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-18167/UKB-b-18167_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18167/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18167/UKB-b-18167_data.vcf.gz ...
Read summary statistics for 9216957 SNPs.
Dropped 9806 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, 1287738 SNPs remain.
After merging with regression SNP LD, 1287738 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0285 (0.0019)
Lambda GC: 1.257
Mean Chi^2: 1.2934
Intercept: 1.0567 (0.0079)
Ratio: 0.1934 (0.0269)
Analysis finished at Thu Oct 17 14:41:58 2019
Total time elapsed: 1.0m:39.56s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9483,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 30,
    "n_p_sig": 992,
    "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": 105705,
    "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": 1287738,
    "ldsc_nsnp_merge_regression_ld": 1287738,
    "ldsc_observed_scale_h2_beta": 0.0285,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.0567,
    "ldsc_intercept_se": 0.0079,
    "ldsc_lambda_gc": 1.257,
    "ldsc_mean_chisq": 1.2934,
    "ldsc_ratio": 0.1933
}

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 9207200 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 9216957 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 8.636999e+00 5.754999e+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 7.880456e+07 5.631501e+07 828.0000000 3.248751e+07 6.938336e+07 1.145337e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.750000e-05 3.687900e-03 -0.0568437 -1.428000e-03 -1.200000e-06 1.440500e-03 4.334390e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.792900e-03 2.154100e-03 0.0009600 1.152000e-03 1.802600e-03 3.832200e-03 2.330620e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.716964e-01 2.961719e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.716971e-01 2.961478e-01 0.0000000 2.085888e-01 4.613231e-01 7.282968e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.156065e-01 2.580187e-01 0.0026730 1.832000e-02 9.504700e-02 3.391470e-01 9.973270e-01 ▇▂▁▁▁
numeric AF_reference 105705 0.9885315 NA NA NA NA NA NA NA 2.163505e-01 2.498544e-01 0.0000000 1.557510e-02 1.132190e-01 3.384580e-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 -0.0018553 0.0017679 0.2900000 0.2939741 0.623859 0.7821490 NA
1 54676 rs2462492 C T -0.0018458 0.0017497 0.2900000 0.2914602 0.400433 NA NA
1 86028 rs114608975 T C 0.0009319 0.0027974 0.7400005 0.7390409 0.103591 0.0277556 NA
1 91536 rs6702460 G T -0.0023417 0.0017234 0.1700000 0.1742301 0.456985 0.4207270 NA
1 234313 rs8179466 C T 0.0101045 0.0034010 0.0030000 0.0029683 0.074487 NA NA
1 534192 rs6680723 C T -0.0025114 0.0019695 0.2000000 0.2022631 0.240941 NA NA
1 546697 rs12025928 A G -0.0001709 0.0024539 0.9400001 0.9444868 0.913367 NA NA
1 693731 rs12238997 A G 0.0001842 0.0016501 0.9100000 0.9111385 0.116255 0.1417730 NA
1 705882 rs72631875 G A 0.0018724 0.0024164 0.4400003 0.4384043 0.067371 0.0315495 NA
1 706368 rs55727773 A G -0.0004089 0.0012224 0.7400005 0.7380073 0.515823 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0028734 0.0014750 0.0510000 0.0514075 0.137910 0.2052720 NA
22 51219387 rs9616832 T C -0.0047022 0.0019142 0.0140001 0.0140292 0.073743 0.0654952 NA
22 51219704 rs147475742 G A -0.0024994 0.0025658 0.3300000 0.3300040 0.041940 0.0473243 NA
22 51221190 rs369304721 G A -0.0054453 0.0025601 0.0329997 0.0334194 0.049742 NA NA
22 51221731 rs115055839 T C -0.0049551 0.0019153 0.0097000 0.0096778 0.073242 0.0625000 NA
22 51222100 rs114553188 G T -0.0005924 0.0022554 0.7899998 0.7928045 0.054416 0.0880591 NA
22 51223637 rs375798137 G A -0.0005999 0.0022662 0.7899998 0.7912456 0.054046 0.0788738 NA
22 51229805 rs9616985 T C -0.0049021 0.0019222 0.0109999 0.0107646 0.073074 0.0730831 NA
22 51232488 rs376461333 A G 0.0005328 0.0045285 0.9100000 0.9063466 0.020022 NA NA
22 51237063 rs3896457 T C 0.0005887 0.0011758 0.6200004 0.6166326 0.298116 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623859 ES:SE:LP:AF:ID  -0.00185529:0.00176788:0.537602:0.623859:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400433 ES:SE:LP:AF:ID  -0.0018458:0.0017497:0.537602:0.400433:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103591 ES:SE:LP:AF:ID  0.000931867:0.00279736:0.130768:0.103591:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456985 ES:SE:LP:AF:ID  -0.00234166:0.00172341:0.769551:0.456985:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074487 ES:SE:LP:AF:ID  0.0101045:0.00340104:2.52288:0.074487:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240941 ES:SE:LP:AF:ID  -0.00251142:0.00196954:0.69897:0.240941:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913367 ES:SE:LP:AF:ID  -0.00017087:0.00245391:0.0268721:0.913367:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116255 