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-1070/UKB-b-1070_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1070/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1070/UKB-b-1070_data.vcf.gz ...
Read summary statistics for 9793768 SNPs.
Dropped 14239 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, 1289028 SNPs remain.
After merging with regression SNP LD, 1289028 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0125 (0.0016)
Lambda GC: 1.1103
Mean Chi^2: 1.123
Intercept: 1.0435 (0.0062)
Ratio: 0.3534 (0.0507)
Analysis finished at Thu Oct 17 14:42:05 2019
Total time elapsed: 1.0m:46.16s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9497,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 3,
    "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": 180955,
    "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": 1289028,
    "ldsc_nsnp_merge_regression_ld": 1289028,
    "ldsc_observed_scale_h2_beta": 0.0125,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0435,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.1103,
    "ldsc_mean_chisq": 1.123,
    "ldsc_ratio": 0.3537
}

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 9779595 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 9793768 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 8.622973e+00 5.748698e+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 7.885786e+07 5.628799e+07 828.0000000 3.258211e+07 6.948115e+07 1.145916e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.300000e-05 5.497300e-03 -0.0744201 -1.732700e-03 -1.770000e-05 1.678700e-03 8.423820e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.937700e-03 3.669000e-03 0.0011228 1.372000e-03 2.286100e-03 5.239200e-03 5.863390e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.868751e-01 2.927503e-01 0.0000000 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 4.868771e-01 2.927247e-01 0.0000000 2.292236e-01 4.829150e-01 7.403996e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.043805e-01 2.568223e-01 0.0010690 1.354700e-02 7.925600e-02 3.182130e-01 9.989310e-01 ▇▂▁▁▁
numeric AF_reference 180955 0.9815235 NA NA NA NA NA NA NA 2.074541e-01 2.483832e-01 0.0000000 1.198080e-02 1.008390e-01 3.218850e-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 0.0022450 0.0020638 0.2800000 0.2766820 0.623703 0.7821490 NA
1 54676 rs2462492 C T -0.0023129 0.0020457 0.2599998 0.2582196 0.400591 NA NA
1 86028 rs114608975 T C 0.0003897 0.0032670 0.9100000 0.9050506 0.103646 0.0277556 NA
1 91536 rs6702460 G T 0.0009325 0.0020158 0.6400000 0.6436554 0.456755 0.4207270 NA
1 234313 rs8179466 C T 0.0045593 0.0039722 0.2500000 0.2510559 0.074488 NA NA
1 534192 rs6680723 C T -0.0030942 0.0023032 0.1800002 0.1791263 0.241139 NA NA
1 546697 rs12025928 A G -0.0017201 0.0028745 0.5500004 0.5495691 0.913630 NA NA
1 693731 rs12238997 A G 0.0003501 0.0019298 0.8600001 0.8560543 0.116246 0.1417730 NA
1 705882 rs72631875 G A -0.0003284 0.0028221 0.9100000 0.9073728 0.067411 0.0315495 NA
1 706368 rs55727773 A G 0.0025855 0.0014295 0.0700003 0.0704905 0.516239 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0017349 0.0030016 0.5600000 0.5632839 0.041899 0.0473243 NA
22 51219766 rs182321900 C T -0.0117514 0.0143356 0.4100001 0.4123669 0.001852 NA NA
22 51220146 rs868950473 C T -0.0149984 0.0141724 0.2900000 0.2899268 0.001907 NA NA
22 51221190 rs369304721 G A -0.0002340 0.0029959 0.9400001 0.9377393 0.049590 NA NA
22 51221731 rs115055839 T C -0.0013408 0.0022411 0.5500004 0.5496464 0.073075 0.0625000 NA
22 51222100 rs114553188 G T -0.0004247 0.0026393 0.8700001 0.8721501 0.054317 0.0880591 NA
22 51223637 rs375798137 G A -0.0003412 0.0026518 0.9000000 0.8976057 0.053958 0.0788738 NA
22 51229805 rs9616985 T C -0.0015998 0.0022490 0.4799997 0.4768981 0.072910 0.0730831 NA
22 51232488 rs376461333 A G -0.0002969 0.0053041 0.9599999 0.9553605 0.019941 NA NA
22 51237063 rs3896457 T C -0.0001501 0.0013745 0.9100000 0.9130670 0.298217 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623703 ES:SE:LP:AF:ID  0.00224503:0.00206382:0.552842:0.623703:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400591 ES:SE:LP:AF:ID  -0.00231291:0.00204572:0.585027:0.400591:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103646 ES:SE:LP:AF:ID  0.000389706:0.00326705:0.0409586:0.103646:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456755 ES:SE:LP:AF:ID  0.000932483:0.00201577:0.19382:0.456755:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074488 ES:SE:LP:AF:ID  0.00455928:0.00397223:0.60206:0.074488:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241139 ES:SE:LP:AF:ID  -0.00309418:0.00230316:0.744727:0.241139:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91363  ES:SE:LP:AF:ID  -0.0017201:0.00287447:0.259637:0.91363:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116246 ES:SE:LP:AF:ID  0.000350064:0.0019298:0.0655015:0.116246:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067411 