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-14449/UKB-b-14449_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14449/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14449/UKB-b-14449_data.vcf.gz ...
Read summary statistics for 9019193 SNPs.
Dropped 8783 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, 1287262 SNPs remain.
After merging with regression SNP LD, 1287262 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0045 (0.0042)
Lambda GC: 0.9863
Mean Chi^2: 0.9937
Intercept: 1.0025 (0.0059)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Thu Oct 17 14:44:52 2019
Total time elapsed: 1.0m:12.84s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 93930,
    "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": 1287262,
    "ldsc_nsnp_merge_regression_ld": 1287262,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0025,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 0.9863,
    "ldsc_mean_chisq": 0.9937,
    "ldsc_ratio": -0.3968
}

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 FALSE
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 9010450 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 9019193 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 8.642993e+00 5.758159e+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 7.878515e+07 5.633955e+07 828.0000000 3.242933e+07 6.934611e+07 1.145386e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.670000e-05 1.229090e-02 -0.1605740 -4.693300e-03 1.510000e-05 4.716800e-03 1.364430e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.901000e-03 7.272600e-03 0.0035881 4.279100e-03 6.560000e-03 1.358400e-02 8.329890e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 5.015097e-01 2.885989e-01 0.0000001 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 5.015100e-01 2.885731e-01 0.0000001 2.516258e-01 5.023903e-01 7.513796e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.199638e-01 2.585111e-01 0.0035340 2.039000e-02 1.011740e-01 3.468100e-01 9.964660e-01 ▇▂▁▁▁
numeric AF_reference 93930 0.9895855 NA NA NA NA NA NA NA 2.202959e-01 2.504130e-01 0.0000000 1.777160e-02 1.186100e-01 3.452480e-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 -0.0047155 0.0066305 0.4799997 0.4769745 0.623768 0.7821490 NA
1 54676 rs2462492 C T -0.0041847 0.0065869 0.5300002 0.5252253 0.398689 NA NA
1 86028 rs114608975 T C 0.0163653 0.0104537 0.1199999 0.1174650 0.103970 0.0277556 NA
1 91536 rs6702460 G T -0.0089895 0.0064743 0.1600000 0.1649879 0.455611 0.4207270 NA
1 234313 rs8179466 C T -0.0019169 0.0126940 0.8800001 0.8799716 0.074778 NA NA
1 534192 rs6680723 C T -0.0063009 0.0074053 0.3900004 0.3948486 0.240465 NA NA
1 546697 rs12025928 A G 0.0047912 0.0091781 0.5999997 0.6016521 0.912866 NA NA
1 693731 rs12238997 A G 0.0105203 0.0061580 0.0879995 0.0875650 0.117762 0.1417730 NA
1 705882 rs72631875 G A 0.0060152 0.0090115 0.5000000 0.5044499 0.067648 0.0315495 NA
1 706368 rs55727773 A G -0.0057818 0.0045660 0.2099999 0.2054165 0.514191 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0008825 0.0055229 0.8700001 0.8730521 0.137219 0.2052720 NA
22 51219387 rs9616832 T C -0.0011565 0.0071983 0.8700001 0.8723605 0.072607 0.0654952 NA
22 51219704 rs147475742 G A -0.0045275 0.0095686 0.6400000 0.6360959 0.041856 0.0473243 NA
22 51221190 rs369304721 G A 0.0014028 0.0096298 0.8800001 0.8841832 0.049110 NA NA
22 51221731 rs115055839 T C 0.0000145 0.0072005 1.0000000 0.9983915 0.072139 0.0625000 NA
22 51222100 rs114553188 G T -0.0043674 0.0084159 0.5999997 0.6037983 0.054532 0.0880591 NA
22 51223637 rs375798137 G A -0.0041429 0.0084599 0.6200004 0.6243352 0.054144 0.0788738 NA
22 51229805 rs9616985 T C 0.0000012 0.0072266 1.0000000 0.9998712 0.072002 0.0730831 NA
22 51232488 rs376461333 A G -0.0180095 0.0170352 0.2900000 0.2904234 0.020056 NA NA
22 51237063 rs3896457 T C -0.0061853 0.0043934 0.1600000 0.1591729 0.298314 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623768 ES:SE:LP:AF:ID  -0.00471546:0.0066305:0.318759:0.623768:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398689 ES:SE:LP:AF:ID  -0.00418472:0.00658688:0.275724:0.398689:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10397  ES:SE:LP:AF:ID  0.0163653:0.0104537:0.920819:0.10397:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455611 ES:SE:LP:AF:ID  -0.0089895:0.0064743:0.79588:0.455611:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074778 ES:SE:LP:AF:ID  -0.00191686:0.012694:0.0555173:0.074778:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240465 ES:SE:LP:AF:ID  -0.00630088:0.00740533:0.408935:0.240465:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912866 ES:SE:LP:AF:ID  0.00479123:0.00917814:0.221849:0.912866:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117762 ES:SE:LP:AF:ID  