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-5640/UKB-b-5640_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5640/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:32 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5640/UKB-b-5640_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: 0.0292 (0.0017)
Lambda GC: 1.3014
Mean Chi^2: 1.3522
Intercept: 1.0864 (0.0082)
Ratio: 0.2452 (0.0233)
Analysis finished at Thu Oct 17 14:47:08 2019
Total time elapsed: 1.0m:35.58s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 14,
    "n_p_sig": 808,
    "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": 0.0292,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.0864,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.3014,
    "ldsc_mean_chisq": 1.3522,
    "ldsc_ratio": 0.2453
}

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 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 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 -1.575000e-04 7.485600e-03 -0.1110860 -2.404600e-03 -4.910000e-05 2.277400e-03 1.328780e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.082500e-03 4.811300e-03 0.0014222 1.741000e-03 2.919400e-03 6.736200e-03 7.477220e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.665563e-01 2.975677e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.665564e-01 2.975432e-01 0.0000000 2.005362e-01 4.549088e-01 7.241759e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035075e-01 2.568622e-01 0.0009880 1.316900e-02 7.791100e-02 3.164530e-01 9.990080e-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 0.0033550 0.0026161 0.2000000 0.1997011 0.623753 0.7821490 NA
1 54676 rs2462492 C T 0.0002910 0.0025918 0.9100000 0.9106053 0.400416 NA NA
1 86028 rs114608975 T C -0.0054406 0.0041442 0.1900002 0.1892397 0.103565 0.0277556 NA
1 91536 rs6702460 G T 0.0031422 0.0025525 0.2200002 0.2183134 0.456863 0.4207270 NA
1 234313 rs8179466 C T -0.0015432 0.0050331 0.7600007 0.7591451 0.074500 NA NA
1 534192 rs6680723 C T 0.0033097 0.0029148 0.2599998 0.2561834 0.240997 NA NA
1 546697 rs12025928 A G 0.0028000 0.0036381 0.4400003 0.4415236 0.913521 NA NA
1 693731 rs12238997 A G -0.0026610 0.0024427 0.2800000 0.2759956 0.116354 0.1417730 NA
1 705882 rs72631875 G A -0.0058653 0.0035799 0.1000000 0.1013395 0.067276 0.0315495 NA
1 706368 rs55727773 A G 0.0004866 0.0018097 0.7899998 0.7880187 0.515574 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0009284 0.0038009 0.8100000 0.8070353 0.041937 0.0473243 NA
22 51219766 rs182321900 C T -0.0254176 0.0177675 0.1499999 0.1525543 0.001924 NA NA
22 51220146 rs868950473 C T -0.0279932 0.0175981 0.1100001 0.1116784 0.001973 NA NA
22 51221190 rs369304721 G A -0.0013607 0.0037938 0.7199992 0.7198482 0.049724 NA NA
22 51221731 rs115055839 T C -0.0016234 0.0028376 0.5700002 0.5672586 0.073218 0.0625000 NA
22 51222100 rs114553188 G T 0.0022676 0.0033397 0.5000000 0.4971543 0.054470 0.0880591 NA
22 51223637 rs375798137 G A 0.0025088 0.0033559 0.4500005 0.4547155 0.054098 0.0788738 NA
22 51229805 rs9616985 T C -0.0015710 0.0028479 0.5800000 0.5811852 0.073054 0.0730831 NA
22 51232488 rs376461333 A G 0.0032946 0.0067071 0.6200004 0.6232789 0.020043 NA NA
22 51237063 rs3896457 T C 0.0001351 0.0017415 0.9400001 0.9381645 0.297958 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623753 ES:SE:LP:AF:ID  0.00335496:0.00261615:0.69897:0.623753:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400416 ES:SE:LP:AF:ID  0.00029099:0.00259176:0.0409586:0.400416:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103565 ES:SE:LP:AF:ID  -0.00544065:0.00414421:0.721246:0.103565:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  0.00314218:0.00255249:0.657577:0.456863:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.0745   ES:SE:LP:AF:ID  -0.00154317:0.00503311:0.119186:0.0745:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240997 ES:SE:LP:AF:ID  0.00330969:0.00291485:0.585027:0.240997:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913521 ES:SE:LP:AF:ID  0.00279995:0.00363808:0.356547:0.913521:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116354 ES:SE:LP:AF:ID  -0.00266101:0.00244273:0.552842:0.116354:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067276 ES:SE:LP:AF:ID  -0.00586532:0.00357992:1:0.067276:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515574 ES:SE:LP:AF:ID  0.000486592:0.00180967:0.102373:0.515574:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032998 ES:SE:LP:AF:ID  