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-14525/UKB-b-14525_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14525/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:44 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14525/UKB-b-14525_data.vcf.gz ...
Read summary statistics for 6070127 SNPs.
Dropped 2843 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, 1219483 SNPs remain.
After merging with regression SNP LD, 1219483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0031 (0.0011)
Lambda GC: 1.0476
Mean Chi^2: 1.0504
Intercept: 1.0217 (0.0073)
Ratio: 0.4317 (0.1447)
Analysis finished at Thu Oct 17 14:44:54 2019
Total time elapsed: 1.0m:9.96s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9255,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -7.0549e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 15,
    "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": 55108,
    "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": 1219483,
    "ldsc_nsnp_merge_regression_ld": 1219483,
    "ldsc_observed_scale_h2_beta": 0.0031,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0217,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0476,
    "ldsc_mean_chisq": 1.0504,
    "ldsc_ratio": 0.4306
}

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 6067303 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 6070127 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 8.670113e+00 5.762044e+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 7.857986e+07 5.652158e+07 828.0000000 3.198905e+07 6.902631e+07 1.145087e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -7.000000e-07 5.057000e-04 -0.0040587 -2.995000e-04 -2.100000e-06 2.966000e-04 4.102900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.694000e-04 1.616000e-04 0.0003042 3.367000e-04 4.061000e-04 5.634000e-04 1.692500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.936885e-01 2.913216e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.936894e-01 2.912943e-01 0.0000000 2.388299e-01 4.911519e-01 7.466302e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.090108e-01 2.540071e-01 0.0322410 9.382500e-02 2.258980e-01 4.739760e-01 9.677590e-01 ▇▃▂▂▁
numeric AF_reference 55108 0.9909214 NA NA NA NA NA NA NA 3.056938e-01 2.470299e-01 0.0000000 1.028350e-01 2.338260e-01 4.646570e-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 0.0002677 0.0005599 0.6300007 0.6325841 0.623772 0.7821490 NA
1 54676 rs2462492 C T 0.0006744 0.0005546 0.2200002 0.2240129 0.400412 NA NA
1 86028 rs114608975 T C -0.0010853 0.0008868 0.2200002 0.2210292 0.103553 0.0277556 NA
1 91536 rs6702460 G T 0.0001568 0.0005461 0.7700005 0.7739840 0.456848 0.4207270 NA
1 234313 rs8179466 C T -0.0000846 0.0010769 0.9400001 0.9374133 0.074505 NA NA
1 534192 rs6680723 C T 0.0004325 0.0006238 0.4899999 0.4881276 0.240952 NA NA
1 546697 rs12025928 A G 0.0001608 0.0007783 0.8400000 0.8363342 0.913486 NA NA
1 693731 rs12238997 A G -0.0001245 0.0005228 0.8100000 0.8118125 0.116325 0.1417730 NA
1 705882 rs72631875 G A -0.0006974 0.0007662 0.3599996 0.3627129 0.067271 0.0315495 NA
1 706368 rs55727773 A G -0.0006376 0.0003872 0.1000000 0.0996710 0.515613 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0007723 0.0006052 0.2000000 0.2019381 0.073606 0.0826677 NA
22 51219006 rs28729663 G A -0.0007735 0.0004672 0.0980009 0.0977884 0.137928 0.2052720 NA
22 51219387 rs9616832 T C -0.0008277 0.0006064 0.1700000 0.1723110 0.073729 0.0654952 NA
22 51219704 rs147475742 G A -0.0007464 0.0008126 0.3599996 0.3582781 0.041952 0.0473243 NA
22 51221190 rs369304721 G A -0.0008596 0.0008113 0.2900000 0.2893904 0.049719 NA NA
22 51221731 rs115055839 T C -0.0008055 0.0006068 0.1800002 0.1843435 0.073220 0.0625000 NA
22 51222100 rs114553188 G T -0.0004247 0.0007143 0.5500004 0.5521215 0.054462 0.0880591 NA
22 51223637 rs375798137 G A -0.0004402 0.0007178 0.5400003 0.5397352 0.054091 0.0788738 NA
22 51229805 rs9616985 T C -0.0008243 0.0006090 0.1800002 0.1758873 0.073056 0.0730831 NA
22 51237063 rs3896457 T C 0.0002952 0.0003724 0.4299995 0.4279382 0.297948 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  0.000267689:0.00055991:0.200659:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400412 ES:SE:LP:AF:ID  0.000674382:0.000554624:0.657577:0.400412:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103553 ES:SE:LP:AF:ID  -0.00108531:0.000886839:0.657577:0.103553:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456848 ES:SE:LP:AF:ID  0.000156828:0.00054612:0.113509:0.456848:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074505 ES:SE:LP:AF:ID  -8.4562e-05:0.00107693:0.0268721:0.074505:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240952 ES:SE:LP:AF:ID  0.000432466:0.000623788:0.309804:0.240952:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913486 ES:SE:LP:AF:ID  0.000160781:0.000778281:0.0757207:0.913486:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  -0.000124466:0.000522772:0.091515:0.116325:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067271 ES:SE:LP:AF:ID  -0.000697363:0.000766158:0.443698:0.067271:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515613 ES:SE:LP:AF:ID  -0.00063757:0.000387239:1:0.515613:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033014 ES:SE:LP:AF:ID  0.000886742:0.000976124:0.443698:0.033014:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036629 ES:SE:LP:AF:ID  0.000599869:0.000886664:0.30103:0.036629:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036744 ES:SE:LP:AF:ID  0.000646922:0.000883326:0.337242:0.036744:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036444 ES:SE:LP:AF:ID  0.00054964:0.000889683:0.267606:0.036444:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036984 ES:SE:LP:AF:ID  0.000737726:0.000879825:0.39794:0.036984:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037082 ES:SE:LP:AF:ID  0.000748502:0.000876799:0.408935:0.037082:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10123  ES:SE:LP:AF:ID  0.001239:0.000638833:1.284:0.10123:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959088 ES:SE:LP:AF:ID  -0.000439814:0.000845695:0.221849:0.959088:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.05326  ES:SE:LP:AF:ID  -0.00237352:0.00122116:1.284:0.05326:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036599 ES:SE:LP:AF:ID  0.000603605:0.000882499:0.309804:0.036599:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036915 ES:SE:LP:AF:ID  0.000690325:0.000874462:0.366532:0.036915:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843195 ES:SE:LP:AF:ID  -0.000214682:0.000453036:0.19382:0.843195:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055916 ES:SE:LP:AF:ID  -0.000237312:0.000733553:0.124939:0.055916:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122315 ES:SE:LP:AF:ID  3.89843e-06:0.000495895:0.00436481:0.122315:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121558 ES:SE:LP:AF:ID  7.88126e-05:0.000496103:0.0604807:0.121558:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132342 ES:SE:LP:AF:ID  0.000186139:0.000488957:0.154902:0.132342:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.03683  ES:SE:LP:AF:ID  0.000563192:0.000865626:0.283997:0.03683:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838934 ES:SE:LP:AF:ID  -0.000280888:0.000438725:0.283997:0.838934:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838563 ES:SE:LP:AF:ID  -0.0002729:0.000438253:0.275724:0.838563:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869771 ES:SE:LP:AF:ID  -0.000139316:0.000470274:0.113509:0.869771:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129882 ES:SE:LP:AF:ID  9.87995e-05:0.000471231:0.0809219:0.129882:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037342 ES:SE:LP:AF:ID  0.000658429:0.000850945:0.356547:0.037342:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037585 ES:SE:LP:AF:ID  0.000590023:0.000845569:0.309804:0.037585:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  -0.000119648:0.00046935:0.09691:0.869112:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86921  ES:SE:LP:AF:ID  -0.000122617:0.000469537:0.102373:0.86921:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037544 ES:SE:LP:AF:ID  0.000608233:0.000849226:0.327902:0.037544:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  -0.000111501:0.000469341:0.091515:0.869115:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838014 ES:SE:LP:AF:ID  -0.000247755:0.000437034:0.244125:0.838014:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037557 ES:SE:LP:AF:ID  0.000634696:0.000850415:0.337242:0.037557:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838645 ES:SE:LP:AF:ID  -0.000267709:0.000438261:0.267606:0.838645:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839756 ES:SE:LP:AF:ID  -0.00030607:0.000444188:0.309804:0.839756:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869395 ES:SE:LP:AF:ID  -0.00013476:0.000468799:0.113509:0.869395:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868941 ES:SE:LP:AF:ID  -0.000147228:0.000467619:0.124939:0.868941:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867892 ES:SE:LP:AF:ID  -0.000103341:0.000466719:0.0861861:0.867892:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869084 ES:SE:LP:AF:ID  -0.00014587:0.000468002:0.119186:0.869084:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869093 ES:SE:LP:AF:ID  -0.000146236:0.000468038:0.124939:0.869093:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000147222:0.000468049:0.124939:0.869101:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869578 ES:SE:LP:AF:ID  -0.000145926:0.000469335:0.119186:0.869578:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037607 ES:SE:LP:AF:ID  0.000696997:0.000845425:0.387216:0.037607:rs114525117
1   760912  rs1048488   C   T   .   PASS    AF=0.838294 ES:SE:LP:AF:ID  -0.00025321:0.000436203:0.251812:0.838294:rs1048488