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-17805/UKB-b-17805_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17805/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:28 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17805/UKB-b-17805_data.vcf.gz ...
Read summary statistics for 7582681 SNPs.
Dropped 5317 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, 1277398 SNPs remain.
After merging with regression SNP LD, 1277398 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0494 (0.0035)
Lambda GC: 1.2029
Mean Chi^2: 1.2729
Intercept: 1.0322 (0.0082)
Ratio: 0.1179 (0.03)
Analysis finished at Thu Oct 17 14:41:55 2019
Total time elapsed: 1.0m:27.23s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9404,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 41,
    "n_p_sig": 2578,
    "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": 70411,
    "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": 1277398,
    "ldsc_nsnp_merge_regression_ld": 1277398,
    "ldsc_observed_scale_h2_beta": 0.0494,
    "ldsc_observed_scale_h2_se": 0.0035,
    "ldsc_intercept_beta": 1.0322,
    "ldsc_intercept_se": 0.0082,
    "ldsc_lambda_gc": 1.2029,
    "ldsc_mean_chisq": 1.2729,
    "ldsc_ratio": 0.118
}
 

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 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 7577387 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 7582681 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 8.663286e+00 5.764516e+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 7.866213e+07 5.643833e+07 828.0000000 3.219216e+07 6.909904e+07 1.145542e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.050000e-05 2.217600e-03 -0.0398236 -1.110900e-03 -8.000000e-07 1.117000e-03 3.639490e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.827300e-03 9.975000e-04 0.0009041 1.037000e-03 1.395900e-03 2.360800e-03 1.087450e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.735251e-01 2.961560e-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 4.735261e-01 2.961299e-01 0.0000000 2.107076e-01 4.644711e-01 7.306102e-01 9.999997e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.575683e-01 2.608459e-01 0.0110930 4.425200e-02 1.536770e-01 4.067520e-01 9.889070e-01 ▇▂▂▁▁
numeric AF_reference 70411 0.9907142 NA NA NA NA NA NA NA 2.564859e-01 2.526908e-01 0.0000000 4.892170e-02 1.677320e-01 4.009580e-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 0.0018930 0.0016662 0.2599998 0.2559025 0.623403 0.7821490 NA
1 54676 rs2462492 C T 0.0009522 0.0016473 0.5600000 0.5632456 0.400976 NA NA
1 86028 rs114608975 T C -0.0009745 0.0026437 0.7099994 0.7124064 0.103437 0.0277556 NA
1 91536 rs6702460 G T 0.0005588 0.0016230 0.7300002 0.7306140 0.457088 0.4207270 NA
1 234313 rs8179466 C T 0.0012556 0.0032053 0.6999999 0.6952683 0.074451 NA NA
1 534192 rs6680723 C T -0.0027538 0.0018551 0.1400000 0.1376893 0.241186 NA NA
1 546697 rs12025928 A G -0.0001900 0.0023145 0.9299999 0.9345767 0.913577 NA NA
1 693731 rs12238997 A G -0.0004944 0.0015523 0.7499995 0.7501023 0.116703 0.1417730 NA
1 705882 rs72631875 G A 0.0013058 0.0022793 0.5700002 0.5667136 0.067069 0.0315495 NA
1 706368 rs55727773 A G -0.0008098 0.0011512 0.4799997 0.4817621 0.515134 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0002828 0.0013922 0.8400000 0.8390102 0.137913 0.2052720 NA
22 51219387 rs9616832 T C 0.0001055 0.0018066 0.9500000 0.9534482 0.073612 0.0654952 NA
22 51219704 rs147475742 G A 0.0008859 0.0024210 0.7099994 0.7144094 0.041843 0.0473243 NA
22 51221190 rs369304721 G A 0.0009002 0.0024190 0.7099994 0.7097993 0.049574 NA NA
22 51221731 rs115055839 T C 0.0001884 0.0018073 0.9199999 0.9169625 0.073145 0.0625000 NA
22 51222100 rs114553188 G T 0.0008720 0.0021236 0.6800001 0.6813425 0.054643 0.0880591 NA
22 51223637 rs375798137 G A 0.0008517 0.0021337 0.6899999 0.6897638 0.054278 0.0788738 NA
22 51229805 rs9616985 T C 0.0003129 0.0018137 0.8600001 0.8630286 0.073012 0.0730831 NA
22 51232488 rs376461333 A G 0.0056324 0.0042676 0.1900002 0.1868981 0.020061 NA NA
22 51237063 rs3896457 T C 0.0013279 0.0011078 0.2300001 0.2306348 0.297860 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623403 ES:SE:LP:AF:ID  0.00189303:0.00166621:0.585027:0.623403:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400976 ES:SE:LP:AF:ID  0.000952173:0.00164728:0.251812:0.400976:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103437 ES:SE:LP:AF:ID  -0.000974548:0.00264373:0.148742:0.103437:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457088 ES:SE:LP:AF:ID  0.000558803:0.00162297:0.136677:0.457088:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074451 ES:SE:LP:AF:ID  0.00125557:0.00320531:0.154902:0.074451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241186 ES:SE:LP:AF:ID  -0.00275379:0.00185509:0.853872:0.241186:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913577 ES:SE:LP:AF:ID  -0.000189991:0.00231448:0.0315171:0.913577:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116703 