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-16099/UKB-b-16099_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16099/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:47 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16099/UKB-b-16099_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: 0.2545 (0.0083)
Lambda GC: 2.5252
Mean Chi^2: 3.6612
Intercept: 1.2813 (0.022)
Ratio: 0.1057 (0.0083)
Analysis finished at Thu Oct 17 14:46:30 2019
Total time elapsed: 1.0m:43.88s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.92,
    "mean_EFFECT": 7.856e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 512,
    "n_p_sig": 92696,
    "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": 0.2545,
    "ldsc_observed_scale_h2_se": 0.0083,
    "ldsc_intercept_beta": 1.2813,
    "ldsc_intercept_se": 0.022,
    "ldsc_lambda_gc": 2.5252,
    "ldsc_mean_chisq": 3.6612,
    "ldsc_ratio": 0.1057
}

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 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 8.000000e-07 7.232700e-03 -0.2202330 -2.779700e-03 -6.200000e-06 2.769100e-03 1.752710e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.485800e-03 4.245700e-03 0.0012535 1.536800e-03 2.576900e-03 5.945700e-03 6.585660e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.932424e-01 3.123243e-01 0.0000000 9.699960e-02 3.500000e-01 6.600001e-01 1.000000e+00 ▇▅▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.932439e-01 3.123030e-01 0.0000000 9.699900e-02 3.452872e-01 6.607921e-01 9.999998e-01 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035078e-01 2.568614e-01 0.0009850 1.316900e-02 7.791400e-02 3.164558e-01 9.990060e-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 0.0008833 0.0023020 0.6999999 0.7011828 0.623735 0.7821490 NA
1 54676 rs2462492 C T 0.0025592 0.0022810 0.2599998 0.2618740 0.400351 NA NA
1 86028 rs114608975 T C 0.0001742 0.0036462 0.9599999 0.9619015 0.103560 0.0277556 NA
1 91536 rs6702460 G T 0.0041966 0.0022454 0.0619998 0.0616253 0.456845 0.4207270 NA
1 234313 rs8179466 C T -0.0071048 0.0044295 0.1100001 0.1087170 0.074494 NA NA
1 534192 rs6680723 C T -0.0014990 0.0025652 0.5600000 0.5589738 0.240935 NA NA
1 546697 rs12025928 A G 0.0057410 0.0032002 0.0729995 0.0728151 0.913464 NA NA
1 693731 rs12238997 A G -0.0011246 0.0021509 0.5999997 0.6010860 0.116211 0.1417730 NA
1 705882 rs72631875 G A -0.0054475 0.0031494 0.0840001 0.0836831 0.067324 0.0315495 NA
1 706368 rs55727773 A G -0.0022463 0.0015926 0.1600000 0.1584186 0.515785 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0026430 0.0033677 0.4299995 0.4325599 0.041967 0.0473243 NA
22 51219766 rs182321900 C T -0.0180318 0.0156738 0.2500000 0.2499618 0.001942 NA NA
22 51220146 rs868950473 C T -0.0198784 0.0155245 0.2000000 0.2003857 0.001991 NA NA
22 51221190 rs369304721 G A 0.0009950 0.0033616 0.7700005 0.7672340 0.049760 NA NA
22 51221731 rs115055839 T C 0.0016949 0.0025146 0.5000000 0.5002996 0.073278 0.0625000 NA
22 51222100 rs114553188 G T 0.0005236 0.0029605 0.8600001 0.8596180 0.054490 0.0880591 NA
22 51223637 rs375798137 G A 0.0005286 0.0029748 0.8600001 0.8589571 0.054119 0.0788738 NA
22 51229805 rs9616985 T C 0.0017185 0.0025237 0.5000000 0.4959157 0.073111 0.0730831 NA
22 51232488 rs376461333 A G 0.0009955 0.0059440 0.8700001 0.8669928 0.020057 NA NA
22 51237063 rs3896457 T C 0.0011090 0.0015443 0.4700002 0.4726952 0.297897 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623735 ES:SE:LP:AF:ID  0.000883314:0.00230195:0.154902:0.623735:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400351 ES:SE:LP:AF:ID  0.00255922:0.002281:0.585027:0.400351:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10356  ES:SE:LP:AF:ID  0.000174172:0.00364624:0.0177288:0.10356:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456845 ES:SE:LP:AF:ID  0.00419665:0.00224542:1.20761:0.456845:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074494 ES:SE:LP:AF:ID  -0.00710481:0.00442947:0.958607:0.074494:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240935 ES:SE:LP:AF:ID  -0.00149904:0.00256524:0.251812:0.240935:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913464 ES:SE:LP:AF:ID  0.00574103:0.00320015:1.13668:0.913464:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116211 ES:SE:LP:AF:ID  -0.00112457:0.00215089:0.221849:0.116211:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067324 ES:SE:LP:AF:ID  -0.00544748:0.00314937:1.07572:0.067324:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515785 