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-5076/UKB-b-5076_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5076/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5076/UKB-b-5076_data.vcf.gz ...
Read summary statistics for 9264608 SNPs.
Dropped 10074 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, 1287854 SNPs remain.
After merging with regression SNP LD, 1287854 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0347 (0.0018)
Lambda GC: 1.3014
Mean Chi^2: 1.3533
Intercept: 1.0395 (0.0075)
Ratio: 0.1117 (0.0212)
Analysis finished at Thu Oct 17 14:46:29 2019
Total time elapsed: 1.0m:29.98s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9485,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 10,
    "n_p_sig": 339,
    "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": 109209,
    "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": 1287854,
    "ldsc_nsnp_merge_regression_ld": 1287854,
    "ldsc_observed_scale_h2_beta": 0.0347,
    "ldsc_observed_scale_h2_se": 0.0018,
    "ldsc_intercept_beta": 1.0395,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.3014,
    "ldsc_mean_chisq": 1.3533,
    "ldsc_ratio": 0.1118
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
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 9254585 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 9264608 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 8.635906e+00 5.754521e+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 7.880573e+07 5.631122e+07 828.0000000 3.249284e+07 6.938636e+07 1.145358e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.040000e-05 3.605100e-03 -0.0439497 -1.394800e-03 9.400000e-06 1.423100e-03 5.192360e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.718800e-03 2.123600e-03 0.0009225 1.108400e-03 1.743200e-03 3.728300e-03 2.296570e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.677984e-01 2.973898e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.677992e-01 2.973644e-01 0.0000000 2.027199e-01 4.561365e-01 7.252776e-01 9.999996e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.146048e-01 2.578979e-01 0.0025000 1.786800e-02 9.365800e-02 3.372770e-01 9.975000e-01 ▇▂▁▁▁
numeric AF_reference 109209 0.9882122 NA NA NA NA NA NA NA 2.154743e-01 2.497162e-01 0.0000000 1.517570e-02 1.120210e-01 3.368610e-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 0.0020026 0.0016974 0.2399999 0.2380595 0.623739 0.7821490 NA
1 54676 rs2462492 C T -0.0043026 0.0016813 0.0100000 0.0104933 0.400447 NA NA
1 86028 rs114608975 T C 0.0023233 0.0026884 0.3900004 0.3874926 0.103563 0.0277556 NA
1 91536 rs6702460 G T -0.0038975 0.0016557 0.0189998 0.0185743 0.456854 0.4207270 NA
1 234313 rs8179466 C T 0.0042222 0.0032641 0.2000000 0.1958296 0.074518 NA NA
1 534192 rs6680723 C T 0.0000320 0.0018911 0.9900000 0.9864867 0.240965 NA NA
1 546697 rs12025928 A G -0.0028476 0.0023592 0.2300001 0.2274218 0.913474 NA NA
1 693731 rs12238997 A G 0.0006155 0.0015847 0.6999999 0.6977217 0.116340 0.1417730 NA
1 705882 rs72631875 G A 0.0022629 0.0023226 0.3300000 0.3298989 0.067265 0.0315495 NA
1 706368 rs55727773 A G -0.0002426 0.0011740 0.8400000 0.8363084 0.515686 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0009867 0.0014166 0.4899999 0.4860781 0.137953 0.2052720 NA
22 51219387 rs9616832 T C 0.0013038 0.0018389 0.4799997 0.4782947 0.073751 0.0654952 NA
22 51219704 rs147475742 G A 0.0027928 0.0024644 0.2599998 0.2571001 0.041948 0.0473243 NA
22 51221190 rs369304721 G A 0.0017079 0.0024604 0.4899999 0.4875896 0.049729 NA NA
22 51221731 rs115055839 T C 0.0013646 0.0018400 0.4600002 0.4583170 0.073243 0.0625000 NA
22 51222100 rs114553188 G T 0.0008144 0.0021662 0.7099994 0.7069691 0.054458 0.0880591 NA
22 51223637 rs375798137 G A 0.0006886 0.0021767 0.7499995 0.7517258 0.054088 0.0788738 NA
22 51229805 rs9616985 T C 0.0013134 0.0018467 0.4799997 0.4769422 0.073077 0.0730831 NA
22 51232488 rs376461333 A G 0.0038959 0.0043503 0.3700002 0.3704912 0.020040 NA NA
22 51237063 rs3896457 T C -0.0016187 0.0011295 0.1499999 0.1518381 0.297987 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623739 ES:SE:LP:AF:ID  0.00200262:0.00169735:0.619789:0.623739:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400447 ES:SE:LP:AF:ID  -0.00430262:0.00168128:2:0.400447:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103563 ES:SE:LP:AF:ID  0.00232327:0.00268843:0.408935:0.103563:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456854 ES:SE:LP:AF:ID  -0.00389751:0.00165572:1.72125:0.456854:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074518 ES:SE:LP:AF:ID  0.00422222:0.00326412:0.69897:0.074518:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  3.20294e-05:0.00189107:0.00436481:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913474 