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-16334/UKB-b-16334_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16334/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:00 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16334/UKB-b-16334_data.vcf.gz ...
Read summary statistics for 6217548 SNPs.
Dropped 3050 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, 1228342 SNPs remain.
After merging with regression SNP LD, 1228342 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0042 (0.0013)
Lambda GC: 1.0812
Mean Chi^2: 1.0769
Intercept: 1.0469 (0.007)
Ratio: 0.6103 (0.0904)
Analysis finished at Thu Oct 17 14:46:09 2019
Total time elapsed: 1.0m:9.35s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9274,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 3.5203e-06,
    "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": 56787,
    "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": 1228342,
    "ldsc_nsnp_merge_regression_ld": 1228342,
    "ldsc_observed_scale_h2_beta": 0.0042,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0469,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0812,
    "ldsc_mean_chisq": 1.0769,
    "ldsc_ratio": 0.6099
}

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 TRUE
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 6214518 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 6217548 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 8.668264e+00 5.762503e+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 7.859678e+07 5.651967e+07 828.0000000 3.200549e+07 6.902565e+07 1.145285e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.500000e-06 7.030000e-04 -0.0065729 -4.106000e-04 -4.000000e-07 4.132000e-04 6.764700e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.418000e-04 2.328000e-04 0.0004065 4.512000e-04 5.494000e-04 7.758000e-04 2.533200e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.884459e-01 2.911860e-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 4.884476e-01 2.911597e-01 0.0000002 2.341122e-01 4.835268e-01 7.404719e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.034258e-01 2.553068e-01 0.0290920 8.753300e-02 2.183950e-01 4.674140e-01 9.709080e-01 ▇▃▂▂▁
numeric AF_reference 56787 0.9908667 NA NA NA NA NA NA NA 3.004263e-01 2.480809e-01 0.0000000 9.684500e-02 2.266370e-01 4.584660e-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 -0.0011050 0.0007483 0.1400000 0.1397433 0.623815 0.7821490 NA
1 54676 rs2462492 C T 0.0012258 0.0007405 0.0980009 0.0978689 0.400349 NA NA
1 86028 rs114608975 T C -0.0001149 0.0011853 0.9199999 0.9227869 0.103503 0.0277556 NA
1 91536 rs6702460 G T 0.0000052 0.0007300 0.9900000 0.9943369 0.456745 0.4207270 NA
1 234313 rs8179466 C T -0.0002918 0.0014367 0.8400000 0.8390633 0.074540 NA NA
1 534192 rs6680723 C T 0.0009085 0.0008338 0.2800000 0.2758878 0.240912 NA NA
1 546697 rs12025928 A G 0.0001298 0.0010414 0.9000000 0.9007936 0.913578 NA NA
1 693731 rs12238997 A G 0.0011835 0.0006989 0.0899995 0.0904001 0.116120 0.1417730 NA
1 705882 rs72631875 G A 0.0012163 0.0010266 0.2399999 0.2361134 0.067040 0.0315495 NA
1 706368 rs55727773 A G -0.0010806 0.0005176 0.0369999 0.0368055 0.515721 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0007331 0.0008075 0.3599996 0.3640048 0.073867 0.0826677 NA
22 51219006 rs28729663 G A 0.0002241 0.0006248 0.7199992 0.7198663 0.137859 0.2052720 NA
22 51219387 rs9616832 T C 0.0007663 0.0008092 0.3400001 0.3436482 0.073996 0.0654952 NA
22 51219704 rs147475742 G A 0.0011187 0.0010844 0.2999998 0.3022804 0.042096 0.0473243 NA
22 51221190 rs369304721 G A 0.0007398 0.0010827 0.4899999 0.4944236 0.049839 NA NA
22 51221731 rs115055839 T C 0.0007501 0.0008097 0.3500000 0.3542424 0.073474 0.0625000 NA
22 51222100 rs114553188 G T -0.0002455 0.0009580 0.8000000 0.7977333 0.054167 0.0880591 NA
22 51223637 rs375798137 G A -0.0003092 0.0009626 0.7499995 0.7480233 0.053802 0.0788738 NA
22 51229805 rs9616985 T C 0.0007514 0.0008125 0.3599996 0.3550539 0.073322 0.0730831 NA
22 51237063 rs3896457 T C -0.0000252 0.0004977 0.9599999 0.9596330 0.298047 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623815 ES:SE:LP:AF:ID  -0.001105:0.000748266:0.853872:0.623815:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400349 ES:SE:LP:AF:ID  0.0012258:0.000740542:1.00877:0.400349:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103503 ES:SE:LP:AF:ID  -0.000114879:0.00118525:0.0362122:0.103503:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456745 ES:SE:LP:AF:ID  5.18103e-06:0.000729965:0.00436481:0.456745:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07454  ES:SE:LP:AF:ID  -0.000291786:0.00143672:0.0757207:0.07454:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240912 ES:SE:LP:AF:ID  0.000908542:0.000833828:0.552842:0.240912:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913578 ES:SE:LP:AF:ID  0.000129816:0.00104137:0.0457575:0.913578:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11612  ES:SE:LP:AF:ID  