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-16156/UKB-b-16156_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16156/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16156/UKB-b-16156_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: 0.0074 (0.0011)
Lambda GC: 1.1118
Mean Chi^2: 1.1102
Intercept: 1.0439 (0.0068)
Ratio: 0.3978 (0.0617)
Analysis finished at Thu Oct 17 14:46:35 2019
Total time elapsed: 1.0m:40.77s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0001,
    "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": 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": 0.0074,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0439,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.1118,
    "ldsc_mean_chisq": 1.1102,
    "ldsc_ratio": 0.3984
}

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 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 1.484000e-04 8.261500e-03 -0.1434970 -2.442300e-03 4.540000e-05 2.575000e-03 1.356800e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.869200e-03 5.554700e-03 0.0016423 2.010700e-03 3.371600e-03 7.779600e-03 8.636020e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.869503e-01 2.922116e-01 0.0000002 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.869521e-01 2.921865e-01 0.0000002 2.304961e-01 4.823187e-01 7.403963e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035078e-01 2.568609e-01 0.0009990 1.316900e-02 7.791400e-02 3.164538e-01 9.990010e-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 0.0019168 0.0030222 0.5300002 0.5259223 0.623766 0.7821490 NA
1 54676 rs2462492 C T -0.0015577 0.0029940 0.5999997 0.6028763 0.400401 NA NA
1 86028 rs114608975 T C -0.0059971 0.0047868 0.2099999 0.2102675 0.103556 0.0277556 NA
1 91536 rs6702460 G T -0.0024776 0.0029480 0.4000000 0.4006580 0.456846 0.4207270 NA
1 234313 rs8179466 C T 0.0029052 0.0058126 0.6200004 0.6172162 0.074507 NA NA
1 534192 rs6680723 C T 0.0057214 0.0033674 0.0890000 0.0893081 0.240957 NA NA
1 546697 rs12025928 A G 0.0099512 0.0042010 0.0179999 0.0178486 0.913477 NA NA
1 693731 rs12238997 A G 0.0041411 0.0028220 0.1400000 0.1422499 0.116330 0.1417730 NA
1 705882 rs72631875 G A -0.0032188 0.0041353 0.4400003 0.4363463 0.067287 0.0315495 NA
1 706368 rs55727773 A G -0.0012282 0.0020904 0.5600000 0.5568511 0.515643 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0096275 0.0043866 0.0280001 0.0281796 0.041956 0.0473243 NA
22 51219766 rs182321900 C T 0.0045627 0.0204331 0.8200001 0.8233013 0.001938 NA NA
22 51220146 rs868950473 C T 0.0024045 0.0202404 0.9100000 0.9054350 0.001987 NA NA
22 51221190 rs369304721 G A 0.0054255 0.0043793 0.2200002 0.2153823 0.049733 NA NA
22 51221731 rs115055839 T C 0.0037003 0.0032755 0.2599998 0.2585986 0.073238 0.0625000 NA
22 51222100 rs114553188 G T 0.0000549 0.0038562 0.9900000 0.9886312 0.054461 0.0880591 NA
22 51223637 rs375798137 G A 0.0001392 0.0038749 0.9699999 0.9713397 0.054090 0.0788738 NA
22 51229805 rs9616985 T C 0.0037702 0.0032873 0.2500000 0.2514242 0.073073 0.0730831 NA
22 51232488 rs376461333 A G 0.0068542 0.0077444 0.3800004 0.3761305 0.020042 NA NA
22 51237063 rs3896457 T C 0.0026106 0.0020106 0.1900002 0.1941414 0.297972 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623766 ES:SE:LP:AF:ID  0.00191679:0.00302217:0.275724:0.623766:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.0015577:0.00299403:0.221849:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  -0.00599706:0.00478681:0.677781:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.00247762:0.00294798:0.39794:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074507 ES:SE:LP:AF:ID  0.00290516:0.00581265:0.207608:0.074507:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240957 ES:SE:LP:AF:ID  0.00572141:0.0033674:1.05061:0.240957:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913477 ES:SE:LP:AF:ID  0.00995121:0.00420105:1.74473:0.913477:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11633  ES:SE:LP:AF:ID  0.00414111:0.00282195:0.853872:0.11633:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067287 ES:SE:LP:AF:ID  -0.00321881:0.00413528:0.356547:0.067287:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515643 ES:SE:LP:AF:ID  -0.00122818:0.00209043:0.251812:0.515643:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033009 ES:SE:LP:AF:ID  -0.00245119:0.0052697:0.19382:0.033009:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036625 ES:SE:LP:AF:ID  -0.00184541:0.00478671:0.154902:0.036625:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036741 ES:SE:LP:AF:ID  -0.00180889:0.0047686:0.154902:0.036741:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03644  ES:SE:LP:AF:ID  -0.00123864:0.00480301:0.09691:0.03644:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016409 ES:SE:LP:AF:ID  -0.00013511:0.0073952:0.00436481:0.016409:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036981 ES:SE:LP:AF:ID  -0.00116966:0.00474969:0.091515:0.036981:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037077 ES:SE:LP:AF:ID  -0.00144851:0.00473342:0.119186:0.037077:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.1012   ES:SE:LP:AF:ID  -0.00492024:0.00344903:0.823909:0.1012:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95909  ES:SE:LP:AF:ID  -0.000500189:0.00456528:0.0409586:0.95909:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03145  ES:SE:LP:AF:ID  0.00782699:0.00828824:0.468521:0.03145:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053256 ES:SE:LP:AF:ID  -0.0119663:0.00659307:1.1549:0.053256:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  -0.000962815:0.00476413:0.0757207:0.036594:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036911 ES:SE:LP:AF:ID  -0.00130693:0.00472076:0.107905:0.036911:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843202 ES:SE:LP:AF:ID  -0.00275078:0.00244559:0.585027:0.843202:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055913 ES:SE:LP:AF:ID  0.00616335:0.00395978:0.920819:0.055913:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122313 ES:SE:LP:AF:ID  0.00399917:0.0026769:0.853872:0.122313:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025712 ES:SE:LP:AF:ID  0.0103971:0.00658487:0.958607:0.025712:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121555 ES:SE:LP:AF:ID  0.00395284:0.00267803:0.853872:0.121555:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  0.00271261:0.00263947:0.522879:0.132336:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011134 ES:SE:LP:AF:ID  -0.00133641:0.00959713:0.05061:0.011134:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005699 ES:SE:LP:AF:ID  0.00202556:0.0123901:0.0604807:0.005699:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002271 ES:SE:LP:AF:ID  0.0125247:0.0208201:0.259637:0.002271:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001031 ES:SE:LP:AF:ID  0.0151958:0.0340766:0.180456:0.001031:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036825 ES:SE:LP:AF:ID  -0.00082752:0.00467301:0.0655015:0.036825:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838943 ES:SE:LP:AF:ID  -0.00316435:0.00236838:0.744727:0.838943:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838571 ES:SE:LP:AF:ID  -0.00336816:0.00236584:0.823909:0.838571:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869774 ES:SE:LP:AF:ID  -0.00464343:0.00253862:1.17393:0.869774:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129878 ES:SE:LP:AF:ID  0.00495988:0.00254382:1.29243:0.129878:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  -0.00105886:0.00459377:0.0861861:0.037336:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03758  ES:SE:LP:AF:ID  -0.00114407:0.00456475:0.09691:0.03758:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  -0.00476843:0.00253365:1.22185:0.869115:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869213 ES:SE:LP:AF:ID  -0.00472239:0.00253465:1.20761:0.869213:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037538 ES:SE:LP:AF:ID  -0.000874095:0.00458449:0.0705811:0.037538:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  -0.00473245:0.0025336:1.20761:0.869119:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  0.020075:0.0130098:0.920819:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  0.0207436:0.0130439:0.958607:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838024 ES:SE:LP:AF:ID  -0.00322725:0.00235927:0.769551:0.838024:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  -0.000676503:0.00459097:0.0555173:0.03755:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838655 ES:SE:LP:AF:ID  -0.00333984:0.0023659:0.79588:0.838655:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  -0.00938673:0.00825891:0.585027:0.013772:rs181660517