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-9093/UKB-b-9093_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9093/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9093/UKB-b-9093_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: 0.2507 (0.0079)
Lambda GC: 2.4845
Mean Chi^2: 3.6343
Intercept: 1.2857 (0.0216)
Ratio: 0.1084 (0.0082)
Analysis finished at Thu Oct 17 14:43:52 2019
Total time elapsed: 1.0m:40.91s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.92,
    "mean_EFFECT": 5.1891e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 513,
    "n_p_sig": 90628,
    "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": 0.2507,
    "ldsc_observed_scale_h2_se": 0.0079,
    "ldsc_intercept_beta": 1.2857,
    "ldsc_intercept_se": 0.0216,
    "ldsc_lambda_gc": 2.4845,
    "ldsc_mean_chisq": 3.6343,
    "ldsc_ratio": 0.1085
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 5.200000e-06 6.968700e-03 -0.2533810 -2.661000e-03 -5.800000e-06 2.655200e-03 1.678090e-01 ▁▁▆▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.322800e-03 4.091400e-03 0.0012078 1.480900e-03 2.483300e-03 5.729600e-03 6.344050e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.943736e-01 3.118442e-01 0.0000000 9.800090e-02 3.500000e-01 6.600001e-01 1.000000e+00 ▇▅▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.943769e-01 3.118239e-01 0.0000000 9.813160e-02 3.488770e-01 6.610712e-01 9.999996e-01 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035078e-01 2.568614e-01 0.0009840 1.317000e-02 7.791400e-02 3.164550e-01 9.990050e-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 0.0014254 0.0022188 0.5199996 0.5205978 0.623737 0.7821490 NA
1 54676 rs2462492 C T 0.0020169 0.0021986 0.3599996 0.3589630 0.400352 NA NA
1 86028 rs114608975 T C -0.0008500 0.0035147 0.8100000 0.8089071 0.103556 0.0277556 NA
1 91536 rs6702460 G T 0.0045234 0.0021643 0.0369999 0.0366187 0.456854 0.4207270 NA
1 234313 rs8179466 C T -0.0077281 0.0042693 0.0700003 0.0702716 0.074495 NA NA
1 534192 rs6680723 C T -0.0043485 0.0024726 0.0790005 0.0786280 0.240937 NA NA
1 546697 rs12025928 A G 0.0058588 0.0030844 0.0580003 0.0575003 0.913459 NA NA
1 693731 rs12238997 A G -0.0028924 0.0020732 0.1600000 0.1629815 0.116206 0.1417730 NA
1 705882 rs72631875 G A -0.0065000 0.0030355 0.0320000 0.0322471 0.067327 0.0315495 NA
1 706368 rs55727773 A G -0.0011082 0.0015351 0.4700002 0.4703481 0.515779 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0044444 0.0032450 0.1700000 0.1708082 0.041969 0.0473243 NA
22 51219766 rs182321900 C T -0.0107006 0.0151010 0.4799997 0.4785714 0.001943 NA NA
22 51220146 rs868950473 C T -0.0110340 0.0149572 0.4600002 0.4606938 0.001992 NA NA
22 51221190 rs369304721 G A -0.0006362 0.0032392 0.8400000 0.8442778 0.049764 NA NA
22 51221731 rs115055839 T C 0.0006781 0.0024230 0.7800007 0.7795836 0.073281 0.0625000 NA
22 51222100 rs114553188 G T 0.0003626 0.0028528 0.9000000 0.8988614 0.054486 0.0880591 NA
22 51223637 rs375798137 G A 0.0003926 0.0028666 0.8900000 0.8910537 0.054115 0.0788738 NA
22 51229805 rs9616985 T C 0.0007983 0.0024318 0.7400005 0.7427109 0.073115 0.0730831 NA
22 51232488 rs376461333 A G 0.0013086 0.0057282 0.8200001 0.8192945 0.020054 NA NA
22 51237063 rs3896457 T C 0.0002125 0.0014881 0.8900000 0.8864389 0.297906 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623737 ES:SE:LP:AF:ID  0.00142543:0.00221883:0.283997:0.623737:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400352 ES:SE:LP:AF:ID  0.00201687:0.0021986:0.443698:0.400352:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  -0.000849977:0.00351468:0.091515:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456854 ES:SE:LP:AF:ID  0.00452345:0.00216434:1.4318:0.456854:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074495 ES:SE:LP:AF:ID  -0.00772808:0.00426929:1.1549:0.074495:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240937 ES:SE:LP:AF:ID  -0.00434848:0.00247255:1.10237:0.240937:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913459 ES:SE:LP:AF:ID  0.0058588:0.00308441:1.23657:0.913459:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116206 ES:SE:LP:AF:ID  -0.00289242:0.00207325:0.79588:0.116206:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067327 ES:SE:LP:AF:ID  -0.00650004:0.00303551:1.49485:0.067327:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515779 ES:SE:LP:AF:ID  -0.00110823:0.00153513:0.327902:0.515779:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032986 