ES:SE:LP:AF:ID  -0.00224629:0.00159265:0.79588:0.515785:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032987 ES:SE:LP:AF:ID  -0.000825277:0.00401552:0.0757207:0.032987:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036598 ES:SE:LP:AF:ID  -0.000667415:0.00364776:0.0705811:0.036598:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036717 ES:SE:LP:AF:ID  -0.00046812:0.00363369:0.0457575:0.036717:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036414 ES:SE:LP:AF:ID  -0.00122879:0.0036601:0.130768:0.036414:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016392 ES:SE:LP:AF:ID  0.000831408:0.00563682:0.0555173:0.016392:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036954 ES:SE:LP:AF:ID  -0.000920506:0.00361953:0.09691:0.036954:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  -0.000841689:0.00360703:0.0861861:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101241 ES:SE:LP:AF:ID  0.00218855:0.00262713:0.39794:0.101241:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959097 ES:SE:LP:AF:ID  0.00125591:0.00347804:0.142668:0.959097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031462 ES:SE:LP:AF:ID  -0.000648338:0.00630983:0.0362122:0.031462:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  0.00359024:0.00501928:0.327902:0.053255:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036573 ES:SE:LP:AF:ID  -0.00173997:0.0036302:0.200659:0.036573:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  -0.00234667:0.00359714:0.29243:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843327 ES:SE:LP:AF:ID  0.0013731:0.00186358:0.337242:0.843327:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055853 ES:SE:LP:AF:ID  -0.004386:0.00301812:0.823909:0.055853:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122186 ES:SE:LP:AF:ID  -0.00115884:0.00204032:0.244125:0.122186:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  -0.000927639:0.00501329:0.0705811:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121426 ES:SE:LP:AF:ID  -0.00102223:0.00204119:0.207608:0.121426:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132212 ES:SE:LP:AF:ID  -0.00198329:0.00201149:0.49485:0.132212:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011122 ES:SE:LP:AF:ID  0.00714383:0.00731784:0.481486:0.011122:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  0.00853028:0.00944074:0.431798:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002287 ES:SE:LP:AF:ID  0.00266035:0.0158042:0.0604807:0.002287:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  0.0216134:0.0258522:0.39794:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036805 ES:SE:LP:AF:ID  -0.00224924:0.0035608:0.275724:0.036805:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839057 ES:SE:LP:AF:ID  0.00132992:0.00180464:0.337242:0.839057:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838683 ES:SE:LP:AF:ID  0.00141982:0.00180265:0.366532:0.838683:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869878 ES:SE:LP:AF:ID  0.000917492:0.00193458:0.19382:0.869878:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129762 ES:SE:LP:AF:ID  -0.0011753:0.00193862:0.267606:0.129762:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  -0.00363248:0.00350044:0.522879:0.037317:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037562 ES:SE:LP:AF:ID  -0.00359041:0.00347828:0.522879:0.037562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869222 ES:SE:LP:AF:ID  0.000975944:0.00193078:0.21467:0.869222:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86932  ES:SE:LP:AF:ID  0.000970584:0.00193154:0.207608:0.86932:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037515 ES:SE:LP:AF:ID  -0.00353797:0.00349354:0.508638:0.037515:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869225 ES:SE:LP:AF:ID  0.00100151:0.00193074:0.221849:0.869225:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005132 ES:SE:LP:AF:ID  0.000142382:0.00989732:0.00436481:0.005132:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005098 ES:SE:LP:AF:ID  -0.000121328:0.00992295:0.00436481:0.005098:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83814  ES:SE:LP:AF:ID  0.00141206:0.00179769:0.366532:0.83814:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  -0.00359552:0.00349848:0.522879:0.037527:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838772 ES:SE:LP:AF:ID  0.0014205:0.00180276:0.366532:0.838772:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  0.0135618:0.00629002:1.50864:0.013775:rs181660517