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-8089/UKB-b-8089_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8089/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8089/UKB-b-8089_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: 0.0384 (0.0019)
Lambda GC: 1.3284
Mean Chi^2: 1.3945
Intercept: 1.0545 (0.008)
Ratio: 0.1383 (0.0203)
Analysis finished at Thu Oct 17 14:43:07 2019
Total time elapsed: 1.0m:57.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.2544,
    "mean_EFFECT": -7.7801e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 17,
    "n_p_sig": 1031,
    "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": 0.0384,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.0545,
    "ldsc_intercept_se": 0.008,
    "ldsc_lambda_gc": 1.3284,
    "ldsc_mean_chisq": 1.3945,
    "ldsc_ratio": 0.1381
}

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 -7.800000e-06 7.683400e-03 -0.1165520 -2.491100e-03 -1.050000e-05 2.492000e-03 2.131200e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.381900e-03 5.096700e-03 0.0015054 1.843200e-03 3.090800e-03 7.131800e-03 7.907050e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.662660e-01 2.982735e-01 0.0000000 2.000000e-01 4.500005e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.662672e-01 2.982486e-01 0.0000000 1.993854e-01 4.542501e-01 7.254693e-01 9.999997e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035072e-01 2.568643e-01 0.0009760 1.316800e-02 7.790500e-02 3.164520e-01 9.990240e-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 0.0046219 0.0027698 0.0949992 0.0951775 0.623730 0.7821490 NA
1 54676 rs2462492 C T 0.0007254 0.0027437 0.7899998 0.7914836 0.400451 NA NA
1 86028 rs114608975 T C -0.0024907 0.0043869 0.5700002 0.5701970 0.103549 0.0277556 NA
1 91536 rs6702460 G T 0.0038620 0.0027014 0.1499999 0.1528288 0.456827 0.4207270 NA
1 234313 rs8179466 C T -0.0054937 0.0053242 0.2999998 0.3021490 0.074530 NA NA
1 534192 rs6680723 C T 0.0053126 0.0030860 0.0850002 0.0851634 0.240995 NA NA
1 546697 rs12025928 A G -0.0036756 0.0038527 0.3400001 0.3400661 0.913533 NA NA
1 693731 rs12238997 A G 0.0020142 0.0025863 0.4400003 0.4360908 0.116371 0.1417730 NA
1 705882 rs72631875 G A 0.0023043 0.0037916 0.5400003 0.5433650 0.067231 0.0315495 NA
1 706368 rs55727773 A G -0.0018405 0.0019161 0.3400001 0.3367939 0.515587 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0091402 0.0040223 0.0230001 0.0230647 0.041951 0.0473243 NA
22 51219766 rs182321900 C T 0.0149324 0.0187496 0.4299995 0.4257928 0.001936 NA NA
22 51220146 rs868950473 C T 0.0099126 0.0185646 0.5900000 0.5933738 0.001986 NA NA
22 51221190 rs369304721 G A -0.0060947 0.0040169 0.1299999 0.1291961 0.049702 NA NA
22 51221731 rs115055839 T C -0.0027959 0.0030038 0.3500000 0.3519597 0.073205 0.0625000 NA
22 51222100 rs114553188 G T 0.0026303 0.0035347 0.4600002 0.4567938 0.054484 0.0880591 NA
22 51223637 rs375798137 G A 0.0026268 0.0035519 0.4600002 0.4595762 0.054112 0.0788738 NA
22 51229805 rs9616985 T C -0.0028373 0.0030147 0.3500000 0.3466189 0.073042 0.0730831 NA
22 51232488 rs376461333 A G 0.0106199 0.0070986 0.1299999 0.1346364 0.020048 NA NA
22 51237063 rs3896457 T C 0.0005192 0.0018436 0.7800007 0.7782454 0.297880 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62373  ES:SE:LP:AF:ID  0.00462194:0.00276979:1.02228:0.62373:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400451 ES:SE:LP:AF:ID  0.0007254:0.00274373:0.102373:0.400451:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -0.00249069:0.00438686:0.244125:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456827 ES:SE:LP:AF:ID  0.00386195:0.0027014:0.823909:0.456827:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07453  ES:SE:LP:AF:ID  -0.00549368:0.00532418:0.522879:0.07453:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240995 ES:SE:LP:AF:ID  0.00531258:0.00308605:1.07058:0.240995:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913533 ES:SE:LP:AF:ID  -0.0036756:0.00385269:0.468521:0.913533:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116371 ES:SE:LP:AF:ID  0.00201424:0.0025863:0.356547:0.116371:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067231 ES:SE:LP:AF:ID  0.00230429:0.00379162:0.267606:0.067231:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515587 ES:SE:LP:AF:ID  -0.00184048:0.00191613:0.468521:0.515587:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033032 ES:SE:LP:AF:ID  -0.00658446:0.00482772:0.769551:0.033032:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036653 