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-2535/UKB-b-2535_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2535/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:49 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2535/UKB-b-2535_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: 0.0318 (0.0018)
Lambda GC: 1.2545
Mean Chi^2: 1.293
Intercept: 1.0092 (0.0087)
Ratio: 0.0315 (0.0295)
Analysis finished at Thu Oct 17 14:44:30 2019
Total time elapsed: 1.0m:41.31s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 40,
    "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": 0.0318,
    "ldsc_observed_scale_h2_se": 0.0018,
    "ldsc_intercept_beta": 1.0092,
    "ldsc_intercept_se": 0.0087,
    "ldsc_lambda_gc": 1.2545,
    "ldsc_mean_chisq": 1.293,
    "ldsc_ratio": 0.0314
}

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 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 5.410000e-05 5.769300e-03 -0.0938715 -1.821000e-03 1.160000e-05 1.855200e-03 1.186850e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.078500e-03 3.861200e-03 0.0011411 1.397000e-03 2.342600e-03 5.405400e-03 6.005290e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.736253e-01 2.958279e-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 4.736267e-01 2.958035e-01 0.0000000 2.106804e-01 4.648352e-01 7.295827e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035074e-01 2.568628e-01 0.0009890 1.316900e-02 7.791200e-02 3.164570e-01 9.990100e-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 0.0026480 0.0020995 0.2099999 0.2072196 0.623779 0.7821490 NA
1 54676 rs2462492 C T 0.0007117 0.0020799 0.7300002 0.7322306 0.400397 NA NA
1 86028 rs114608975 T C -0.0005588 0.0033247 0.8700001 0.8665281 0.103576 0.0277556 NA
1 91536 rs6702460 G T 0.0011123 0.0020481 0.5900000 0.5870614 0.456859 0.4207270 NA
1 234313 rs8179466 C T 0.0012581 0.0040384 0.7600007 0.7553899 0.074498 NA NA
1 534192 rs6680723 C T 0.0007412 0.0023394 0.7499995 0.7513789 0.240979 NA NA
1 546697 rs12025928 A G 0.0004413 0.0029183 0.8800001 0.8798101 0.913472 NA NA
1 693731 rs12238997 A G 0.0054627 0.0019604 0.0053001 0.0053284 0.116342 0.1417730 NA
1 705882 rs72631875 G A 0.0036591 0.0028728 0.2000000 0.2027685 0.067290 0.0315495 NA
1 706368 rs55727773 A G -0.0034396 0.0014522 0.0179999 0.0178638 0.515635 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0008609 0.0030479 0.7800007 0.7775892 0.041954 0.0473243 NA
22 51219766 rs182321900 C T 0.0133553 0.0142150 0.3500000 0.3474630 0.001934 NA NA
22 51220146 rs868950473 C T 0.0112483 0.0140787 0.4199997 0.4243144 0.001983 NA NA
22 51221190 rs369304721 G A -0.0001896 0.0030431 0.9500000 0.9503239 0.049726 NA NA
22 51221731 rs115055839 T C 0.0004800 0.0022762 0.8300000 0.8329744 0.073228 0.0625000 NA
22 51222100 rs114553188 G T -0.0014321 0.0026801 0.5900000 0.5930893 0.054449 0.0880591 NA
22 51223637 rs375798137 G A -0.0015396 0.0026930 0.5700002 0.5675294 0.054078 0.0788738 NA
22 51229805 rs9616985 T C 0.0009712 0.0022844 0.6700003 0.6707239 0.073065 0.0730831 NA
22 51232488 rs376461333 A G -0.0092862 0.0053825 0.0840001 0.0844818 0.020035 NA NA
22 51237063 rs3896457 T C 0.0007468 0.0013971 0.5900000 0.5929662 0.298007 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623779 ES:SE:LP:AF:ID  0.00264804:0.00209954:0.677781:0.623779:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400397 ES:SE:LP:AF:ID  0.000711665:0.00207992:0.136677:0.400397:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103576 ES:SE:LP:AF:ID  -0.000558776:0.00332466:0.0604807:0.103576:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  0.0011123:0.00204806:0.229148:0.456859:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074498 ES:SE:LP:AF:ID  0.00125814:0.00403845:0.119186:0.074498:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240979 ES:SE:LP:AF:ID  0.000741179:0.00233942:0.124939:0.240979:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913472 ES:SE:LP:AF:ID  0.000441282:0.00291834:0.0555173:0.913472:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116342 ES:SE:LP:AF:ID  0.00546272:0.00196044:2.27572:0.116342:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06729  ES:SE:LP:AF:ID  0.00365907:0.00287278:0.69897:0.06729:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515635 ES:SE:LP:AF:ID  -0.00343955:0.00145225:1.74473:0.515635:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033    