_irnt/ukb-d-30850_irnt.vcf.gz ...
Read summary statistics for 13585068 SNPs.
Dropped 12707 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, 1283501 SNPs remain.
After merging with regression SNP LD, 1283501 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0725 (0.0108)
Lambda GC: 1.2584
Mean Chi^2: 1.4895
Intercept: 1.0455 (0.0108)
Ratio: 0.0929 (0.022)
Analysis finished at Mon Nov 25 15:03:15 2019
Total time elapsed: 2.0m:50.85s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1668,
    "mean_EFFECT": 7.6881e-07,
    "n": 312102,
    "n_snps": 13585068,
    "n_clumped_hits": 100,
    "n_p_sig": 17462,
    "n_mono": 0,
    "n_ns": 1251749,
    "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": 568966,
    "n_est": 313518.5109,
    "ratio_se_n": 1.0023,
    "mean_diff": 1.7719e-06,
    "ratio_diff": 1.3929,
    "sd_y_est1": 0.6046,
    "sd_y_est2": 0.606,
    "r2_sum1": 0.0099,
    "r2_sum2": 0.0271,
    "r2_sum3": 0.027,
    "r2_sum4": 0.027,
    "ldsc_nsnp_merge_refpanel_ld": 1283501,
    "ldsc_nsnp_merge_regression_ld": 1283501,
    "ldsc_observed_scale_h2_beta": 0.0725,
    "ldsc_observed_scale_h2_se": 0.0108,
    "ldsc_intercept_beta": 1.0455,
    "ldsc_intercept_se": 0.0108,
    "ldsc_lambda_gc": 1.2584,
    "ldsc_mean_chisq": 1.4895,
    "ldsc_ratio": 0.093
}
 

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 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 13573025 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 9.051273e+00 6.184938e+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 7.902581e+07 5.591529e+07 3.02000e+02 3.293089e+07 7.013920e+07 1.148611e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 8.000000e-07 9.153500e-03 -2.36230e-01 -2.628900e-03 -1.740000e-05 2.601800e-03 1.539200e-01 ▁▁▃▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 6.429400e-03 6.202400e-03 1.24080e-03 1.831000e-03 3.373600e-03 9.237400e-03 3.147200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.738794e-01 2.969519e-01 0.00000e+00 2.101701e-01 4.662598e-01 7.315803e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.738789e-01 2.969521e-01 0.00000e+00 2.101743e-01 4.662623e-01 7.315826e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908226e-01 2.544084e-01 1.00000e-03 7.433500e-03 6.005700e-02 2.953400e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568966 0.9581183 NA NA NA NA NA 1.963496e-01 2.471053e-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 3.121020e+05 0.000000e+00 3.12102e+05 3.121020e+05 3.121020e+05 3.121020e+05 3.121020e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0017549 0.0026812 0.5127705 0.5127766 0.1105700 0.1894970 312102
1 693731 rs12238997 A G -0.0033314 0.0025331 0.1884799 0.1884604 0.1157900 0.1417730 312102
1 707522 rs371890604 G C -0.0023829 0.0028490 0.4029304 0.4029306 0.0972050 0.1293930 312102
1 717587 rs144155419 G A -0.0089468 0.0068035 0.1884998 0.1885001 0.0156560 0.0045926 312102
1 723329 rs189787166 A T 0.0283040 0.0201950 0.1610601 0.1610541 0.0017138 0.0003994 312102
1 730087 rs148120343 T C 0.0027032 0.0035281 0.4435596 0.4435624 0.0565080 0.0127796 312102
1 731718 rs142557973 T C -0.0024313 0.0024019 0.3114204 0.3114232 0.1217200 0.1543530 312102
1 732032 rs61770163 A C -0.0030546 0.0025630 0.2333399 0.2333371 0.1211100 0.1555510 312102
1 734349 rs141242758 T C -0.0024159 0.0024031 0.3147502 0.3147397 0.1209500 0.1525560 312102
1 740284 rs61770167 C T -0.0109680 0.0110340 0.3201998 0.3202139 0.0057506 0.0023962 312102
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0022680 0.0027370 0.4073099 0.4073056 0.056136 0.0309934 312102
23 154923374 rs111332691 T A -0.0011677 0.0030096 0.6980299 0.6980221 0.044702 0.0116556 312102
23 154925045 rs509981 C T 0.0036232 0.0014462 0.0122360 0.0122339 0.245850 0.3634440 312102
23 154925895 rs538470 C T 0.0039164 0.0014794 0.0081130 0.0081140 0.242170 0.3634440 312102
23 154927581 rs644138 G A 0.0036977 0.0013601 0.0065544 0.0065540 0.302350 0.4635760 312102
23 154929412 rs557132 C T 0.0035871 0.0014466 0.0131519 0.0131502 0.245700 0.3568210 312102
23 154929637 rs35185538 CT C 0.0034802 0.0015094 0.0211329 0.0211283 0.230090 0.3011920 312102
23 154929952 rs4012982 CAA C 0.0041165 0.0015212 0.0068097 0.0068081 0.239690 0.3165560 312102
23 154930230 rs781880 A G 0.0035981 0.0014464 0.0128609 0.0128599 0.246100 0.3618540 312102
23 154930487 rs781879 T A -0.0006308 0.0049571 0.8987500 0.8987459 0.019591 0.1263580 312102

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11057  ES:SE:LP:AF:SS:ID   -0.0017549:0.0026812:0.290077:0.11057:312102:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11579  ES:SE:LP:AF:SS:ID   -0.0033314:0.0025331:0.724735:0.11579:312102:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097205 ES:SE:LP:AF:SS:ID   -0.0023829:0.002849:0.39477:0.097205:312102:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015656 ES:SE:LP:AF:SS:ID   -0.0089468:0.0068035:0.724689:0.015656:312102:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017138    ES:SE:LP:AF:SS:ID   0.028304:0.020195:0.793012:0.0017138:312102:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056508 ES:SE:LP:AF:SS:ID   0.0027032:0.0035281:0.353048:0.056508:312102:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12172  ES:SE:LP:AF:SS:ID   -0.0024313:0.0024019:0.506653:0.12172:312102:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12111  ES:SE:LP:AF:SS:ID   -0.0030546:0.002563:0.632011:0.12111:312102:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12095  ES:SE:LP:AF:SS:ID   -0.0024159:0.0024031:0.502034:0.12095:312102:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057506    ES:SE:LP:AF:SS:ID   -0.010968:0.011034:0.494579:0.0057506:312102:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018642    ES:SE:LP:AF:SS:ID   -0.003128:0.020892:0.055034:0.0018642:312102:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86987  ES:SE:LP:AF:SS:ID   0.0023833:0.0023698:0.502297:0.86987:312102:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015184    ES:SE:LP:AF:SS:ID   -0.0011049:0.021524:0.0181542:0.0015184:312102:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12283  ES:SE:LP:AF:SS:ID   -0.001904:0.0023466:0.379718:0.12283:312102:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14265  ES:SE:LP:AF:SS:ID   -0.0021154:0.0023195:0.441591:0.14265:312102:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12294  ES:SE:LP:AF:SS:ID   -0.0018768:0.0023434:0.373454:0.12294:312102:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87099  ES:SE:LP:AF:SS:ID   0.0018315:0.0022836:0.374142:0.87099:312102:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87559  ES:SE:LP:AF:SS:ID   0.0017244:0.0023217:0.339457:0.87559:312102:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12856  ES:SE:LP:AF:SS:ID   -0.0018593:0.0022891:0.380229:0.12856:312102:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036378 ES:SE:LP:AF:SS:ID   0.00035823:0.0041532:0.0309291:0.036378:312102:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87058  ES:SE:LP:AF:SS:ID   0.0018996:0.0022812:0.392545:0.87058:312102:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87069  ES:SE:LP:AF:SS:ID   0.0018261:0.0022823:0.373013:0.87069:312102:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87058  ES:SE:LP:AF:SS:ID   0.0019594:0.0022811:0.408524:0.87058:312102:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050665    ES:SE:LP:AF:SS:ID   -0.0019225:0.011682:0.0608403:0.0050665:312102:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050345    ES:SE:LP:AF:SS:ID   -0.0015086:0.011713:0.0469607:0.0050345:312102:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055257    ES:SE:LP:AF:SS:ID   0.0096566:0.011407:0.400925:0.0055257:312102:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87067  ES:SE:LP:AF:SS:ID   0.0020369:0.0022772:0.430556:0.87067:312102:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12589  ES:SE:LP:AF:SS:ID   -0.002111:0.0023235:0.4394:0.12589:312102:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87024  ES:SE:LP:AF:SS:ID   0.0019515:0.0022718:0.408568:0.87024:312102:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86952  ES:SE:LP:AF:SS:ID   0.0020397:0.0022696:0.433186:0.86952:312102:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87039  ES:SE:LP:AF:SS:ID   0.001956:0.0022737:0.409359:0.87039:312102:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.8704   ES:SE:LP:AF:SS:ID   0.0019565:0.0022738:0.409437:0.8704:312102:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   0.0019554:0.0022739:0.409125:0.87041:312102:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87085  ES:SE:LP:AF:SS:ID   0.0021521:0.0022797:0.461992:0.87085:312102:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098704 ES:SE:LP:AF:SS:ID   -0.001747:0.0026505:0.292583:0.098704:312102:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064042    ES:SE:LP:AF:SS:ID   0.0080825:0.01031:0.363422:0.0064042:312102:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87478  ES:SE:LP:AF:SS:ID   0.001918:0.0023141:0.390182:0.87478:312102:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86413  ES:SE:LP:AF:SS:ID   0.0018329:0.0022692:0.377537:0.86413:312102:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86954  ES:SE:LP:AF:SS:ID   0.0022803:0.002291:0.495434:0.86954:312102:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86646  ES:SE:LP:AF:SS:ID   0.0021233:0.0022914:0.450862:0.86646:312102:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098633 ES:SE:LP:AF:SS:ID   -0.0019081:0.0027439:0.312641:0.098633:312102:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   0.0017615:0.0023178:0.34943:0.87167:312102:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   0.0017614:0.0023178:0.349411:0.87167:312102:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   0.0017497:0.0023179:0.346459:0.87167:312102:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87205  ES:SE:LP:AF:SS:ID   0.0017658:0.0023192:0.350256:0.87205:312102:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12545  ES:SE:LP:AF:SS:ID   -0.0019857:0.0023208:0.40647:0.12545:312102:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10535  ES:SE:LP:AF:SS:ID   -0.0016832:0.0025272:0.296382:0.10535:312102:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85548  ES:SE:LP:AF:SS:ID   0.0019828:0.0022684:0.41788:0.85548:312102:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016292    ES:SE:LP:AF:SS:ID   0.026145:0.020261:0.705754:0.0016292:312102:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83851  ES:SE:LP:AF:SS:ID   -0.00044722:0.0022345:0.075013:0.83851:312102:rs376645387