ES:SE:LP:AF:ID  -0.00284763:0.00235921:0.638272:0.913474:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11634  ES:SE:LP:AF:ID  0.000615494:0.0015847:0.154902:0.11634:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067265 ES:SE:LP:AF:ID  0.00226294:0.00232259:0.481486:0.067265:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515686 ES:SE:LP:AF:ID  -0.000242561:0.00117396:0.0757207:0.515686:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032994 ES:SE:LP:AF:ID  0.00202313:0.0029601:0.309804:0.032994:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036606 ES:SE:LP:AF:ID  0.00179994:0.00268885:0.30103:0.036606:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  0.00177524:0.00267868:0.29243:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036422 ES:SE:LP:AF:ID  0.00198308:0.00269797:0.337242:0.036422:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016422 ES:SE:LP:AF:ID  -0.00449617:0.0041513:0.552842:0.016422:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036962 ES:SE:LP:AF:ID  0.00174917:0.00266803:0.29243:0.036962:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037058 ES:SE:LP:AF:ID  0.00148244:0.00265895:0.236572:0.037058:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10117  ES:SE:LP:AF:ID  -0.00113306:0.00193715:0.251812:0.10117:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959116 ES:SE:LP:AF:ID  -0.00287314:0.00256467:0.585027:0.959116:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031456 ES:SE:LP:AF:ID  -0.00172076:0.00465402:0.148742:0.031456:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053258 ES:SE:LP:AF:ID  -0.00227433:0.0037027:0.267606:0.053258:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036575 ES:SE:LP:AF:ID  0.0016079:0.0026762:0.259637:0.036575:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  0.00139078:0.00265184:0.221849:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843218 ES:SE:LP:AF:ID  -0.00107403:0.00137353:0.366532:0.843218:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055922 ES:SE:LP:AF:ID  0.00199032:0.00222375:0.431798:0.055922:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122325 ES:SE:LP:AF:ID  0.0011192:0.00150329:0.337242:0.122325:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  0.0012:0.0036978:0.124939:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121567 ES:SE:LP:AF:ID  0.00107337:0.00150393:0.318759:0.121567:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132324 ES:SE:LP:AF:ID  0.00118314:0.0014824:0.376751:0.132324:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  -0.0041433:0.00539019:0.356547:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005703 ES:SE:LP:AF:ID  0.00799425:0.00695525:0.60206:0.005703:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  0.0014442:0.00262495:0.236572:0.036808:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838956 ES:SE:LP:AF:ID  -0.000899913:0.00133017:0.30103:0.838956:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838586 ES:SE:LP:AF:ID  -0.000939306:0.00132874:0.318759:0.838586:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86977  ES:SE:LP:AF:ID  -0.00142002:0.00142574:0.49485:0.86977:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129879 ES:SE:LP:AF:ID  0.00117966:0.00142865:0.387216:0.129879:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037318 ES:SE:LP:AF:ID  0.00173761:0.00258051:0.30103:0.037318:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  0.00176136:0.00256425:0.309804:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  -0.0014219:0.00142296:0.49485:0.869116:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -0.00148063:0.00142353:0.522879:0.869214:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037519 ES:SE:LP:AF:ID  0.00175465:0.00257533:0.30103:0.037519:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  -0.00143372:0.00142293:0.508638:0.869119:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005117 ES:SE:LP:AF:ID  -0.00368922:0.00730964:0.21467:0.005117:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005083 ES:SE:LP:AF:ID  -0.0033743:0.00732885:0.187087:0.005083:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83804  ES:SE:LP:AF:ID  -0.000990214:0.00132507:0.346787:0.83804:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.00189041:0.00257899:0.337242:0.03753:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838671 ES:SE:LP:AF:ID  -0.00101529:0.00132879:0.356547:0.838671:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013766 ES:SE:LP:AF:ID  0.000524977:0.00463955:0.0409586:0.013766:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005545 ES:SE:LP:AF:ID  0.0113353:0.00715764:0.958607:0.005545:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839782 ES:SE:LP:AF:ID  -0.00113358:0.00134675:0.39794:0.839782:rs3131965