0.0105203:0.00615804:1.05552:0.117762:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067648 ES:SE:LP:AF:ID  0.00601521:0.00901149:0.30103:0.067648:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514191 ES:SE:LP:AF:ID  -0.00578175:0.00456597:0.677781:0.514191:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033661 ES:SE:LP:AF:ID  -0.000748648:0.0113928:0.0222764:0.033661:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037322 ES:SE:LP:AF:ID  -0.00148092:0.0103619:0.05061:0.037322:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037402 ES:SE:LP:AF:ID  -0.00226842:0.0103288:0.0809219:0.037402:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037096 ES:SE:LP:AF:ID  -0.0010669:0.0103999:0.0362122:0.037096:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016725 ES:SE:LP:AF:ID  -0.00679772:0.0160398:0.173925:0.016725:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037663 ES:SE:LP:AF:ID  -0.000182133:0.010284:0.00436481:0.037663:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03775  ES:SE:LP:AF:ID  -0.001145:0.0102524:0.0409586:0.03775:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10128  ES:SE:LP:AF:ID  0.00516288:0.00754869:0.309804:0.10128:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958034 ES:SE:LP:AF:ID  -0.00684951:0.00986137:0.309804:0.958034:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03183  ES:SE:LP:AF:ID  -0.0138839:0.0180388:0.356547:0.03183:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052517 ES:SE:LP:AF:ID  -0.00783087:0.0145919:0.229148:0.052517:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037207 ES:SE:LP:AF:ID  -0.00155811:0.0103249:0.0555173:0.037207:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037523 ES:SE:LP:AF:ID  -0.00279573:0.0102374:0.107905:0.037523:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840944 ES:SE:LP:AF:ID  -0.010877:0.00533275:1.38722:0.840944:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056183 ES:SE:LP:AF:ID  0.0130655:0.00867542:0.886057:0.056183:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123691 ES:SE:LP:AF:ID  0.0099161:0.00584516:1.04576:0.123691:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025919 ES:SE:LP:AF:ID  -0.0219584:0.0143425:0.886057:0.025919:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122885 ES:SE:LP:AF:ID  0.00953779:0.00584815:1:0.122885:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133653 ES:SE:LP:AF:ID  0.00876072:0.00576432:0.886057:0.133653:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011245 ES:SE:LP:AF:ID  -0.0238105:0.0208631:0.60206:0.011245:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006012 ES:SE:LP:AF:ID  0.0198375:0.0262747:0.346787:0.006012:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037493 ES:SE:LP:AF:ID  -0.00421045:0.0101237:0.167491:0.037493:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836703 ES:SE:LP:AF:ID  -0.00860311:0.00516037:1.02228:0.836703:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836271 ES:SE:LP:AF:ID  -0.00948769:0.00515451:1.18046:0.836271:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.867978 ES:SE:LP:AF:ID  -0.0108816:0.00552903:1.3098:0.867978:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131684 ES:SE:LP:AF:ID  0.0110572:0.00554091:1.33724:0.131684:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037935 ES:SE:LP:AF:ID  -0.00617824:0.00996431:0.267606:0.037935:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038183 ES:SE:LP:AF:ID  -0.00623098:0.0099026:0.275724:0.038183:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867282 ES:SE:LP:AF:ID  -0.0116802:0.00551786:1.46852:0.867282:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867383 ES:SE:LP:AF:ID  -0.0116874:0.00552044:1.46852:0.867383:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038135 ES:SE:LP:AF:ID  -0.0062752:0.00994211:0.275724:0.038135:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867281 ES:SE:LP:AF:ID  -0.0118452:0.00551752:1.49485:0.867281:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  -0.0165592:0.0285782:0.251812:0.005088:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005055 ES:SE:LP:AF:ID  -0.017833:0.0286578:0.275724:0.005055:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835816 ES:SE:LP:AF:ID  -0.0088783:0.0051435:1.07572:0.835816:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038153 ES:SE:LP:AF:ID  -0.00635627:0.00995513:0.283997:0.038153:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83642  ES:SE:LP:AF:ID  -0.008855:0.00515727:1.0655:0.83642:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.0132   ES:SE:LP:AF:ID  0.0108159:0.0184886:0.251812:0.0132:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005514 ES:SE:LP:AF:ID  0.000292866:0.0279416:0.00436481:0.005514:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837712 ES:SE:LP:AF:ID  -0.00861773:0.00522789:1.00436:0.837712:rs3131965