ES:SE:LP:AF:ID  -0.00501354:0.00438495:0.60206:0.036653:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036769 ES:SE:LP:AF:ID  -0.00501353:0.00436839:0.60206:0.036769:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036468 ES:SE:LP:AF:ID  -0.00473002:0.0044:0.552842:0.036468:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016398 ES:SE:LP:AF:ID  -0.00482757:0.00677982:0.318759:0.016398:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037009 ES:SE:LP:AF:ID  -0.00532784:0.00435107:0.657577:0.037009:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037106 ES:SE:LP:AF:ID  -0.00517259:0.00433613:0.638272:0.037106:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101256 ES:SE:LP:AF:ID  -0.00279447:0.00315955:0.420216:0.101256:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959092 ES:SE:LP:AF:ID  0.00550972:0.00418412:0.721246:0.959092:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031437 ES:SE:LP:AF:ID  0.00610376:0.00760098:0.376751:0.031437:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053281 ES:SE:LP:AF:ID  0.000226079:0.00603635:0.0132283:0.053281:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036621 ES:SE:LP:AF:ID  -0.00518604:0.00436444:0.638272:0.036621:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036936 ES:SE:LP:AF:ID  -0.0057934:0.00432485:0.744727:0.036936:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843162 ES:SE:LP:AF:ID  -0.000382262:0.00224186:0.0655015:0.843162:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055981 ES:SE:LP:AF:ID  -0.00114468:0.00362683:0.124939:0.055981:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122351 ES:SE:LP:AF:ID  0.00254259:0.00245342:0.522879:0.122351:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025696 ES:SE:LP:AF:ID  -0.00895047:0.00603594:0.853872:0.025696:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121594 ES:SE:LP:AF:ID  0.00264236:0.00245443:0.552842:0.121594:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132415 ES:SE:LP:AF:ID  0.00120163:0.00241891:0.207608:0.132415:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011144 ES:SE:LP:AF:ID  0.00784131:0.0087898:0.431798:0.011144:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005722 ES:SE:LP:AF:ID  0.00401363:0.0113252:0.142668:0.005722:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002261 ES:SE:LP:AF:ID  0.0188213:0.0191336:0.481486:0.002261:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001024 ES:SE:LP:AF:ID  0.0221979:0.0313742:0.318759:0.001024:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036843 ES:SE:LP:AF:ID  -0.00507461:0.00428174:0.619789:0.036843:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838916 ES:SE:LP:AF:ID  0.000179021:0.00217113:0.0315171:0.838916:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838557 ES:SE:LP:AF:ID  0.00022862:0.0021689:0.0362122:0.838557:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869784 ES:SE:LP:AF:ID  -0.00138433:0.00232724:0.259637:0.869784:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129856 ES:SE:LP:AF:ID  0.00123355:0.00233211:0.221849:0.129856:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037349 ES:SE:LP:AF:ID  -0.00383723:0.00420953:0.443698:0.037349:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037593 ES:SE:LP:AF:ID  -0.00365891:0.00418284:0.420216:0.037593:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869141 ES:SE:LP:AF:ID  -0.00134432:0.00232283:0.251812:0.869141:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869242 ES:SE:LP:AF:ID  -0.00122466:0.00232378:0.221849:0.869242:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037549 ES:SE:LP:AF:ID  -0.00371056:0.00420111:0.420216:0.037549:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869142 ES:SE:LP:AF:ID  -0.00134977:0.00232279:0.251812:0.869142:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005112 ES:SE:LP:AF:ID  0.00208051:0.0119377:0.0655015:0.005112:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005078 ES:SE:LP:AF:ID  0.00208557:0.0119691:0.0655015:0.005078:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838023 ES:SE:LP:AF:ID  0.000154772:0.00216313:0.0268721:0.838023:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037564 ES:SE:LP:AF:ID  -0.00380886:0.00420691:0.431798:0.037564:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838653 ES:SE:LP:AF:ID  2.30134e-05:0.00216921:0.00436481:0.838653:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013778 ES:SE:LP:AF:ID  0.0044096:0.00756815:0.251812:0.013778:rs181660517