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-16698/UKB-b-16698_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16698/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16698/UKB-b-16698_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: 0.2506 (0.008)
Lambda GC: 2.4746
Mean Chi^2: 3.6322
Intercept: 1.2803 (0.0213)
Ratio: 0.1065 (0.0081)
Analysis finished at Thu Oct 17 14:46:52 2019
Total time elapsed: 1.0m:35.48s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.92,
    "mean_EFFECT": 3.1699e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 523,
    "n_p_sig": 92301,
    "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": 0.2506,
    "ldsc_observed_scale_h2_se": 0.008,
    "ldsc_intercept_beta": 1.2803,
    "ldsc_intercept_se": 0.0213,
    "ldsc_lambda_gc": 2.4746,
    "ldsc_mean_chisq": 3.6322,
    "ldsc_ratio": 0.1065
}

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 3.000000e-07 6.843600e-03 -0.2598830 -2.602600e-03 -2.500000e-06 2.600100e-03 1.611620e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.242500e-03 4.015400e-03 0.0011853 1.453400e-03 2.437100e-03 5.623100e-03 6.225720e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.947813e-01 3.116225e-01 0.0000000 9.900110e-02 3.500000e-01 6.600001e-01 1.000000e+00 ▇▅▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.947825e-01 3.116005e-01 0.0000000 9.924710e-02 3.494097e-01 6.610059e-01 1.000000e+00 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568614e-01 0.0009850 1.316900e-02 7.791400e-02 3.164550e-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 0.0015642 0.0021776 0.4700002 0.4725607 0.623737 0.7821490 NA
1 54676 rs2462492 C T 0.0019398 0.0021578 0.3700002 0.3686735 0.400347 NA NA
1 86028 rs114608975 T C -0.0015749 0.0034494 0.6499995 0.6479746 0.103558 0.0277556 NA
1 91536 rs6702460 G T 0.0047158 0.0021242 0.0259998 0.0264119 0.456845 0.4207270 NA
1 234313 rs8179466 C T -0.0074770 0.0041902 0.0739997 0.0743570 0.074494 NA NA
1 534192 rs6680723 C T -0.0039122 0.0024267 0.1100001 0.1069227 0.240935 NA NA
1 546697 rs12025928 A G 0.0063304 0.0030272 0.0369999 0.0365117 0.913461 NA NA
1 693731 rs12238997 A G -0.0030912 0.0020347 0.1299999 0.1287055 0.116210 0.1417730 NA
1 705882 rs72631875 G A -0.0067037 0.0029792 0.0239999 0.0244383 0.067325 0.0315495 NA
1 706368 rs55727773 A G -0.0020284 0.0015066 0.1800002 0.1781935 0.515779 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0051691 0.0031846 0.1000000 0.1045505 0.041969 0.0473243 NA
22 51219766 rs182321900 C T -0.0132500 0.0148210 0.3700002 0.3713210 0.001942 NA NA
22 51220146 rs868950473 C T -0.0159020 0.0146798 0.2800000 0.2786942 0.001991 NA NA
22 51221190 rs369304721 G A -0.0012444 0.0031788 0.6999999 0.6954453 0.049762 NA NA
22 51221731 rs115055839 T C -0.0001003 0.0023779 0.9699999 0.9663469 0.073281 0.0625000 NA
22 51222100 rs114553188 G T 0.0010049 0.0027996 0.7199992 0.7196468 0.054488 0.0880591 NA
22 51223637 rs375798137 G A 0.0010592 0.0028132 0.7099994 0.7065412 0.054117 0.0788738 NA
22 51229805 rs9616985 T C -0.0000353 0.0023865 0.9900000 0.9881925 0.073114 0.0730831 NA
22 51232488 rs376461333 A G 0.0024567 0.0056213 0.6600001 0.6620892 0.020055 NA NA
22 51237063 rs3896457 T C 0.0000069 0.0014604 1.0000000 0.9962302 0.297904 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623737 ES:SE:LP:AF:ID  0.00156424:0.00217764:0.327902:0.623737:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400347 ES:SE:LP:AF:ID  0.00193976:0.00215778:0.431798:0.400347:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103558 ES:SE:LP:AF:ID  -0.00157491:0.00344938:0.187087:0.103558:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456845 ES:SE:LP:AF:ID  0.00471585:0.00212416:1.58503:0.456845:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074494 ES:SE:LP:AF:ID  -0.007477:0.00419018:1.13077:0.074494:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240935 ES:SE:LP:AF:ID  -0.00391223:0.00242667:0.958607:0.240935:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913461 ES:SE:LP:AF:ID  0.00633045:0.00302721:1.4318:0.913461:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11621  ES:SE:LP:AF:ID  -0.00309117:0.0020347:0.886057:0.11621:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067325 ES:SE:LP:AF:ID  -0.00670372:0.00297921:1.61979:0.067325:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515779 ES:SE:LP:AF:ID  -0.00202842:0.00150662:0.744727:0.515779:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032987 ES:SE:LP:AF:ID  -7.59558e-05:0.00379858:0.00877392:0.032987:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036599 ES:SE:LP:AF:ID  0.000181427:0.00345071:0.0177288:0.036599:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036717 ES:SE:LP:AF:ID  0.00050669:0.00343741:0.0555173:0.036717:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036414 ES:SE:LP:AF:ID  -0.000186847:0.00346238:0.0177288:0.036414:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01639  ES:SE:LP:AF:ID  0.00271567:0.00533258:0.21467:0.01639:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036954 ES:SE:LP:AF:ID  -0.000192872:0.003424:0.0177288:0.036954:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  -6.25774e-05:0.00341218:0.00436481:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101244 ES:SE:LP:AF:ID  0.00287565:0.00248519:0.60206:0.101244:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959096 ES:SE:LP:AF:ID  0.000728199:0.00329014:0.0861861:0.959096:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031463 ES:SE:LP:AF:ID  -0.00066429:0.00596873:0.0409586:0.031463:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053252 ES:SE:LP:AF:ID  0.00319614:0.0047487:0.30103:0.053252:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036573 ES:SE:LP:AF:ID  -0.000595092:0.00343409:0.0655015:0.036573:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  -0.00112622:0.00340283:0.130768:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843326 ES:SE:LP:AF:ID  0.00261922:0.00176291:0.853872:0.843326:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055856 ES:SE:LP:AF:ID  -0.00627142:0.00285501:1.55284:0.055856:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122187 ES:SE:LP:AF:ID  -0.00310322:0.00193009:0.958607:0.122187:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  0.00257247:0.00474242:0.229148:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121427 ES:SE:LP:AF:ID  -0.00295174:0.00193092:0.886057:0.121427:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132213 ES:SE:LP:AF:ID  -0.00336602:0.00190284:1.11351:0.132213:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011122 ES:SE:LP:AF:ID  0.00705162:0.00692261:0.508638:0.011122:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  0.00742115:0.00893023:0.387216:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002287 ES:SE:LP:AF:ID  8.49864e-05:0.0149496:-0:0.002287:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  -0.00106763:0.0244542:0.0132283:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036805 ES:SE:LP:AF:ID  -0.000726141:0.00336845:0.0809219:0.036805:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839055 ES:SE:LP:AF:ID  0.00281238:0.00170715:1.00436:0.839055:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838682 ES:SE:LP:AF:ID  0.00284319:0.00170528:1.02228:0.838682:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869876 ES:SE:LP:AF:ID  0.00324927:0.00183006:1.11919:0.869876:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129763 ES:SE:LP:AF:ID  -0.00337104:0.00183389:1.18046:0.129763:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  -0.00214444:0.00331135:0.283997:0.037317:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037562 ES:SE:LP:AF:ID  -0.00207289:0.00329039:0.275724:0.037562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  0.0032396:0.00182646:1.11919:0.869221:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869318 ES:SE:LP:AF:ID  0.00322061:0.00182719:1.10791:0.869318:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037515 ES:SE:LP:AF:ID  -0.00211659:0.00330482:0.283997:0.037515:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869223 ES:SE:LP:AF:ID  0.00325971:0.00182643:1.13077:0.869223:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005132 ES:SE:LP:AF:ID  -0.010032:0.00936212:0.552842:0.005132:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005099 ES:SE:LP:AF:ID  -0.010403:0.00938636:0.568636:0.005099:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838139 ES:SE:LP:AF:ID  0.00282479:0.00170058:1.01323:0.838139:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  -0.00214666:0.00330949:0.283997:0.037527:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838771 ES:SE:LP:AF:ID  0.00294892:0.00170538:1.07572:0.838771:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  0.0124971:0.00595026:1.4437:0.013775:rs181660517