0.00118349:0.000698929:1.04576:0.11612:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06704  ES:SE:LP:AF:ID  0.00121626:0.00102659:0.619789:0.06704:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515721 ES:SE:LP:AF:ID  -0.00108064:0.000517569:1.4318:0.515721:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032977 ES:SE:LP:AF:ID  -0.00107663:0.0013054:0.387216:0.032977:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036622 ES:SE:LP:AF:ID  -0.00103954:0.00118497:0.420216:0.036622:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036738 ES:SE:LP:AF:ID  -0.000859601:0.00118051:0.327902:0.036738:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036448 ES:SE:LP:AF:ID  -0.00092637:0.00118885:0.356547:0.036448:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036978 ES:SE:LP:AF:ID  -0.000976516:0.00117586:0.387216:0.036978:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037081 ES:SE:LP:AF:ID  -0.000980928:0.00117172:0.39794:0.037081:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101212 ES:SE:LP:AF:ID  0.00116457:0.000854133:0.769551:0.101212:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959094 ES:SE:LP:AF:ID  0.00107653:0.00112992:0.468521:0.959094:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031466 ES:SE:LP:AF:ID  -0.00321174:0.00204826:0.920819:0.031466:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053302 ES:SE:LP:AF:ID  -0.001991:0.00163022:0.657577:0.053302:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036601 ES:SE:LP:AF:ID  -0.00120302:0.0011792:0.508638:0.036601:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036927 ES:SE:LP:AF:ID  -0.00109443:0.0011683:0.455932:0.036927:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843361 ES:SE:LP:AF:ID  -0.000888789:0.000605638:0.853872:0.843361:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055665 ES:SE:LP:AF:ID  0.000274318:0.000982187:0.107905:0.055665:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122091 ES:SE:LP:AF:ID  0.00115235:0.000663045:1.08619:0.122091:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12133  ES:SE:LP:AF:ID  0.00111094:0.000663316:1.02687:0.12133:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132131 ES:SE:LP:AF:ID  0.000478966:0.000653764:0.337242:0.132131:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036833 ES:SE:LP:AF:ID  -0.000924623:0.00115668:0.376751:0.036833:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839001 ES:SE:LP:AF:ID  -0.000814285:0.00058633:0.79588:0.839001:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838638 ES:SE:LP:AF:ID  -0.000806334:0.000585716:0.769551:0.838638:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869885 ES:SE:LP:AF:ID  -0.000958946:0.000628538:0.886057:0.869885:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12976  ES:SE:LP:AF:ID  0.000888864:0.00062979:0.79588:0.12976:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037343 ES:SE:LP:AF:ID  -0.000997818:0.0011371:0.420216:0.037343:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037575 ES:SE:LP:AF:ID  -0.000993675:0.00113013:0.420216:0.037575:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869236 ES:SE:LP:AF:ID  -0.000915298:0.000627335:0.853872:0.869236:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869337 ES:SE:LP:AF:ID  -0.000912967:0.000627596:0.823909:0.869337:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037555 ES:SE:LP:AF:ID  -0.000980474:0.00113468:0.408935:0.037555:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869239 ES:SE:LP:AF:ID  -0.000921527:0.000627331:0.853872:0.869239:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838088 ES:SE:LP:AF:ID  -0.000752413:0.000584096:0.69897:0.838088:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037564 ES:SE:LP:AF:ID  -0.00100753:0.00113641:0.420216:0.037564:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838712 ES:SE:LP:AF:ID  -0.000770576:0.000585749:0.721246:0.838712:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83981  ES:SE:LP:AF:ID  -0.000872356:0.000593596:0.853872:0.83981:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869516 ES:SE:LP:AF:ID  -0.000923124:0.000626582:0.853872:0.869516:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869043 ES:SE:LP:AF:ID  -0.000896453:0.000624959:0.823909:0.869043:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868017 ES:SE:LP:AF:ID  -0.000862989:0.000623808:0.769551:0.868017:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.8692   ES:SE:LP:AF:ID  -0.000891416:0.000625497:0.823909:0.8692:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869209 ES:SE:LP:AF:ID  -0.000891539:0.000625546:0.823909:0.869209:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869217 ES:SE:LP:AF:ID  -0.000893748:0.000625559:0.823909:0.869217:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869701 ES:SE:LP:AF:ID  -0.000935023:0.000627298:0.853872:0.869701:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.03762  ES:SE:LP:AF:ID  -0.00115754:0.0011296:0.508638:0.03762:rs114525117