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-14177/UKB-b-14177_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14177/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:22 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14177/UKB-b-14177_data.vcf.gz ...
Read summary statistics for 9180753 SNPs.
Dropped 9582 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, 1287635 SNPs remain.
After merging with regression SNP LD, 1287635 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1112 (0.004)
Lambda GC: 1.6914
Mean Chi^2: 2.132
Intercept: 1.0976 (0.014)
Ratio: 0.0862 (0.0124)
Analysis finished at Thu Oct 17 14:45:00 2019
Total time elapsed: 1.0m:37.97s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9482,
    "inflation_factor": 1.4921,
    "mean_EFFECT": 1.2993e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 232,
    "n_p_sig": 25919,
    "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": 103163,
    "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": 1287635,
    "ldsc_nsnp_merge_regression_ld": 1287635,
    "ldsc_observed_scale_h2_beta": 0.1112,
    "ldsc_observed_scale_h2_se": 0.004,
    "ldsc_intercept_beta": 1.0976,
    "ldsc_intercept_se": 0.014,
    "ldsc_lambda_gc": 1.6914,
    "ldsc_mean_chisq": 2.132,
    "ldsc_ratio": 0.0862
}

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 9171219 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 9180753 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 8.638190e+00 5.755459e+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 7.880270e+07 5.632041e+07 828.0000000 3.247673e+07 6.937868e+07 1.145326e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.000000e-07 3.543900e-03 -0.0575352 -1.508800e-03 1.200000e-06 1.501100e-03 4.775660e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.526500e-03 1.930300e-03 0.0008776 1.051300e-03 1.638900e-03 3.467300e-03 2.133330e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.351670e-01 3.059998e-01 0.0000000 1.499999e-01 4.100001e-01 6.999999e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.351674e-01 3.059775e-01 0.0000000 1.530885e-01 4.115971e-01 6.998192e-01 1.000000e+00 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.163871e-01 2.581178e-01 0.0028180 1.868100e-02 9.615700e-02 3.405880e-01 9.971820e-01 ▇▂▁▁▁
numeric AF_reference 103163 0.9887631 NA NA NA NA NA NA NA 2.170415e-01 2.499621e-01 0.0000000 1.577480e-02 1.142170e-01 3.396570e-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 -0.0015863 0.0016130 0.3300000 0.3253876 0.623769 0.7821490 NA
1 54676 rs2462492 C T 0.0018919 0.0015979 0.2399999 0.2364031 0.400415 NA NA
1 86028 rs114608975 T C 0.0012646 0.0025548 0.6200004 0.6205991 0.103557 0.0277556 NA
1 91536 rs6702460 G T 0.0001152 0.0015733 0.9400001 0.9416365 0.456849 0.4207270 NA
1 234313 rs8179466 C T 0.0009752 0.0031018 0.7499995 0.7532223 0.074513 NA NA
1 534192 rs6680723 C T -0.0005564 0.0017973 0.7600007 0.7568659 0.240956 NA NA
1 546697 rs12025928 A G -0.0039419 0.0022420 0.0790005 0.0787152 0.913480 NA NA
1 693731 rs12238997 A G -0.0004414 0.0015061 0.7700005 0.7694436 0.116325 0.1417730 NA
1 705882 rs72631875 G A -0.0002212 0.0022070 0.9199999 0.9201573 0.067288 0.0315495 NA
1 706368 rs55727773 A G -0.0006507 0.0011157 0.5600000 0.5597618 0.515647 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0000828 0.0013488 0.9500000 0.9510737 0.137960 0.2052720 NA
22 51219387 rs9616832 T C 0.0002874 0.0017508 0.8700001 0.8696098 0.073753 0.0654952 NA
22 51219704 rs147475742 G A -0.0003209 0.0023462 0.8900000 0.8912258 0.041960 0.0473243 NA
22 51221190 rs369304721 G A 0.0006522 0.0023423 0.7800007 0.7806719 0.049736 NA NA
22 51221731 rs115055839 T C 0.0001883 0.0017519 0.9100000 0.9144075 0.073244 0.0625000 NA
22 51222100 rs114553188 G T -0.0014956 0.0020626 0.4700002 0.4684108 0.054459 0.0880591 NA
22 51223637 rs375798137 G A -0.0015779 0.0020726 0.4500005 0.4464839 0.054088 0.0788738 NA
22 51229805 rs9616985 T C 0.0002550 0.0017583 0.8800001 0.8846732 0.073079 0.0730831 NA
22 51232488 rs376461333 A G -0.0030382 0.0041424 0.4600002 0.4632945 0.020040 NA NA
22 51237063 rs3896457 T C 0.0030174 0.0010755 0.0050000 0.0050217 0.297956 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623769 ES:SE:LP:AF:ID  -0.00158627:0.00161297:0.481486:0.623769:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400415 ES:SE:LP:AF:ID  0.00189193:0.00159788:0.619789:0.400415:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  0.00126461:0.00255476:0.207608:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456849 ES:SE:LP:AF:ID  0.000115184:0.00157327:0.0268721:0.456849:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074513 ES:SE:LP:AF:ID  0.000975182:0.00310179:0.124939:0.074513:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  -0.00055643:0.00179726:0.119186:0.240956:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91348  ES:SE:LP:AF:ID  -0.00394188:0.00224201:1.10237:0.91348:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  -0.000441442:0.0015061:0.113509:0.116325:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  -0.000221219:0.00220699:0.0362122:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515647 ES:SE:LP:AF:ID  -0.000650671:0.0011157:0.251812:0.515647:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033004 ES:SE:LP:AF:ID  -0.000690642:0.00281273:0.091515:0.033004:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036621 ES:SE:LP:AF:ID  -0.00141901:0.00255483:0.236572:0.036621:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036737 ES:SE:LP:AF:ID  -0.00127245:0.00254516:0.207608:0.036737:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036437 ES:SE:LP:AF:ID  -0.00134289:0.00256349:0.221849:0.036437:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016412 ES:SE:LP:AF:ID  0.00541691:0.00394667:0.769551:0.016412:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036975 ES:SE:LP:AF:ID  -0.00125528:0.00253514:0.207608:0.036975:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037071 ES:SE:LP:AF:ID  -0.00148045:0.00252646:0.251812:0.037071:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101212 ES:SE:LP:AF:ID  -0.000640205:0.00184053:0.136677:0.101212:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959101 ES:SE:LP:AF:ID  0.00151225:0.00243683:0.275724:0.959101:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031444 ES:SE:LP:AF:ID  -0.00151562:0.00442432:0.136677:0.031444:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053258 ES:SE:LP:AF:ID  0.000753318:0.00351859:0.0809219:0.053258:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036591 ES:SE:LP:AF:ID  -0.00143794:0.00254274:0.244125:0.036591:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036907 ES:SE:LP:AF:ID  -0.00172084:0.00251958:0.309804:0.036907:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843223 ES:SE:LP:AF:ID  0.00137237:0.00130529:0.537602:0.843223:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055914 ES:SE:LP:AF:ID  -0.00242397:0.00211329:0.60206:0.055914:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122303 ES:SE:LP:AF:ID  -0.000267962:0.00142871:0.0705811:0.122303:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025718 ES:SE:LP:AF:ID  0.00203574:0.00351366:0.251812:0.025718:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121546 ES:SE:LP:AF:ID  -0.000245534:0.00142931:0.0655015:0.121546:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132322 ES:SE:LP:AF:ID  -0.00192197:0.00140874:0.769551:0.132322:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011131 ES:SE:LP:AF:ID  0.0064837:0.00512285:0.677781:0.011131:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005697 ES:SE:LP:AF:ID  0.0124997:0.00661498:1.22915:0.005697:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03682  ES:SE:LP:AF:ID  -0.00146826:0.00249421:0.251812:0.03682:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838958 ES:SE:LP:AF:ID  0.00170139:0.00126407:0.744727:0.838958:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838588 ES:SE:LP:AF:ID  0.00162133:0.00126271:0.69897:0.838588:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869784 ES:SE:LP:AF:ID  0.000827919:0.00135496:0.267606:0.869784:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129864 ES:SE:LP:AF:ID  -0.000673496:0.00135773:0.207608:0.129864:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03733  ES:SE:LP:AF:ID  -0.00109404:0.00245195:0.180456:0.03733:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037574 ES:SE:LP:AF:ID  -0.000856793:0.00243645:0.136677:0.037574:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869128 ES:SE:LP:AF:ID  0.000735455:0.00135231:0.229148:0.869128:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869226 ES:SE:LP:AF:ID  0.000739341:0.00135285:0.236572:0.869226:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037532 ES:SE:LP:AF:ID  -0.00109911:0.002447:0.187087:0.037532:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86913  ES:SE:LP:AF:ID  0.000723068:0.00135228:0.229148:0.86913:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00512  ES:SE:LP:AF:ID  -0.00915793:0.00694508:0.721246:0.00512:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005085 ES:SE:LP:AF:ID  -0.00933751:0.00696333:0.744727:0.005085:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83804  ES:SE:LP:AF:ID  0.00158167:0.0012592:0.677781:0.83804:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.00118137:0.00245045:0.200659:0.037545:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83867  ES:SE:LP:AF:ID  0.00157523:0.00126274:0.677781:0.83867:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013773 ES:SE:LP:AF:ID  -0.0088053:0.00440759:1.33724:0.013773:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005543 ES:SE:LP:AF:ID  0.000402033:0.00680265:0.0222764:0.005543:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839783 ES:SE:LP:AF:ID  0.00178169:0.00127981:0.79588:0.839783:rs3131965