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_100018.vcf.gz --id UKB-b:17406 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_100018.txt.gz --cohort_controls 62991 --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-17406/UKB-b-17406_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17406/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17406/UKB-b-17406_data.vcf.gz ...
Read summary statistics for 8580280 SNPs.
Dropped 7280 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, 1285615 SNPs remain.
After merging with regression SNP LD, 1285615 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0239 (0.0072)
Lambda GC: 1.0389
Mean Chi^2: 1.0421
Intercept: 1.0125 (0.0059)
Ratio: 0.2975 (0.1394)
Analysis finished at Thu Oct 17 14:41:58 2019
Total time elapsed: 1.0m:40.41s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.946,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 82301,
    "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": 1285615,
    "ldsc_nsnp_merge_regression_ld": 1285615,
    "ldsc_observed_scale_h2_beta": 0.0239,
    "ldsc_observed_scale_h2_se": 0.0072,
    "ldsc_intercept_beta": 1.0125,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0389,
    "ldsc_mean_chisq": 1.0421,
    "ldsc_ratio": 0.2969
}

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 8573034 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 8580280 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 8.651067e+00 5.761273e+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 7.876600e+07 5.637460e+07 828.0000000 3.237662e+07 6.928582e+07 1.145689e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.250000e-05 1.625670e-02 -0.1703420 -6.900500e-03 -1.830000e-05 6.789400e-03 1.861490e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.337320e-02 9.054200e-03 0.0053649 6.309100e-03 9.261900e-03 1.804410e-02 9.277880e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.949330e-01 2.899190e-01 0.0000001 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.949346e-01 2.898935e-01 0.0000001 2.429967e-01 4.933849e-01 7.457458e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.302323e-01 2.596115e-01 0.0055570 2.581600e-02 1.153760e-01 3.643830e-01 9.944420e-01 ▇▂▁▁▁
numeric AF_reference 82301 0.9904081 NA NA NA NA NA NA NA 2.299466e-01 2.515713e-01 0.0000000 2.416130e-02 1.317890e-01 3.612220e-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 -0.0142938 0.0098902 0.1499999 0.1483872 0.624155 0.7821490 NA
1 54676 rs2462492 C T -0.0039701 0.0098538 0.6899999 0.6870243 0.399060 NA NA
1 86028 rs114608975 T C -0.0009485 0.0157307 0.9500000 0.9519221 0.103303 0.0277556 NA
1 91536 rs6702460 G T -0.0107992 0.0096995 0.2700001 0.2655461 0.455976 0.4207270 NA
1 234313 rs8179466 C T -0.0024534 0.0191723 0.9000000 0.8981768 0.074456 NA NA
1 534192 rs6680723 C T 0.0094458 0.0110285 0.3900004 0.3917278 0.242386 NA NA
1 546697 rs12025928 A G 0.0110149 0.0137120 0.4199997 0.4217992 0.912945 NA NA
1 693731 rs12238997 A G 0.0086730 0.0091922 0.3500000 0.3454147 0.117668 0.1417730 NA
1 705882 rs72631875 G A -0.0019040 0.0134334 0.8900000 0.8872860 0.067585 0.0315495 NA
1 706368 rs55727773 A G -0.0088236 0.0068331 0.2000000 0.1965968 0.513330 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0002993 0.0083161 0.9699999 0.9712876 0.135861 0.2052720 NA
22 51219387 rs9616832 T C 0.0053229 0.0108525 0.6200004 0.6237959 0.071502 0.0654952 NA
22 51219704 rs147475742 G A 0.0014168 0.0144475 0.9199999 0.9218831 0.040979 0.0473243 NA
22 51221190 rs369304721 G A 0.0087064 0.0145408 0.5500004 0.5493370 0.048142 NA NA
22 51221731 rs115055839 T C 0.0052468 0.0108554 0.6300007 0.6288575 0.071051 0.0625000 NA
22 51222100 rs114553188 G T -0.0120447 0.0125674 0.3400001 0.3378569 0.054730 0.0880591 NA
22 51223637 rs375798137 G A -0.0115688 0.0126339 0.3599996 0.3598268 0.054347 0.0788738 NA
22 51229805 rs9616985 T C 0.0059150 0.0108871 0.5900000 0.5869183 0.070977 0.0730831 NA
22 51232488 rs376461333 A G -0.0193969 0.0250848 0.4400003 0.4393726 0.020396 NA NA
22 51237063 rs3896457 T C -0.0048798 0.0065642 0.4600002 0.4572417 0.298430 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624155 ES:SE:LP:AF:ID  -0.0142938:0.00989018:0.823909:0.624155:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39906  ES:SE:LP:AF:ID  -0.00397007:0.00985382:0.161151:0.39906:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103303 ES:SE:LP:AF:ID  -0.000948454:0.0157307:0.0222764:0.103303:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455976 ES:SE:LP:AF:ID  -0.0107992:0.00969949:0.568636:0.455976:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074456 ES:SE:LP:AF:ID  -0.00245338:0.0191723:0.0457575:0.074456:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242386 ES:SE:LP:AF:ID  0.00944578:0.0110285:0.408935:0.242386:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912945 ES:SE:LP:AF:ID  0.0110149:0.013712:0.376751:0.912945:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117668 