ES:SE:LP:AF:ID  -0.000130793:0.0038705:0.0132283:0.032986:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036598 ES:SE:LP:AF:ID  -0.000227848:0.00351605:0.0222764:0.036598:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036716 ES:SE:LP:AF:ID  0.000183968:0.00350249:0.0177288:0.036716:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036413 ES:SE:LP:AF:ID  -0.000711375:0.00352794:0.0757207:0.036413:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016391 ES:SE:LP:AF:ID  -0.000947221:0.00543338:0.0655015:0.016391:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036953 ES:SE:LP:AF:ID  -0.000532958:0.00348884:0.0555173:0.036953:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037051 ES:SE:LP:AF:ID  -0.000427805:0.00347679:0.0457575:0.037051:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101246 ES:SE:LP:AF:ID  0.00120904:0.00253222:0.200659:0.101246:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959096 ES:SE:LP:AF:ID  0.0011521:0.00335241:0.136677:0.959096:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031463 ES:SE:LP:AF:ID  -0.00232451:0.00608137:0.154902:0.031463:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  0.00250334:0.00483832:0.221849:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036572 ES:SE:LP:AF:ID  -0.000977588:0.00349911:0.107905:0.036572:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03689  ES:SE:LP:AF:ID  -0.00158717:0.00346726:0.187087:0.03689:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843331 ES:SE:LP:AF:ID  0.00250513:0.00179632:0.79588:0.843331:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05586  ES:SE:LP:AF:ID  -0.00576526:0.00290895:1.3279:0.05586:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122183 ES:SE:LP:AF:ID  -0.00288924:0.00196665:0.853872:0.122183:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  0.00169519:0.00483216:0.136677:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121424 ES:SE:LP:AF:ID  -0.00278656:0.00196747:0.79588:0.121424:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132208 ES:SE:LP:AF:ID  -0.00273525:0.00193891:0.79588:0.132208:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011123 ES:SE:LP:AF:ID  0.00418021:0.00705339:0.259637:0.011123:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005691 ES:SE:LP:AF:ID  0.00956908:0.0091016:0.537602:0.005691:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002288 ES:SE:LP:AF:ID  0.00311673:0.015231:0.0757207:0.002288:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  0.00392817:0.0249145:0.0604807:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036804 ES:SE:LP:AF:ID  -0.000893192:0.00343223:0.102373:0.036804:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83906  ES:SE:LP:AF:ID  0.00248084:0.0017395:0.823909:0.83906:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838686 ES:SE:LP:AF:ID  0.00254914:0.00173759:0.853872:0.838686:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869879 ES:SE:LP:AF:ID  0.00275292:0.00186471:0.853872:0.869879:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12976  ES:SE:LP:AF:ID  -0.00300023:0.00186861:0.958607:0.12976:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037316 ES:SE:LP:AF:ID  -0.00234558:0.00337406:0.309804:0.037316:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  -0.00220348:0.0033527:0.29243:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869223 ES:SE:LP:AF:ID  0.0028073:0.00186104:0.886057:0.869223:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869321 ES:SE:LP:AF:ID  0.00278059:0.00186178:0.853872:0.869321:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  -0.00234649:0.0033674:0.309804:0.037514:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869226 ES:SE:LP:AF:ID  0.00283851:0.001861:0.886057:0.869226:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005131 ES:SE:LP:AF:ID  -0.00519292:0.00954281:0.229148:0.005131:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005098 ES:SE:LP:AF:ID  -0.00540407:0.00956754:0.244125:0.005098:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838143 ES:SE:LP:AF:ID  0.00258911:0.0017328:0.853872:0.838143:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  -0.00235357:0.00337216:0.309804:0.037526:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838775 ES:SE:LP:AF:ID  0.00266665:0.00173769:0.920819:0.838775:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  0.0140918:0.00606298:1.69897:0.013775:rs181660517