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-13354/UKB-b-13354_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13354/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:21 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13354/UKB-b-13354_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: 0.2766 (0.0091)
Lambda GC: 2.5944
Mean Chi^2: 3.9397
Intercept: 1.331 (0.0242)
Ratio: 0.1126 (0.0082)
Analysis finished at Thu Oct 17 14:44:06 2019
Total time elapsed: 1.0m:45.14s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 2.0012,
    "mean_EFFECT": -6.2867e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 556,
    "n_p_sig": 109098,
    "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": 0.2766,
    "ldsc_observed_scale_h2_se": 0.0091,
    "ldsc_intercept_beta": 1.331,
    "ldsc_intercept_se": 0.0242,
    "ldsc_lambda_gc": 2.5944,
    "ldsc_mean_chisq": 3.9397,
    "ldsc_ratio": 0.1126
}

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 -6.300000e-06 7.003700e-03 -0.2419760 -2.680500e-03 -5.100000e-06 2.674400e-03 1.859590e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.277700e-03 4.048700e-03 0.0011948 1.465500e-03 2.457300e-03 5.669700e-03 6.275430e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.895952e-01 3.124726e-01 0.0000000 9.200050e-02 3.400001e-01 6.600001e-01 1.000000e+00 ▇▃▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.895969e-01 3.124518e-01 0.0000000 9.204230e-02 3.403918e-01 6.570744e-01 9.999999e-01 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568614e-01 0.0009850 1.317000e-02 7.791400e-02 3.164540e-01 9.990060e-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 0.0008902 0.0021946 0.6899999 0.6850244 0.623734 0.7821490 NA
1 54676 rs2462492 C T 0.0027916 0.0021746 0.2000000 0.1992320 0.400349 NA NA
1 86028 rs114608975 T C -0.0002575 0.0034762 0.9400001 0.9409593 0.103560 0.0277556 NA
1 91536 rs6702460 G T 0.0048271 0.0021408 0.0239999 0.0241419 0.456844 0.4207270 NA
1 234313 rs8179466 C T -0.0083067 0.0042229 0.0490004 0.0491754 0.074494 NA NA
1 534192 rs6680723 C T -0.0034218 0.0024456 0.1600000 0.1617694 0.240935 NA NA
1 546697 rs12025928 A G 0.0063794 0.0030508 0.0369999 0.0365241 0.913459 NA NA
1 693731 rs12238997 A G -0.0027466 0.0020505 0.1800002 0.1804204 0.116215 0.1417730 NA
1 705882 rs72631875 G A -0.0063981 0.0030026 0.0329997 0.0330978 0.067322 0.0315495 NA
1 706368 rs55727773 A G -0.0016532 0.0015183 0.2800000 0.2762359 0.515789 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0046580 0.0032137 0.1499999 0.1472237 0.041969 0.0473243 NA
22 51219766 rs182321900 C T -0.0122395 0.0149583 0.4100001 0.4132194 0.001942 NA NA
22 51220146 rs868950473 C T -0.0134756 0.0148158 0.3599996 0.3630638 0.001991 NA NA
22 51221190 rs369304721 G A -0.0005516 0.0032079 0.8600001 0.8634708 0.049763 NA NA
22 51221731 rs115055839 T C 0.0006417 0.0023996 0.7899998 0.7891364 0.073283 0.0625000 NA
22 51222100 rs114553188 G T 0.0009495 0.0028253 0.7400005 0.7368069 0.054487 0.0880591 NA
22 51223637 rs375798137 G A 0.0009059 0.0028389 0.7499995 0.7496524 0.054116 0.0788738 NA
22 51229805 rs9616985 T C 0.0007338 0.0024082 0.7600007 0.7605838 0.073116 0.0730831 NA
22 51232488 rs376461333 A G 0.0008421 0.0056725 0.8800001 0.8819839 0.020056 NA NA
22 51237063 rs3896457 T C 0.0005014 0.0014737 0.7300002 0.7336984 0.297890 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623734 ES:SE:LP:AF:ID  0.000890174:0.00219462:0.161151:0.623734:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400349 ES:SE:LP:AF:ID  0.00279164:0.00217461:0.69897:0.400349:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10356  ES:SE:LP:AF:ID  -0.000257462:0.0034762:0.0268721:0.10356:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456844 ES:SE:LP:AF:ID  0.0048271:0.00214075:1.61979:0.456844:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074494 ES:SE:LP:AF:ID  -0.00830669:0.00422288:1.3098:0.074494:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240935 ES:SE:LP:AF:ID  -0.00342182:0.00244565:0.79588:0.240935:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913459 ES:SE:LP:AF:ID  0.0063794:0.00305082:1.4318:0.913459:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116215 ES:SE:LP:AF:ID  -0.00274662:0.00205054:0.744727:0.116215:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067322 ES:SE:LP:AF:ID  -0.00639812:0.00300255:1.48149:0.067322:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515789 ES:SE:LP:AF:ID  -0.00165319:0.00151834:0.552842:0.515789:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032986 ES:SE:LP:AF:ID  4.46983e-05:0.00382825:0.00436481:0.032986:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036598 ES:SE:LP:AF:ID  0.000132188:0.00347764:0.0132283:0.036598:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036717 ES:SE:LP:AF:ID  0.000444953:0.0034642:0.0457575:0.036717:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036413 ES:SE:LP:AF:ID  -0.000268451:0.0034894:0.0268721:0.036413:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01639  ES:SE:LP:AF:ID  -0.00102554:0.00537415:0.0705811:0.01639:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036953 ES:SE:LP:AF:ID  -0.000157419:0.00345072:0.0177288:0.036953:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037051 ES:SE:LP:AF:ID  -8.38273e-05:0.00343881:0.00877392:0.037051:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101231 ES:SE:LP:AF:ID  0.00190749:0.00250474:0.346787:0.101231:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959098 ES:SE:LP:AF:ID  0.000501343:0.00331584:0.0555173:0.959098:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031464 ES:SE:LP:AF:ID  -0.00338588:0.00601542:0.244125:0.031464:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  0.00342307:0.00478466:0.327902:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036572 ES:SE:LP:AF:ID  -0.000675815:0.0034609:0.0705811:0.036572:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03689  ES:SE:LP:AF:ID  -0.00127775:0.00342939:0.148742:0.03689:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843324 ES:SE:LP:AF:ID  0.00231501:0.00177665:0.721246:0.843324:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055858 ES:SE:LP:AF:ID  -0.0059663:0.00287715:1.42022:0.055858:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12219  ES:SE:LP:AF:ID  -0.00264238:0.00194511:0.769551:0.12219:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02573  ES:SE:LP:AF:ID  0.0035041:0.00477957:0.337242:0.02573:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121431 ES:SE:LP:AF:ID  -0.00255811:0.00194594:0.721246:0.121431:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132217 ES:SE:LP:AF:ID  -0.00267641:0.00191761:0.79588:0.132217:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011123 ES:SE:LP:AF:ID  0.0084148:0.00697634:0.638272:0.011123:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  0.00801748:0.00900004:0.431798:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002287 ES:SE:LP:AF:ID  0.00187032:0.0150678:0.0457575:0.002287:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  0.0159911:0.0246475:0.283997:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036804 ES:SE:LP:AF:ID  -0.00101099:0.00339472:0.113509:0.036804:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839053 ES:SE:LP:AF:ID  0.00217672:0.00172044:0.677781:0.839053:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838681 ES:SE:LP:AF:ID  0.00219009:0.00171856:0.69897:0.838681:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869874 ES:SE:LP:AF:ID  0.00230912:0.00184432:0.677781:0.869874:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129765 ES:SE:LP:AF:ID  -0.00248291:0.00184817:0.744727:0.129765:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037316 ES:SE:LP:AF:ID  -0.002429:0.00333719:0.327902:0.037316:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  -0.00238501:0.00331605:0.327902:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869219 ES:SE:LP:AF:ID  0.00231747:0.00184069:0.677781:0.869219:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869316 ES:SE:LP:AF:ID  0.00229935:0.00184142:0.677781:0.869316:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  -0.00236417:0.00333059:0.318759:0.037514:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869222 ES:SE:LP:AF:ID  0.00234056:0.00184065:0.69897:0.869222:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00513  ES:SE:LP:AF:ID  0.00107483:0.00943729:0.0409586:0.00513:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005096 ES:SE:LP:AF:ID  0.000815262:0.00946173:0.0315171:0.005096:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838137 ES:SE:LP:AF:ID  0.00223348:0.00171382:0.721246:0.838137:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  -0.00233429:0.00333529:0.318759:0.037527:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838769 ES:SE:LP:AF:ID  0.00230881:0.00171866:0.744727:0.838769:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  0.0155818:0.00599639:2.02687:0.013776:rs181660517