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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_100220.vcf.gz --id UKB-b:1780 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_100220.txt.gz --cohort_controls 64942 --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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}

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-1780/UKB-b-1780_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1780/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-1780/UKB-b-1780_data.vcf.gz ...
Read summary statistics for 8624970 SNPs.
Dropped 7372 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, 1285749 SNPs remain.
After merging with regression SNP LD, 1285749 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0146 (0.0063)
Lambda GC: 1.0172
Mean Chi^2: 1.0206
Intercept: 1.0017 (0.0056)
Ratio: 0.0818 (0.2702)
Analysis finished at Thu Oct 17 14:42:11 2019
Total time elapsed: 1.0m:42.43s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 83091,
    "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": 1285749,
    "ldsc_nsnp_merge_regression_ld": 1285749,
    "ldsc_observed_scale_h2_beta": 0.0146,
    "ldsc_observed_scale_h2_se": 0.0063,
    "ldsc_intercept_beta": 1.0017,
    "ldsc_intercept_se": 0.0056,
    "ldsc_lambda_gc": 1.0172,
    "ldsc_mean_chisq": 1.0206,
    "ldsc_ratio": 0.0825
}

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 8617632 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 8624970 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 8.650341e+00 5.760980e+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 7.877011e+07 5.637160e+07 828.0000000 3.238542e+07 6.929208e+07 1.145689e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.930000e-05 5.422400e-03 -0.0541772 -2.280000e-03 -3.310000e-05 2.229200e-03 6.891610e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.465800e-03 3.048300e-03 0.0017736 2.088700e-03 3.079600e-03 6.036800e-03 3.057380e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.976169e-01 2.891388e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.976160e-01 2.891109e-01 0.0000000 2.459340e-01 4.971981e-01 7.478248e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291177e-01 2.594882e-01 0.0053900 2.519000e-02 1.138980e-01 3.626280e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83091 0.9903662 NA NA NA NA NA NA NA 2.288667e-01 2.514590e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 -0.0024757 0.0032688 0.4500005 0.4488224 0.623812 0.7821490 NA
1 54676 rs2462492 C T 0.0004783 0.0032593 0.8800001 0.8833173 0.399142 NA NA
1 86028 rs114608975 T C 0.0015292 0.0051882 0.7700005 0.7681841 0.103539 0.0277556 NA
1 91536 rs6702460 G T -0.0006479 0.0032057 0.8400000 0.8398334 0.455916 0.4207270 NA
1 234313 rs8179466 C T -0.0029474 0.0063400 0.6400000 0.6420050 0.074453 NA NA
1 534192 rs6680723 C T -0.0012632 0.0036511 0.7300002 0.7293628 0.242057 NA NA
1 546697 rs12025928 A G 0.0064279 0.0045305 0.1600000 0.1559513 0.912865 NA NA
1 693731 rs12238997 A G -0.0037000 0.0030446 0.2200002 0.2242537 0.117310 0.1417730 NA
1 705882 rs72631875 G A -0.0031648 0.0044377 0.4799997 0.4757480 0.067699 0.0315495 NA
1 706368 rs55727773 A G 0.0009484 0.0022599 0.6700003 0.6747135 0.513305 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0017884 0.0027485 0.5199996 0.5152423 0.136314 0.2052720 NA
22 51219387 rs9616832 T C -0.0026096 0.0035823 0.4700002 0.4663293 0.071797 0.0654952 NA
22 51219704 rs147475742 G A -0.0056533 0.0047656 0.2399999 0.2355151 0.041188 0.0473243 NA
22 51221190 rs369304721 G A -0.0036065 0.0047993 0.4500005 0.4523705 0.048371 NA NA
22 51221731 rs115055839 T C -0.0024173 0.0035831 0.5000000 0.4999109 0.071348 0.0625000 NA
22 51222100 rs114553188 G T -0.0005960 0.0041519 0.8900000 0.8858516 0.054856 0.0880591 NA
22 51223637 rs375798137 G A -0.0011204 0.0041736 0.7899998 0.7883492 0.054476 0.0788738 NA
22 51229805 rs9616985 T C -0.0027559 0.0035942 0.4400003 0.4432165 0.071253 0.0730831 NA
22 51232488 rs376461333 A G -0.0026750 0.0082777 0.7499995 0.7465745 0.020462 NA NA
22 51237063 rs3896457 T C 0.0000054 0.0021698 1.0000000 0.9980096 0.298382 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.0024757:0.00326877:0.346787:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399142 ES:SE:LP:AF:ID  0.000478346:0.00325926:0.0555173:0.399142:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103539 ES:SE:LP:AF:ID  0.00152923:0.00518821:0.113509:0.103539:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  -0.000647899:0.00320573:0.0757207:0.455916:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074453 ES:SE:LP:AF:ID  -0.00294743:0.00633996:0.19382:0.074453:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  -0.00126319:0.00365112:0.136677:0.242057:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912865 ES:SE:LP:AF:ID  0.00642791:0.00453046:0.79588:0.912865:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11731  