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/public/UKB-b-16407/UKB-b-16407_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16407/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16407/UKB-b-16407_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1955 (0.0054)
Lambda GC: 2.2843
Mean Chi^2: 2.9604
Intercept: 1.1859 (0.0169)
Ratio: 0.0948 (0.0086)
Analysis finished at Thu Oct 17 14:46:47 2019
Total time elapsed: 1.0m:46.03s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.8418,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 389,
    "n_p_sig": 49879,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 184849,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.1955,
    "ldsc_observed_scale_h2_se": 0.0054,
    "ldsc_intercept_beta": 1.1859,
    "ldsc_intercept_se": 0.0169,
    "ldsc_lambda_gc": 2.2843,
    "ldsc_mean_chisq": 2.9604,
    "ldsc_ratio": 0.0948
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 9837196 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9851866 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.622825e+00 5.748290e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.590000e-05 9.957200e-03 -0.2410150 -3.754700e-03 2.090000e-05 3.781000e-03 1.446640e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.377800e-03 6.036500e-03 0.0017828 2.184900e-03 3.663800e-03 8.453400e-03 9.375230e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.043193e-01 3.105679e-01 0.0000000 1.100001e-01 3.599996e-01 6.700003e-01 1.000000e+00 ▇▅▅▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.043219e-01 3.105466e-01 0.0000000 1.117094e-01 3.636476e-01 6.711201e-01 1.000000e+00 ▇▅▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568614e-01 0.0009840 1.316900e-02 7.791400e-02 3.164540e-01 9.990060e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0005068 0.0032761 0.8800001 0.8770663 0.623737 0.7821490 NA
1 54676 rs2462492 C T 0.0007399 0.0032462 0.8200001 0.8196890 0.400358 NA NA
1 86028 rs114608975 T C 0.0089033 0.0051895 0.0860003 0.0862304 0.103553 0.0277556 NA
1 91536 rs6702460 G T -0.0006205 0.0031957 0.8499999 0.8460467 0.456857 0.4207270 NA
1 234313 rs8179466 C T -0.0068988 0.0063035 0.2700001 0.2737557 0.074496 NA NA
1 534192 rs6680723 C T 0.0023303 0.0036507 0.5199996 0.5232645 0.240937 NA NA
1 546697 rs12025928 A G -0.0011591 0.0045541 0.8000000 0.7990908 0.913461 NA NA
1 693731 rs12238997 A G 0.0003363 0.0030611 0.9100000 0.9125092 0.116204 0.1417730 NA
1 705882 rs72631875 G A 0.0026880 0.0044818 0.5500004 0.5486627 0.067327 0.0315495 NA
1 706368 rs55727773 A G 0.0021652 0.0022666 0.3400001 0.3394398 0.515781 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0039690 0.0047792 0.4100001 0.4062734 0.041971 0.0473243 NA
22 51219766 rs182321900 C T -0.0124521 0.0222399 0.5800000 0.5755483 0.001943 NA NA
22 51220146 rs868950473 C T -0.0170886 0.0220281 0.4400003 0.4378885 0.001992 NA NA
22 51221190 rs369304721 G A 0.0051194 0.0047707 0.2800000 0.2832298 0.049763 NA NA
22 51221731 rs115055839 T C 0.0048536 0.0035687 0.1700000 0.1738195 0.073281 0.0625000 NA
22 51222100 rs114553188 G T -0.0011017 0.0042017 0.7899998 0.7931582 0.054486 0.0880591 NA
22 51223637 rs375798137 G A -0.0009300 0.0042220 0.8300000 0.8256576 0.054116 0.0788738 NA
22 51229805 rs9616985 T C 0.0046363 0.0035816 0.2000000 0.1955068 0.073114 0.0730831 NA
22 51232488 rs376461333 A G 0.0037117 0.0084366 0.6600001 0.6599738 0.020053 NA NA
22 51237063 rs3896457 T C 0.0031242 0.0021917 0.1499999 0.1540274 0.297907 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623737 ES:SE:LP:AF:ID  -0.000506773:0.00327607:0.0555173:0.623737:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400358 ES:SE:LP:AF:ID  0.000739946:0.00324616:0.0861861:0.400358:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103553 ES:SE:LP:AF:ID  0.00890328:0.00518952:1.0655:0.103553:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456857 ES:SE:LP:AF:ID  -0.000620489:0.00319568:0.0705811:0.456857:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074496 ES:SE:LP:AF:ID  -0.00689885:0.00630346:0.568636:0.074496:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240937 ES:SE:LP:AF:ID  0.00233032:0.0036507:0.283997:0.240937:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913461 ES:SE:LP:AF:ID  -0.00115912:0.00455407:0.09691:0.913461:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116204 ES:SE:LP:AF:ID  0.000336338:0.00306112:0.0409586:0.116204:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067327 ES:SE:LP:AF:ID  0.00268804:0.00448182:0.259637:0.067327:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515781 