ES:SE:LP:AF:ID  0.00248558:0.00366147:0.30103:0.033:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036616 ES:SE:LP:AF:ID  0.00150997:0.00332588:0.187087:0.036616:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036732 ES:SE:LP:AF:ID  0.00234205:0.0033133:0.318759:0.036732:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036432 ES:SE:LP:AF:ID  0.0021192:0.00333712:0.275724:0.036432:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016406 ES:SE:LP:AF:ID  0.00183035:0.00513801:0.142668:0.016406:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036971 ES:SE:LP:AF:ID  0.00234687:0.00330018:0.318759:0.036971:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  0.00195099:0.00328893:0.259637:0.037066:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101217 ES:SE:LP:AF:ID  -0.00152278:0.00239584:0.275724:0.101217:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959113 ES:SE:LP:AF:ID  -0.00237178:0.00317252:0.346787:0.959113:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031451 ES:SE:LP:AF:ID  -0.0135106:0.00575784:1.72125:0.031451:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053269 ES:SE:LP:AF:ID  -0.00436204:0.00457882:0.468521:0.053269:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036586 ES:SE:LP:AF:ID  0.00170858:0.0033102:0.21467:0.036586:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036903 ES:SE:LP:AF:ID  0.00188913:0.00327998:0.251812:0.036903:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843214 ES:SE:LP:AF:ID  -0.00492531:0.00169911:2.4318:0.843214:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055926 ES:SE:LP:AF:ID  0.00555364:0.00275071:1.36653:0.055926:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122324 ES:SE:LP:AF:ID  0.00467792:0.00185968:1.92082:0.122324:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025718 ES:SE:LP:AF:ID  0.000565239:0.00457374:0.0457575:0.025718:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121566 ES:SE:LP:AF:ID  0.00485942:0.00186047:2.04576:0.121566:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132343 ES:SE:LP:AF:ID  0.00540143:0.00183365:2.49485:0.132343:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  0.013205:0.00666835:1.31876:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005699 ES:SE:LP:AF:ID  0.00764237:0.00860646:0.431798:0.005699:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002262 ES:SE:LP:AF:ID  -0.00665431:0.0145052:0.187087:0.002262:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001026 ES:SE:LP:AF:ID  0.0222234:0.0237703:0.455932:0.001026:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036816 ES:SE:LP:AF:ID  0.00133311:0.00324695:0.167491:0.036816:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  -0.00486758:0.00164541:2.50864:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838576 ES:SE:LP:AF:ID  -0.00478262:0.00164364:2.4437:0.838576:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869764 ES:SE:LP:AF:ID  -0.00490475:0.00176369:2.26761:0.869764:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129881 ES:SE:LP:AF:ID  0.00487016:0.0017673:2.22915:0.129881:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037326 ES:SE:LP:AF:ID  0.00147783:0.00319194:0.19382:0.037326:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037569 ES:SE:LP:AF:ID  0.00151693:0.00317178:0.200659:0.037569:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  -0.00483056:0.00176024:2.21467:0.86911:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869208 ES:SE:LP:AF:ID  -0.00480603:0.00176094:2.20066:0.869208:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037528 ES:SE:LP:AF:ID  0.00152132:0.00318549:0.200659:0.037528:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  -0.0048551:0.00176021:2.23657:0.869112:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005124 ES:SE:LP:AF:ID  0.00239123:0.00903647:0.102373:0.005124:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509  ES:SE:LP:AF:ID  0.00282722:0.00906018:0.119186:0.00509:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838029 ES:SE:LP:AF:ID  -0.00489799:0.0016391:2.55284:0.838029:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  0.00157546:0.00318998:0.207608:0.03754:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83866  ES:SE:LP:AF:ID  -0.0049743:0.00164371:2.60206:0.83866:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013777 ES:SE:LP:AF:ID  -0.00773186:0.00573672:0.744727:0.013777:rs181660517