ES:SE:LP:AF:ID  0.00867301:0.00919218:0.455932:0.117668:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067585 ES:SE:LP:AF:ID  -0.00190404:0.0134334:0.05061:0.067585:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51333  ES:SE:LP:AF:ID  -0.0088236:0.00683307:0.69897:0.51333:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033781 ES:SE:LP:AF:ID  -0.014885:0.0170128:0.420216:0.033781:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037555 ES:SE:LP:AF:ID  -0.0112915:0.0154336:0.337242:0.037555:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037743 ES:SE:LP:AF:ID  -0.0103332:0.0153526:0.30103:0.037743:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037311 ES:SE:LP:AF:ID  -0.00985829:0.015495:0.283997:0.037311:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016296 ES:SE:LP:AF:ID  0.0357138:0.0243216:0.853872:0.016296:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037959 ES:SE:LP:AF:ID  -0.00954056:0.0153006:0.275724:0.037959:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.038054 ES:SE:LP:AF:ID  -0.00863009:0.0152524:0.244125:0.038054:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102504 ES:SE:LP:AF:ID  0.0135604:0.0111589:0.657577:0.102504:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95798  ES:SE:LP:AF:ID  0.00158814:0.0147307:0.0409586:0.95798:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031705 ES:SE:LP:AF:ID  -0.00437446:0.0269734:0.0604807:0.031705:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052613 ES:SE:LP:AF:ID  0.0038673:0.0217931:0.0655015:0.052613:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037531 ES:SE:LP:AF:ID  -0.00869459:0.015356:0.244125:0.037531:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037814 ES:SE:LP:AF:ID  -0.00923295:0.0152268:0.267606:0.037814:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840986 ES:SE:LP:AF:ID  -0.00207527:0.00795415:0.102373:0.840986:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056409 ES:SE:LP:AF:ID  -0.00209519:0.0129305:0.0604807:0.056409:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123469 ES:SE:LP:AF:ID  0.00336576:0.00873264:0.154902:0.123469:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025214 ES:SE:LP:AF:ID  0.00594829:0.0217274:0.107905:0.025214:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122711 ES:SE:LP:AF:ID  0.00347623:0.00873576:0.161151:0.122711:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134575 ES:SE:LP:AF:ID  -0.00255803:0.00857705:0.113509:0.134575:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011523 ES:SE:LP:AF:ID  0.00675071:0.0306369:0.0809219:0.011523:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006108 ES:SE:LP:AF:ID  -0.0259821:0.0388389:0.30103:0.006108:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.0377   ES:SE:LP:AF:ID  -0.00941746:0.0150832:0.275724:0.0377:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836568 ES:SE:LP:AF:ID  -0.00187772:0.00769487:0.091515:0.836568:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836262 ES:SE:LP:AF:ID  -0.00226718:0.00768901:0.113509:0.836262:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868172 ES:SE:LP:AF:ID  -0.00465901:0.00826045:0.244125:0.868172:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131408 ES:SE:LP:AF:ID  0.00472983:0.00828073:0.244125:0.131408:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038153 ES:SE:LP:AF:ID  -0.0101599:0.0148442:0.309804:0.038153:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038402 ES:SE:LP:AF:ID  -0.0109375:0.0147513:0.337242:0.038402:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867573 ES:SE:LP:AF:ID  -0.0053897:0.00824691:0.29243:0.867573:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867642 ES:SE:LP:AF:ID  -0.00525414:0.00825023:0.283997:0.867642:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03831  ES:SE:LP:AF:ID  -0.010681:0.01482:0.327902:0.03831:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867585 ES:SE:LP:AF:ID  -0.00535222:0.0082467:0.283997:0.867585:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.835684 ES:SE:LP:AF:ID  -0.0029915:0.00766597:0.154902:0.835684:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038314 ES:SE:LP:AF:ID  -0.0105083:0.0148416:0.318759:0.038314:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836325 ES:SE:LP:AF:ID  -0.00323836:0.00768714:0.173925:0.836325:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013011 ES:SE:LP:AF:ID  -0.0301496:0.0279014:0.552842:0.013011:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005638 ES:SE:LP:AF:ID  0.0435036:0.0414348:0.537602:0.005638:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837634 ES:SE:LP:AF:ID  -0.00202937:0.0077948:0.102373:0.837634:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.867839 ES:SE:LP:AF:ID  -0.00507877:0.00823646:0.267606:0.867839:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867354 ES:SE:LP:AF:ID  -0.0053755:0.00821484:0.29243:0.867354:rs3131962