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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_21001.vcf.gz --id UKB-b:19953 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_21001.txt.gz --cohort_controls 461460 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-19953/ukb-b-19953.vcf.gz; Date=Sun May 10 12:42:39 2020"
}
 

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-19953/UKB-b-19953_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19953/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:58 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19953/UKB-b-19953_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: 0.2332 (0.0073)
Lambda GC: 2.4891
Mean Chi^2: 3.3813
Intercept: 1.1909 (0.0168)
Ratio: 0.0802 (0.0071)
Analysis finished at Thu Oct 17 14:43:43 2019
Total time elapsed: 1.0m:44.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.92,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 458,
    "n_p_sig": 69096,
    "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": 0.2332,
    "ldsc_observed_scale_h2_se": 0.0073,
    "ldsc_intercept_beta": 1.1909,
    "ldsc_intercept_se": 0.0168,
    "ldsc_lambda_gc": 2.4891,
    "ldsc_mean_chisq": 3.3813,
    "ldsc_ratio": 0.0802
}
 

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 5.300000e-05 1.083130e-02 -0.2492440 -4.165100e-03 7.700000e-06 4.207500e-03 1.809370e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.812200e-03 6.447500e-03 0.0019027 2.333800e-03 3.913400e-03 9.029200e-03 1.001310e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.946199e-01 3.116705e-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 3.946221e-01 3.116499e-01 0.0000000 9.906580e-02 3.488897e-01 6.615598e-01 1.000000e+00 ▇▃▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035077e-01 2.568614e-01 0.0009930 1.317000e-02 7.791400e-02 3.164560e-01 9.990080e-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 0.0010389 0.0034984 0.7700005 0.7664894 0.623764 0.7821490 NA
1 54676 rs2462492 C T 0.0021460 0.0034658 0.5400003 0.5357888 0.400407 NA NA
1 86028 rs114608975 T C 0.0069251 0.0055411 0.2099999 0.2113806 0.103550 0.0277556 NA
1 91536 rs6702460 G T 0.0041051 0.0034125 0.2300001 0.2289874 0.456845 0.4207270 NA
1 234313 rs8179466 C T -0.0120947 0.0067288 0.0719996 0.0722629 0.074497 NA NA
1 534192 rs6680723 C T 0.0003343 0.0038979 0.9299999 0.9316496 0.240940 NA NA
1 546697 rs12025928 A G -0.0005041 0.0048622 0.9199999 0.9174300 0.913458 NA NA
1 693731 rs12238997 A G -0.0004714 0.0032674 0.8900000 0.8852777 0.116281 0.1417730 NA
1 705882 rs72631875 G A 0.0011474 0.0047867 0.8100000 0.8105534 0.067302 0.0315495 NA
1 706368 rs55727773 A G -0.0003037 0.0024198 0.9000000 0.9001199 0.515705 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0021638 0.0051104 0.6700003 0.6719921 0.041948 0.0473243 NA
22 51219766 rs182321900 C T -0.0025239 0.0238146 0.9199999 0.9155969 0.001936 NA NA
22 51220146 rs868950473 C T -0.0053662 0.0235893 0.8200001 0.8200470 0.001985 NA NA
22 51221190 rs369304721 G A 0.0031475 0.0051023 0.5400003 0.5373165 0.049729 NA NA
22 51221731 rs115055839 T C 0.0045989 0.0038159 0.2300001 0.2281262 0.073237 0.0625000 NA
22 51222100 rs114553188 G T -0.0004741 0.0044918 0.9199999 0.9159352 0.054474 0.0880591 NA
22 51223637 rs375798137 G A -0.0003516 0.0045135 0.9400001 0.9379070 0.054102 0.0788738 NA
22 51229805 rs9616985 T C 0.0044404 0.0038297 0.2500000 0.2462752 0.073071 0.0730831 NA
22 51232488 rs376461333 A G 0.0032650 0.0090184 0.7199992 0.7173211 0.020052 NA NA
22 51237063 rs3896457 T C 0.0051138 0.0023424 0.0290001 0.0290227 0.297905 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.00103892:0.0034984:0.113509:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  0.00214602:0.00346583:0.267606:0.400407:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10355  ES:SE:LP:AF:ID  0.00692512:0.00554108:0.677781:0.10355:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456845 ES:SE:LP:AF:ID  0.00410514:0.0034125:0.638272:0.456845:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074497 ES:SE:LP:AF:ID  -0.0120947:0.00672878:1.14267:0.074497:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24094  ES:SE:LP:AF:ID  0.000334321:0.0038979:0.0315171:0.24094:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913458 ES:SE:LP:AF:ID  -0.000504077:0.00486225:0.0362122:0.913458:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116281 ES:SE:LP:AF:ID  -0.00047142:0.00326735:0.05061:0.116281:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067302 ES:SE:LP:AF:ID  0.00114744:0.00478674:0.091515:0.067302:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515705 