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-8463/UKB-b-8463_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8463/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8463/UKB-b-8463_data.vcf.gz ...
Read summary statistics for 8846166 SNPs.
Dropped 8081 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, 1286606 SNPs remain.
After merging with regression SNP LD, 1286606 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0369 (0.0045)
Lambda GC: 1.0815
Mean Chi^2: 1.0839
Intercept: 0.9987 (0.0065)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:43:10 2019
Total time elapsed: 1.0m:29.45s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9472,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -1.2695e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 88085,
    "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": 1286606,
    "ldsc_nsnp_merge_regression_ld": 1286606,
    "ldsc_observed_scale_h2_beta": 0.0369,
    "ldsc_observed_scale_h2_se": 0.0045,
    "ldsc_intercept_beta": 0.9987,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0815,
    "ldsc_mean_chisq": 1.0839,
    "ldsc_ratio": -0.0155
}

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 8838122 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 8846166 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 8.648041e+00 5.760025e+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 7.877315e+07 5.634122e+07 828.0000000 3.240953e+07 6.932990e+07 1.145472e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.300000e-06 6.052900e-03 -0.0656696 -2.454700e-03 6.900000e-06 2.469900e-03 6.545210e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.880000e-03 3.463400e-03 0.0018399 2.186200e-03 3.293800e-03 6.660500e-03 4.217350e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.906135e-01 2.909915e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.906146e-01 2.909676e-01 0.0000000 2.366033e-01 4.868096e-01 7.427708e-01 9.999994e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.238443e-01 2.589320e-01 0.0043440 2.238700e-02 1.066060e-01 3.535680e-01 9.956560e-01 ▇▂▁▁▁
numeric AF_reference 88085 0.9900426 NA NA NA NA NA NA NA 2.238665e-01 2.508830e-01 0.0000000 1.976840e-02 1.236020e-01 3.514380e-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 -0.0065211 0.0033903 0.0539995 0.0544208 0.624155 0.7821490 NA
1 54676 rs2462492 C T -0.0002430 0.0033667 0.9400001 0.9424704 0.399850 NA NA
1 86028 rs114608975 T C 0.0082834 0.0053828 0.1199999 0.1238390 0.103349 0.0277556 NA
1 91536 rs6702460 G T -0.0010465 0.0033100 0.7499995 0.7518788 0.457515 0.4207270 NA
1 234313 rs8179466 C T -0.0049306 0.0065473 0.4500005 0.4514047 0.074429 NA NA
1 534192 rs6680723 C T -0.0066312 0.0037862 0.0800000 0.0798717 0.240670 NA NA
1 546697 rs12025928 A G 0.0073062 0.0047419 0.1199999 0.1233682 0.914047 NA NA
1 693731 rs12238997 A G -0.0080759 0.0031677 0.0109999 0.0107887 0.116008 0.1417730 NA
1 705882 rs72631875 G A 0.0028501 0.0046632 0.5400003 0.5410746 0.066789 0.0315495 NA
1 706368 rs55727773 A G 0.0047324 0.0023433 0.0430002 0.0434297 0.515058 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0015922 0.0028320 0.5700002 0.5739761 0.138572 0.2052720 NA
22 51219387 rs9616832 T C 0.0020772 0.0036613 0.5700002 0.5704899 0.074440 0.0654952 NA
22 51219704 rs147475742 G A 0.0022288 0.0049031 0.6499995 0.6494261 0.042184 0.0473243 NA
22 51221190 rs369304721 G A -0.0001853 0.0048972 0.9699999 0.9698135 0.050232 NA NA
22 51221731 rs115055839 T C 0.0020579 0.0036647 0.5700002 0.5744170 0.073916 0.0625000 NA
22 51222100 rs114553188 G T 0.0001789 0.0043447 0.9699999 0.9671590 0.054307 0.0880591 NA
22 51223637 rs375798137 G A 0.0006577 0.0043652 0.8800001 0.8802375 0.053946 0.0788738 NA
22 51229805 rs9616985 T C 0.0021102 0.0036749 0.5700002 0.5658155 0.073804 0.0730831 NA
22 51232488 rs376461333 A G -0.0034905 0.0087412 0.6899999 0.6896613 0.020055 NA NA
22 51237063 rs3896457 T C 0.0020877 0.0022618 0.3599996 0.3559987 0.297818 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624155 ES:SE:LP:AF:ID  -0.00652109:0.00339027:1.26761:0.624155:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39985  ES:SE:LP:AF:ID  -0.000242958:0.00336669:0.0268721:0.39985:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103349 ES:SE:LP:AF:ID  0.00828344:0.00538285:0.920819:0.103349:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457515 ES:SE:LP:AF:ID  -0.00104649:0.00330997:0.124939:0.457515:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074429 ES:SE:LP:AF:ID  -0.00493061:0.0065473:0.346787:0.074429:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24067  ES:SE:LP:AF:ID  -0.00663125:0.00378619:1.09691:0.24067:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.914047 ES:SE:LP:AF:ID  0.00730622:0.00474187:0.920819:0.914047:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116008 ES:SE:LP:AF:ID  -0.0080759:0.00316768:1.95861:0.116008:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066789 ES:SE:LP:AF:ID  0.00285012:0.00466324:0.267606:0.066789:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515058 ES:SE:LP:AF:ID  0.00473244:0.00234331:1.36653:0.515058:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033309 ES:SE:LP:AF:ID  -0.00735255:0.0058852:0.677781:0.033309:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036827 ES:SE:LP:AF:ID  -0.00632774:0.00535911:0.619789:0.036827:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036945 ES:SE:LP:AF:ID  -0.00630995:0.0053383:0.619789:0.036945:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036665 ES:SE:LP:AF:ID  -0.00563338:0.00537633:0.537602:0.036665:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016593 ES:SE:LP:AF:ID  -0.00722818:0.00822999:0.420216:0.016593:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037195 ES:SE:LP:AF:ID  -0.00631315:0.00531672:0.619789:0.037195:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037295 ES:SE:LP:AF:ID  -0.00597213:0.005299:0.585027:0.037295:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100976 ES:SE:LP:AF:ID  0.00678343:0.0038729:1.09691:0.100976:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958758 ES:SE:LP:AF:ID  0.00700761:0.00510315:0.769551:0.958758:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031387 ES:SE:LP:AF:ID  0.00688774:0.00926507:0.337242:0.031387:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053678 ES:SE:LP:AF:ID  -0.000655718:0.00733402:0.0315171:0.053678:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03678  ES:SE:LP:AF:ID  -0.00441421:0.00533309:0.387216:0.03678:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037061 ES:SE:LP:AF:ID  -0.00548832:0.00528938:0.522879:0.037061:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843004 ES:SE:LP:AF:ID  0.00845675:0.00273989:2.69897:0.843004:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055459 ES:SE:LP:AF:ID  -0.00933164:0.00446576:1.4318:0.055459:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122194 ES:SE:LP:AF:ID  -0.00747842:0.00300082:1.88606:0.122194:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.026035 ES:SE:LP:AF:ID  0.00734104:0.00735305:0.49485:0.026035:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121449 ES:SE:LP:AF:ID  -0.00762484:0.00300185:1.95861:0.121449:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132063 ES:SE:LP:AF:ID  -0.00834545:0.00296706:2.3098:0.132063:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011199 ES:SE:LP:AF:ID  -0.00529152:0.0107279:0.207608:0.011199:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005703 ES:SE:LP:AF:ID  -0.000452333:0.0139218:0.0132283:0.005703:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037026 ES:SE:LP:AF:ID  -0.00643885:0.00522947:0.657577:0.037026:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838772 ES:SE:LP:AF:ID  0.00737944:0.00265505:2.26761:0.838772:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  0.00759593:0.00265249:2.37675:0.838434:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869823 ES:SE:LP:AF:ID  0.00666796:0.00284537:1.72125:0.869823:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129823 ES:SE:LP:AF:ID  -0.00684792:0.0028518:1.79588:0.129823:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037588 ES:SE:LP:AF:ID  -0.00624495:0.00513921:0.657577:0.037588:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037831 ES:SE:LP:AF:ID  -0.00596978:0.00510688:0.619789:0.037831:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869201 ES:SE:LP:AF:ID  0.00689072:0.00284038:1.82391:0.869201:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869258 ES:SE:LP:AF:ID  0.00683092:0.00284113:1.79588:0.869258:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.0378   ES:SE:LP:AF:ID  -0.00623311:0.00512755:0.657577:0.0378:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869188 ES:SE:LP:AF:ID  0.00690317:0.00284016:1.82391:0.869188:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005109 ES:SE:LP:AF:ID  0.0128293:0.0146391:0.420216:0.005109:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005083 ES:SE:LP:AF:ID  0.012696:0.0146689:0.408935:0.005083:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837863 ES:SE:LP:AF:ID  0.00769694:0.0026448:2.4437:0.837863:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037803 ES:SE:LP:AF:ID  -0.0061415:0.00513549:0.638272:0.037803:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838504 ES:SE:LP:AF:ID  0.00780214:0.00265267:2.48149:0.838504:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013864 ES:SE:LP:AF:ID  0.00501862:0.00924402:0.229148:0.013864:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005357 ES:SE:LP:AF:ID  0.0161834:0.0145964:0.568636:0.005357:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839688 ES:SE:LP:AF:ID  0.00731775:0.00268835:2.18709:0.839688:rs3131965