ES:SE:LP:AF:ID  0.00018416:0.00165014:0.0409586:0.116255:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067371 ES:SE:LP:AF:ID  0.00187243:0.00241638:0.356547:0.067371:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515823 ES:SE:LP:AF:ID  -0.000408868:0.00122235:0.130768:0.515823:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033015 ES:SE:LP:AF:ID  -0.00348145:0.00308014:0.585027:0.033015:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036646 ES:SE:LP:AF:ID  -0.00287606:0.00279699:0.522879:0.036646:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036754 ES:SE:LP:AF:ID  -0.00288767:0.00278684:0.522879:0.036754:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036456 ES:SE:LP:AF:ID  -0.00320434:0.00280688:0.60206:0.036456:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01642  ES:SE:LP:AF:ID  -0.0046392:0.00432177:0.552842:0.01642:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036995 ES:SE:LP:AF:ID  -0.00286655:0.00277572:0.522879:0.036995:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037089 ES:SE:LP:AF:ID  -0.00304613:0.00276635:0.568636:0.037089:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101253 ES:SE:LP:AF:ID  0.000586462:0.00201584:0.113509:0.101253:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959091 ES:SE:LP:AF:ID  0.00318359:0.0026687:0.638272:0.959091:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031473 ES:SE:LP:AF:ID  -0.00456192:0.00484175:0.455932:0.031473:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053297 ES:SE:LP:AF:ID  0.00523429:0.00385051:0.769551:0.053297:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036607 ES:SE:LP:AF:ID  -0.00364555:0.00278428:0.721246:0.036607:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036924 ES:SE:LP:AF:ID  -0.00378566:0.002759:0.769551:0.036924:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843228 ES:SE:LP:AF:ID  0.000487661:0.00142962:0.136677:0.843228:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055907 ES:SE:LP:AF:ID  0.00155743:0.002315:0.30103:0.055907:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122252 ES:SE:LP:AF:ID  0.000425432:0.00156525:0.102373:0.122252:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  -0.00138942:0.00384743:0.142668:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121499 ES:SE:LP:AF:ID  0.0003605:0.00156588:0.0861861:0.121499:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  -8.60071e-05:0.00154294:0.0177288:0.13233:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011113 ES:SE:LP:AF:ID  -0.00119879:0.00561467:0.0809219:0.011113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005698 ES:SE:LP:AF:ID  0.000284913:0.00724241:0.0132283:0.005698:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036846 ES:SE:LP:AF:ID  -0.00412515:0.00273071:0.886057:0.036846:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838958 ES:SE:LP:AF:ID  0.000444276:0.00138459:0.124939:0.838958:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838586 ES:SE:LP:AF:ID  0.000459263:0.00138304:0.130768:0.838586:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869843 ES:SE:LP:AF:ID  -0.000371215:0.00148452:0.09691:0.869843:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12981  ES:SE:LP:AF:ID  0.000217061:0.00148757:0.0555173:0.12981:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037348 ES:SE:LP:AF:ID  -0.00408609:0.00268487:0.886057:0.037348:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037591 ES:SE:LP:AF:ID  -0.00407172:0.00266799:0.886057:0.037591:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869185 ES:SE:LP:AF:ID  -0.000281407:0.00148157:0.0705811:0.869185:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869282 ES:SE:LP:AF:ID  -0.000267497:0.00148214:0.0655015:0.869282:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  -0.00422204:0.00267944:0.920819:0.03755:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869186 ES:SE:LP:AF:ID  -0.000266983:0.00148154:0.0655015:0.869186:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  -0.00232899:0.00760852:0.119186:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005085 ES:SE:LP:AF:ID  -0.0022338:0.00762873:0.113509:0.005085:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  0.000676536:0.00137918:0.207608:0.838033:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  -0.0042447:0.00268329:0.958607:0.037561:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838668 ES:SE:LP:AF:ID  0.000585313:0.00138309:0.173925:0.838668:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013744 ES:SE:LP:AF:ID  -0.00243114:0.00483349:0.21467:0.013744:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005551 ES:SE:LP:AF:ID  0.00152204:0.00744208:0.0757207:0.005551:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839778 ES:SE:LP:AF:ID  0.000898302:0.00140177:0.283997:0.839778:rs3131965