ES:SE:LP:AF:ID  -0.00030371:0.00241981:0.0457575:0.515705:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033007 ES:SE:LP:AF:ID  0.00185715:0.00610021:0.119186:0.033007:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036622 ES:SE:LP:AF:ID  0.00115093:0.00554111:0.0757207:0.036622:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03674  ES:SE:LP:AF:ID  0.00141515:0.00551996:0.09691:0.03674:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036439 ES:SE:LP:AF:ID  9.67154e-05:0.00555979:0.00436481:0.036439:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016397 ES:SE:LP:AF:ID  -0.00305442:0.00856376:0.142668:0.016397:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036978 ES:SE:LP:AF:ID  0.000709829:0.00549827:0.0457575:0.036978:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037075 ES:SE:LP:AF:ID  0.000512106:0.0054794:0.0315171:0.037075:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101205 ES:SE:LP:AF:ID  0.00167835:0.00399248:0.173925:0.101205:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959089 ES:SE:LP:AF:ID  0.000396146:0.00528462:0.0268721:0.959089:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  0.00601786:0.0095932:0.275724:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053249 ES:SE:LP:AF:ID  -0.00139956:0.00763279:0.0705811:0.053249:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036596 ES:SE:LP:AF:ID  -5.81846e-05:0.00551461:0.00436481:0.036596:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036913 ES:SE:LP:AF:ID  -0.0012656:0.00546443:0.0861861:0.036913:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843254 ES:SE:LP:AF:ID  0.000984938:0.00283131:0.136677:0.843254:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055886 ES:SE:LP:AF:ID  -0.00969616:0.00458477:1.46852:0.055886:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122255 ES:SE:LP:AF:ID  -0.000680229:0.00309938:0.0809219:0.122255:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025719 ES:SE:LP:AF:ID  -0.00847226:0.00762133:0.568636:0.025719:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121497 ES:SE:LP:AF:ID  -0.000379714:0.00310068:0.0457575:0.121497:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132297 ES:SE:LP:AF:ID  -0.000914003:0.00305582:0.119186:0.132297:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  -0.00178878:0.0111102:0.0604807:0.011132:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005695 ES:SE:LP:AF:ID  0.0218699:0.0143458:0.886057:0.005695:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002275 ES:SE:LP:AF:ID  0.011722:0.0240777:0.200659:0.002275:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001031 ES:SE:LP:AF:ID  -0.00367847:0.0394423:0.0315171:0.001031:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036829 ES:SE:LP:AF:ID  0.000182607:0.0054091:0.0132283:0.036829:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838993 ES:SE:LP:AF:ID  0.000915797:0.00274194:0.130768:0.838993:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838624 ES:SE:LP:AF:ID  0.00133006:0.00273898:0.200659:0.838624:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86983  ES:SE:LP:AF:ID  0.000410906:0.00293925:0.05061:0.86983:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129815 ES:SE:LP:AF:ID  -0.00134096:0.00294532:0.187087:0.129815:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03734  ES:SE:LP:AF:ID  -0.00128345:0.00531746:0.091515:0.03734:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037582 ES:SE:LP:AF:ID  -0.00108394:0.00528399:0.0757207:0.037582:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869176 ES:SE:LP:AF:ID  0.00082542:0.00293351:0.107905:0.869176:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869273 ES:SE:LP:AF:ID  0.000768575:0.00293467:0.102373:0.869273:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -0.00126684:0.00530693:0.091515:0.037539:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869178 ES:SE:LP:AF:ID  0.000854505:0.00293345:0.113509:0.869178:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00512  ES:SE:LP:AF:ID  -0.00873723:0.0150615:0.251812:0.00512:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  -0.00890754:0.0151004:0.251812:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838078 ES:SE:LP:AF:ID  0.00138116:0.00273142:0.21467:0.838078:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037551 ES:SE:LP:AF:ID  -0.00161633:0.00531444:0.119186:0.037551:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838711 ES:SE:LP:AF:ID  0.00134632:0.00273912:0.207608:0.838711:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013772 ES:SE:LP:AF:ID  0.00397392:0.00956042:0.167491:0.013772:rs181660517