ES:SE:LP:AF:ID  -0.000494424:0.00155233:0.124939:0.116703:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067069 ES:SE:LP:AF:ID  0.00130583:0.00227934:0.244125:0.067069:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515134 ES:SE:LP:AF:ID  -0.000809801:0.00115115:0.318759:0.515134:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03287  ES:SE:LP:AF:ID  -0.00439891:0.0029085:0.886057:0.03287:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03645  ES:SE:LP:AF:ID  -0.00411926:0.00264371:0.920819:0.03645:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036557 ES:SE:LP:AF:ID  -0.00416023:0.00263428:0.958607:0.036557:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036249 ES:SE:LP:AF:ID  -0.00448271:0.00265371:1.04096:0.036249:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016355 ES:SE:LP:AF:ID  -0.000470914:0.00407901:0.0409586:0.016355:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036782 ES:SE:LP:AF:ID  -0.00398288:0.00262442:0.886057:0.036782:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036873 ES:SE:LP:AF:ID  -0.00402129:0.00261568:0.920819:0.036873:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101076 ES:SE:LP:AF:ID  0.000705066:0.0019005:0.148742:0.101076:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959309 ES:SE:LP:AF:ID  0.00459282:0.00252233:1.16115:0.959309:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031432 ES:SE:LP:AF:ID  0.00604154:0.00454978:0.744727:0.031432:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053418 ES:SE:LP:AF:ID  0.00122281:0.00362095:0.130768:0.053418:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036416 ES:SE:LP:AF:ID  -0.00395406:0.00263098:0.886057:0.036416:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036745 ES:SE:LP:AF:ID  -0.00375245:0.00260706:0.823909:0.036745:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843032 ES:SE:LP:AF:ID  0.00153477:0.0013472:0.60206:0.843032:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056041 ES:SE:LP:AF:ID  0.000854422:0.00217961:0.154902:0.056041:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122705 ES:SE:LP:AF:ID  9.34879e-05:0.00147232:0.0222764:0.122705:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025586 ES:SE:LP:AF:ID  -0.00452624:0.00363497:0.677781:0.025586:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121928 ES:SE:LP:AF:ID  0.000156381:0.00147298:0.0362122:0.121928:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132582 ES:SE:LP:AF:ID  -0.00111971:0.00145283:0.356547:0.132582:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  0.00496741:0.00528808:0.455932:0.011132:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.036653 ES:SE:LP:AF:ID  -0.0034167:0.00258107:0.721246:0.036653:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838725 ES:SE:LP:AF:ID  0.000874353:0.00130401:0.30103:0.838725:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838352 ES:SE:LP:AF:ID  0.00103622:0.00130272:0.366532:0.838352:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869399 ES:SE:LP:AF:ID  -0.000278561:0.00139652:0.0757207:0.869399:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130253 ES:SE:LP:AF:ID  -1.4455e-05:0.00139962:0.00436481:0.130253:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037121 ES:SE:LP:AF:ID  -0.00323471:0.00253843:0.69897:0.037121:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037384 ES:SE:LP:AF:ID  -0.00314205:0.00252148:0.677781:0.037384:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868732 ES:SE:LP:AF:ID  -9.01406e-05:0.00139395:0.0222764:0.868732:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868802 ES:SE:LP:AF:ID  -0.000115684:0.00139443:0.0315171:0.868802:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037334 ES:SE:LP:AF:ID  -0.00327105:0.00253268:0.69897:0.037334:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868732 ES:SE:LP:AF:ID  -8.45117e-05:0.0013939:0.0222764:0.868732:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.8378   ES:SE:LP:AF:ID  0.00104527:0.00129906:0.376751:0.8378:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037347 ES:SE:LP:AF:ID  -0.00333627:0.00253648:0.721246:0.037347:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838436 ES:SE:LP:AF:ID  0.000985918:0.00130271:0.346787:0.838436:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013889 ES:SE:LP:AF:ID  -0.00291826:0.00452828:0.283997:0.013889:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839574 ES:SE:LP:AF:ID  0.000703464:0.00132018:0.229148:0.839574:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869019 ES:SE:LP:AF:ID  -0.000341075:0.00139209:0.091515:0.869019:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868559 ES:SE:LP:AF:ID  -0.000444844:0.00138859:0.124939:0.868559:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867537 ES:SE:LP:AF:ID  -0.000238894:0.00138632:0.0655015:0.867537:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868706 ES:SE:LP:AF:ID  -0.000381759:0.00138976:0.107905:0.868706:rs4951929