ES:SE:LP:AF:ID  -0.00370005:0.00304457:0.657577:0.11731:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067699 ES:SE:LP:AF:ID  -0.00316476:0.00443767:0.318759:0.067699:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513305 ES:SE:LP:AF:ID  0.00094844:0.00225987:0.173925:0.513305:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033668 ES:SE:LP:AF:ID  0.00428208:0.00563351:0.346787:0.033668:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037449 ES:SE:LP:AF:ID  0.00508301:0.00510913:0.49485:0.037449:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037634 ES:SE:LP:AF:ID  0.00467281:0.00508255:0.443698:0.037634:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037211 ES:SE:LP:AF:ID  0.00449477:0.00512899:0.420216:0.037211:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016283 ES:SE:LP:AF:ID  -0.0031308:0.00804382:0.154902:0.016283:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037851 ES:SE:LP:AF:ID  0.00402265:0.00506515:0.366532:0.037851:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037945 ES:SE:LP:AF:ID  0.00449556:0.00504909:0.431798:0.037945:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102732 ES:SE:LP:AF:ID  -0.00172171:0.00368779:0.19382:0.102732:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958099 ES:SE:LP:AF:ID  -0.00683203:0.0048766:0.79588:0.958099:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031691 ES:SE:LP:AF:ID  0.00358538:0.00892855:0.161151:0.031691:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052722 ES:SE:LP:AF:ID  0.0133953:0.00719176:1.20066:0.052722:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037439 ES:SE:LP:AF:ID  0.00428345:0.00508225:0.39794:0.037439:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037708 ES:SE:LP:AF:ID  0.00290096:0.00504015:0.251812:0.037708:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84145  ES:SE:LP:AF:ID  0.000680986:0.00263305:0.09691:0.84145:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056332 ES:SE:LP:AF:ID  -0.00408291:0.00427719:0.468521:0.056332:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123075 ES:SE:LP:AF:ID  -0.0030099:0.00289197:0.522879:0.123075:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025133 ES:SE:LP:AF:ID  0.00984277:0.00720161:0.769551:0.025133:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122328 ES:SE:LP:AF:ID  -0.00309719:0.0028929:0.552842:0.122328:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134128 ES:SE:LP:AF:ID  -0.00101401:0.00283998:0.142668:0.134128:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011559 ES:SE:LP:AF:ID  0.005017:0.0101208:0.207608:0.011559:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006101 ES:SE:LP:AF:ID  -0.000528773:0.0128522:0.0132283:0.006101:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03759  ES:SE:LP:AF:ID  0.00260727:0.00499345:0.221849:0.03759:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837035 ES:SE:LP:AF:ID  0.00122326:0.00254708:0.200659:0.837035:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836739 ES:SE:LP:AF:ID  0.000873895:0.00254521:0.136677:0.836739:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868564 ES:SE:LP:AF:ID  0.00229741:0.00273494:0.39794:0.868564:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131003 ES:SE:LP:AF:ID  -0.00191405:0.00274197:0.309804:0.131003:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038034 ES:SE:LP:AF:ID  0.00245553:0.00491523:0.207608:0.038034:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03828  ES:SE:LP:AF:ID  0.00243053:0.00488477:0.207608:0.03828:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867977 ES:SE:LP:AF:ID  0.00182363:0.00273055:0.30103:0.867977:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868051 ES:SE:LP:AF:ID  0.00179938:0.00273166:0.29243:0.868051:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038188 ES:SE:LP:AF:ID  0.00246378:0.00490733:0.207608:0.038188:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867988 ES:SE:LP:AF:ID  0.00180448:0.00273048:0.29243:0.867988:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  -0.0114891:0.0136844:0.39794:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836165 ES:SE:LP:AF:ID  0.000673601:0.00253777:0.102373:0.836165:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038192 ES:SE:LP:AF:ID  0.00252114:0.00491447:0.21467:0.038192:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836799 ES:SE:LP:AF:ID  0.000707646:0.00254472:0.107905:0.836799:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013031 ES:SE:LP:AF:ID  0.0112767:0.00920602:0.657577:0.013031:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005662 ES:SE:LP:AF:ID  -0.00630718:0.0136665:0.19382:0.005662:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838115 ES:SE:LP:AF:ID  0.00105869:0.00258053:0.167491:0.838115:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868229 ES:SE:LP:AF:ID  0.00232199:0.00272696:0.408935:0.868229:rs3115858