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-15926/UKB-b-15926_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15926/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15926/UKB-b-15926_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: 0.058 (0.0022)
Lambda GC: 1.4631
Mean Chi^2: 1.571
Intercept: 1.0729 (0.0097)
Ratio: 0.1278 (0.0169)
Analysis finished at Thu Oct 17 14:46:17 2019
Total time elapsed: 1.0m:43.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 43,
    "n_p_sig": 2392,
    "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": 0.058,
    "ldsc_observed_scale_h2_se": 0.0022,
    "ldsc_intercept_beta": 1.0729,
    "ldsc_intercept_se": 0.0097,
    "ldsc_lambda_gc": 1.4631,
    "ldsc_mean_chisq": 1.571,
    "ldsc_ratio": 0.1277
}

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 1.000000 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+07 828.000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.469000e-04 8.964600e-03 -0.157638 -3.057100e-03 -6.460000e-05 2.879600e-03 2.125610e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.145300e-03 5.822600e-03 0.001719 2.104100e-03 3.528300e-03 8.141500e-03 9.034380e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.549395e-01 3.007623e-01 0.000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.549390e-01 3.007384e-01 0.000000 1.828252e-01 4.378454e-01 7.156375e-01 9.999999e-01 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035068e-01 2.568670e-01 0.000960 1.316800e-02 7.790800e-02 3.164497e-01 9.990310e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.000000 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 0.0015217 0.0031623 0.6300007 0.6303653 0.623788 0.7821490 NA
1 54676 rs2462492 C T -0.0023533 0.0031316 0.4500005 0.4523720 0.400477 NA NA
1 86028 rs114608975 T C -0.0053445 0.0050106 0.2900000 0.2861340 0.103512 0.0277556 NA
1 91536 rs6702460 G T -0.0018580 0.0030837 0.5500004 0.5468214 0.456850 0.4207270 NA
1 234313 rs8179466 C T -0.0006693 0.0060835 0.9100000 0.9123927 0.074460 NA NA
1 534192 rs6680723 C T 0.0003783 0.0035215 0.9100000 0.9144506 0.240945 NA NA
1 546697 rs12025928 A G 0.0022943 0.0043949 0.5999997 0.6016526 0.913536 NA NA
1 693731 rs12238997 A G 0.0013534 0.0029517 0.6499995 0.6465777 0.116338 0.1417730 NA
1 705882 rs72631875 G A 0.0026122 0.0043276 0.5500004 0.5461068 0.067231 0.0315495 NA
1 706368 rs55727773 A G 0.0012032 0.0021866 0.5800000 0.5821528 0.515700 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0041741 0.0045933 0.3599996 0.3634856 0.041934 0.0473243 NA
22 51219766 rs182321900 C T 0.0234356 0.0214825 0.2800000 0.2753099 0.001924 NA NA
22 51220146 rs868950473 C T 0.0287510 0.0212967 0.1800002 0.1770091 0.001970 NA NA
22 51221190 rs369304721 G A -0.0035684 0.0045895 0.4400003 0.4368536 0.049648 NA NA
22 51221731 rs115055839 T C -0.0028378 0.0034315 0.4100001 0.4082449 0.073154 0.0625000 NA
22 51222100 rs114553188 G T -0.0022484 0.0040354 0.5800000 0.5774106 0.054498 0.0880591 NA
22 51223637 rs375798137 G A -0.0025278 0.0040551 0.5300002 0.5330370 0.054123 0.0788738 NA
22 51229805 rs9616985 T C -0.0029185 0.0034438 0.4000000 0.3967408 0.072990 0.0730831 NA
22 51232488 rs376461333 A G -0.0016911 0.0081059 0.8300000 0.8347405 0.020044 NA NA
22 51237063 rs3896457 T C -0.0009772 0.0021048 0.6400000 0.6424684 0.298122 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623788 ES:SE:LP:AF:ID  0.00152172:0.00316226:0.200659:0.623788:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400477 ES:SE:LP:AF:ID  -0.0023533:0.00313161:0.346787:0.400477:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103512 ES:SE:LP:AF:ID  -0.00534449:0.00501058:0.537602:0.103512:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45685  ES:SE:LP:AF:ID  -0.00185804:0.00308373:0.259637:0.45685:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07446  ES:SE:LP:AF:ID  -0.000669313:0.0060835:0.0409586:0.07446:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240945 ES:SE:LP:AF:ID  0.000378306:0.00352153:0.0409586:0.240945:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913536 ES:SE:LP:AF:ID  0.00229426:0.00439492:0.221849:0.913536:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116338 ES:SE:LP:AF:ID  0.0013534:0.00295166:0.187087:0.116338:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067231 ES:SE:LP:AF:ID  0.00261217:0.00432762:0.259637:0.067231:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.5157   ES:SE:LP:AF:ID  0.00120315:0.00218658:0.236572:0.5157:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032928 ES:SE:LP:AF:ID  -0.00165501:0.00551909:0.119186:0.032928:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036538 ES:SE:LP:AF:ID  -0.00122498:0.0050127:0.091515:0.036538:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036652 ES:SE:LP:AF:ID  -0.00147168:0.0049938:0.113509:0.036652:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036354 ES:SE:LP:AF:ID  -0.00182307:0.00502964:0.142668:0.036354:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016413 ES:SE:LP:AF:ID  -0.00385851:0.00773761:0.207608:0.016413:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03689  ES:SE:LP:AF:ID  -0.00137769:0.00497408:0.107905:0.03689:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036987 ES:SE:LP:AF:ID  -0.00143319:0.00495697:0.113509:0.036987:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101269 ES:SE:LP:AF:ID  0.00249794:0.00360666:0.309804:0.101269:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959206 ES:SE:LP:AF:ID  0.00112727:0.00478179:0.091515:0.959206:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031476 ES:SE:LP:AF:ID  0.00252076:0.00866685:0.113509:0.031476:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053226 ES:SE:LP:AF:ID  0.0105078:0.00690075:0.886057:0.053226:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036511 ES:SE:LP:AF:ID  -0.000231709:0.00498907:0.0177288:0.036511:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036822 ES:SE:LP:AF:ID  -0.000488755:0.00494379:0.0362122:0.036822:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843292 ES:SE:LP:AF:ID  -0.000698525:0.00255882:0.107905:0.843292:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056016 ES:SE:LP:AF:ID  0.000618358:0.00413745:0.0555173:0.056016:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122324 ES:SE:LP:AF:ID  0.00155768:0.00279986:0.236572:0.122324:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025737 ES:SE:LP:AF:ID  0.00370746:0.00688246:0.229148:0.025737:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121569 ES:SE:LP:AF:ID  0.00144903:0.00280099:0.221849:0.121569:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132285 ES:SE:LP:AF:ID  0.00139754:0.00276153:0.21467:0.132285:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011133 ES:SE:LP:AF:ID  -0.0103405:0.0100374:0.522879:0.011133:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005691 ES:SE:LP:AF:ID  0.0338352:0.0129747:2.04096:0.005691:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002267 ES:SE:LP:AF:ID  -0.0151528:0.0217763:0.309804:0.002267:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001015 ES:SE:LP:AF:ID  -0.0423663:0.0360124:0.619789:0.001015:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036738 ES:SE:LP:AF:ID  -0.000871057:0.00489381:0.0655015:0.036738:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838993 ES:SE:LP:AF:ID  -0.00203573:0.00247782:0.387216:0.838993:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838638 ES:SE:LP:AF:ID  -0.00199316:0.00247535:0.376751:0.838638:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869752 ES:SE:LP:AF:ID  -0.00267483:0.00265543:0.508638:0.869752:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129884 ES:SE:LP:AF:ID  0.00227387:0.00266097:0.408935:0.129884:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037244 ES:SE:LP:AF:ID  -0.00106198:0.00481114:0.0809219:0.037244:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037482 ES:SE:LP:AF:ID  -0.00096738:0.00478113:0.0757207:0.037482:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869107 ES:SE:LP:AF:ID  -0.00252257:0.00265043:0.468521:0.869107:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869202 ES:SE:LP:AF:ID  -0.00258065:0.00265149:0.481486:0.869202:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037446 ES:SE:LP:AF:ID  -0.00107784:0.00480144:0.0861861:0.037446:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869108 ES:SE:LP:AF:ID  -0.00256029:0.00265038:0.481486:0.869108:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005137 ES:SE:LP:AF:ID  0.0082915:0.0135855:0.267606:0.005137:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005103 ES:SE:LP:AF:ID  0.00712893:0.013621:0.221849:0.005103:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838087 ES:SE:LP:AF:ID  -0.00191977:0.00246842:0.356547:0.838087:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03746  ES:SE:LP:AF:ID  -0.00106639:0.004808:0.0861861:0.03746:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838719 ES:SE:LP:AF:ID  -0.0020026:0.00247536:0.376751:0.838719:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013778 ES:SE:LP:AF:ID  -0.00301894:0.00863908:0.136677:0.013778:rs181660517