ES:SE:LP:AF:ID  -0.000328361:0.00282211:0.0409586:0.067411:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516239 ES:SE:LP:AF:ID  0.00258553:0.00142946:1.1549:0.516239:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032811 ES:SE:LP:AF:ID  -0.00190599:0.00361125:0.221849:0.032811:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036414 ES:SE:LP:AF:ID  -0.00113286:0.00328014:0.136677:0.036414:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036524 ES:SE:LP:AF:ID  -0.00111267:0.00326803:0.136677:0.036524:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036226 ES:SE:LP:AF:ID  -0.000920877:0.00329145:0.107905:0.036226:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016284 ES:SE:LP:AF:ID  -0.00477414:0.00507554:0.455932:0.016284:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036757 ES:SE:LP:AF:ID  -0.00121388:0.00325526:0.148742:0.036757:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036845 ES:SE:LP:AF:ID  -0.00141384:0.00324468:0.180456:0.036845:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101214 ES:SE:LP:AF:ID  -0.000298033:0.00235862:0.0457575:0.101214:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95946  ES:SE:LP:AF:ID  0.00113617:0.0031341:0.142668:0.95946:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031509 ES:SE:LP:AF:ID  0.00018521:0.00566071:0.0132283:0.031509:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053184 ES:SE:LP:AF:ID  -0.00175667:0.00451208:0.154902:0.053184:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036384 ES:SE:LP:AF:ID  -0.0012094:0.00326516:0.148742:0.036384:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036696 ES:SE:LP:AF:ID  -0.00112676:0.00323524:0.136677:0.036696:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843604 ES:SE:LP:AF:ID  0.00038324:0.00167314:0.0861861:0.843604:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056144 ES:SE:LP:AF:ID  0.00234309:0.00270127:0.408935:0.056144:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122264 ES:SE:LP:AF:ID  0.000540411:0.00183017:0.113509:0.122264:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.026004 ES:SE:LP:AF:ID  -0.000501061:0.00447208:0.0409586:0.026004:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121516 ES:SE:LP:AF:ID  0.000585857:0.00183094:0.124939:0.121516:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132307 ES:SE:LP:AF:ID  0.000392159:0.001804:0.0809219:0.132307:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01108  ES:SE:LP:AF:ID  -0.00527793:0.0065851:0.376751:0.01108:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005704 ES:SE:LP:AF:ID  0.000632581:0.00845393:0.0268721:0.005704:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00216  ES:SE:LP:AF:ID  -0.00301919:0.0146852:0.0757207:0.00216:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036613 ES:SE:LP:AF:ID  -0.000836135:0.00320286:0.102373:0.036613:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83931  ES:SE:LP:AF:ID  -0.000177374:0.00162066:0.0409586:0.83931:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838978 ES:SE:LP:AF:ID  -0.000118783:0.0016192:0.0268721:0.838978:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869942 ES:SE:LP:AF:ID  -0.000993141:0.00173695:0.244125:0.869942:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129701 ES:SE:LP:AF:ID  0.000988963:0.00174064:0.244125:0.129701:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037123 ES:SE:LP:AF:ID  -0.000587786:0.00314863:0.0705811:0.037123:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037361 ES:SE:LP:AF:ID  -0.00083868:0.00312874:0.102373:0.037361:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869329 ES:SE:LP:AF:ID  -0.000943587:0.00173381:0.229148:0.869329:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869429 ES:SE:LP:AF:ID  -0.000939476:0.0017345:0.229148:0.869429:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03731  ES:SE:LP:AF:ID  -0.000623547:0.00314308:0.0757207:0.03731:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869332 ES:SE:LP:AF:ID  -0.000944218:0.0017338:0.229148:0.869332:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005159 ES:SE:LP:AF:ID  0.00594596:0.0088454:0.30103:0.005159:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005122 ES:SE:LP:AF:ID  0.00591528:0.00887076:0.30103:0.005122:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838457 ES:SE:LP:AF:ID  -0.000102542:0.00161484:0.0222764:0.838457:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037323 ES:SE:LP:AF:ID  -0.000738132:0.00314753:0.091515:0.037323:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839091 ES:SE:LP:AF:ID  -0.000195532:0.00161942:0.0457575:0.839091:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013906 ES:SE:LP:AF:ID  -0.00590602:0.00561212:0.537602:0.013906:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005498 ES:SE:LP:AF:ID  -0.00296449:0.0087345:0.136677:0.005498:rs184270342