0.000744697:0.0045627:0.0604807:0.032998:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036613 ES:SE:LP:AF:ID  -0.00130122:0.00414447:0.124939:0.036613:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036729 ES:SE:LP:AF:ID  -0.00173098:0.00412883:0.167491:0.036729:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03643  ES:SE:LP:AF:ID  -0.00157133:0.00415844:0.148742:0.03643:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016401 ES:SE:LP:AF:ID  -0.00592885:0.00640466:0.455932:0.016401:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03697  ES:SE:LP:AF:ID  -0.00202458:0.00411228:0.207608:0.03697:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  -0.00173117:0.00409829:0.173925:0.037066:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101239 ES:SE:LP:AF:ID  0.005089:0.00298511:1.05552:0.101239:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959108 ES:SE:LP:AF:ID  0.00498817:0.00395301:0.677781:0.959108:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031455 ES:SE:LP:AF:ID  -0.00477192:0.00717374:0.29243:0.031455:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  0.00303285:0.00570662:0.221849:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036583 ES:SE:LP:AF:ID  -0.00246464:0.00412482:0.259637:0.036583:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036897 ES:SE:LP:AF:ID  -0.0020854:0.00408741:0.21467:0.036897:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843197 ES:SE:LP:AF:ID  0.00334352:0.00211718:0.958607:0.843197:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055928 ES:SE:LP:AF:ID  -0.00174541:0.00342756:0.21467:0.055928:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122331 ES:SE:LP:AF:ID  -0.00280851:0.00231728:0.638272:0.122331:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025705 ES:SE:LP:AF:ID  -0.00489338:0.00570267:0.408935:0.025705:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121574 ES:SE:LP:AF:ID  -0.00270488:0.00231827:0.619789:0.121574:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132355 ES:SE:LP:AF:ID  -0.00265659:0.00228488:0.619789:0.132355:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011128 ES:SE:LP:AF:ID  -0.0015066:0.0083108:0.0655015:0.011128:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005706 ES:SE:LP:AF:ID  -0.0225:0.0107178:1.4437:0.005706:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002269 ES:SE:LP:AF:ID  -0.0231143:0.0180325:0.69897:0.002269:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001027 ES:SE:LP:AF:ID  -0.0113316:0.0295903:0.154902:0.001027:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036811 ES:SE:LP:AF:ID  -0.00141567:0.00404616:0.136677:0.036811:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838937 ES:SE:LP:AF:ID  0.00279921:0.00205035:0.769551:0.838937:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838567 ES:SE:LP:AF:ID  0.00312927:0.00204815:0.886057:0.838567:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86976  ES:SE:LP:AF:ID  0.00259545:0.00219774:0.619789:0.86976:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129886 ES:SE:LP:AF:ID  -0.00305716:0.00220223:0.769551:0.129886:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037321 ES:SE:LP:AF:ID  -0.00169439:0.00397759:0.173925:0.037321:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037565 ES:SE:LP:AF:ID  -0.00190676:0.00395251:0.200659:0.037565:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869105 ES:SE:LP:AF:ID  0.0030249:0.00219344:0.769551:0.869105:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869203 ES:SE:LP:AF:ID  0.00303954:0.00219431:0.769551:0.869203:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037522 ES:SE:LP:AF:ID  -0.00185859:0.00396963:0.19382:0.037522:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869107 ES:SE:LP:AF:ID  0.00300032:0.00219339:0.769551:0.869107:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005127 ES:SE:LP:AF:ID  0.00912821:0.0112547:0.376751:0.005127:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005093 ES:SE:LP:AF:ID  0.00936557:0.0112842:0.387216:0.005093:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83802  ES:SE:LP:AF:ID  0.00327955:0.00204247:0.958607:0.83802:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  -0.00182255:0.00397523:0.187087:0.037535:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838652 ES:SE:LP:AF:ID  0.00338014:0.00204822:1.00436:0.838652:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013756 ES:SE:LP:AF:ID  0.00440169:0.00715397:0.267606:0.013756:rs181660517