ES:SE:LP:AF:ID  0.00216525:0.00226663:0.468521:0.515781:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032984 ES:SE:LP:AF:ID  -0.00290473:0.00571489:0.21467:0.032984:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036595 ES:SE:LP:AF:ID  -0.00355779:0.00519155:0.309804:0.036595:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036713 ES:SE:LP:AF:ID  -0.00380568:0.00517153:0.337242:0.036713:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03641  ES:SE:LP:AF:ID  -0.00489623:0.00520911:0.455932:0.03641:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01639  ES:SE:LP:AF:ID  -0.00320641:0.00802256:0.161151:0.01639:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03695  ES:SE:LP:AF:ID  -0.00424718:0.00515137:0.387216:0.03695:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037048 ES:SE:LP:AF:ID  -0.00443227:0.00513359:0.408935:0.037048:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101247 ES:SE:LP:AF:ID  0.00186609:0.0037388:0.207608:0.101247:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959099 ES:SE:LP:AF:ID  0.00543331:0.00494992:0.568636:0.959099:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031464 ES:SE:LP:AF:ID  0.0159909:0.00897886:1.12494:0.031464:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053253 ES:SE:LP:AF:ID  -0.000387262:0.00714368:0.0177288:0.053253:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036569 ES:SE:LP:AF:ID  -0.00524221:0.00516655:0.508638:0.036569:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036887 ES:SE:LP:AF:ID  -0.00558872:0.00511952:0.568636:0.036887:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843334 ES:SE:LP:AF:ID  0.00205975:0.00265224:0.356547:0.843334:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055861 ES:SE:LP:AF:ID  -0.003137:0.00429496:0.327902:0.055861:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122182 ES:SE:LP:AF:ID  -0.000982826:0.00290372:0.130768:0.122182:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  -0.0155517:0.00713453:1.5376:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121423 ES:SE:LP:AF:ID  -0.000680322:0.00290495:0.091515:0.121423:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132205 ES:SE:LP:AF:ID  -0.00238536:0.00286279:0.39794:0.132205:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011123 ES:SE:LP:AF:ID  0.00146577:0.0104138:0.05061:0.011123:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.00569  ES:SE:LP:AF:ID  0.0104368:0.0134389:0.356547:0.00569:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002288 ES:SE:LP:AF:ID  0.00684918:0.0224873:0.119186:0.002288:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  0.000110355:0.0367841:-0:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036801 ES:SE:LP:AF:ID  -0.00499275:0.00506779:0.49485:0.036801:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839063 ES:SE:LP:AF:ID  0.00231175:0.00256835:0.431798:0.839063:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83869  ES:SE:LP:AF:ID  0.00281201:0.00256553:0.568636:0.83869:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86988  ES:SE:LP:AF:ID  0.0012936:0.00275322:0.19382:0.86988:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129759 ES:SE:LP:AF:ID  -0.00202505:0.00275898:0.337242:0.129759:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037314 ES:SE:LP:AF:ID  -0.00565266:0.00498186:0.585027:0.037314:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037559 ES:SE:LP:AF:ID  -0.00540865:0.00495032:0.568636:0.037559:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869225 ES:SE:LP:AF:ID  0.00169161:0.0027478:0.267606:0.869225:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869322 ES:SE:LP:AF:ID  0.00163142:0.0027489:0.259637:0.869322:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037512 ES:SE:LP:AF:ID  -0.00572021:0.00497203:0.60206:0.037512:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869227 ES:SE:LP:AF:ID  0.00174788:0.00274775:0.283997:0.869227:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005131 ES:SE:LP:AF:ID  -0.0150806:0.0140897:0.552842:0.005131:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005097 ES:SE:LP:AF:ID  -0.0151899:0.0141262:0.552842:0.005097:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838146 ES:SE:LP:AF:ID  0.00287701:0.00255846:0.585027:0.838146:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037524 ES:SE:LP:AF:ID  -0.00616659:0.00497906:0.657577:0.037524:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838778 ES:SE:LP:AF:ID  0.00276549:0.00256568:0.552842:0.838778:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  0.0029038:0.00895149:0.124939:0.013776:rs181660517