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_5114.vcf.gz --id UKB-b:17772 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5114.txt.gz --cohort_controls 84278 --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-17772/UKB-b-17772_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17772/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-17772/UKB-b-17772_data.vcf.gz ...
Read summary statistics for 8887049 SNPs.
Dropped 8242 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, 1286828 SNPs remain.
After merging with regression SNP LD, 1286828 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.047 (0.0057)
Lambda GC: 1.0797
Mean Chi^2: 1.0806
Intercept: 1.0039 (0.006)
Ratio: 0.0484 (0.0742)
Analysis finished at Thu Oct 17 14:41:58 2019
Total time elapsed: 1.0m:40.4s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9474,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 89243,
    "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": 1286828,
    "ldsc_nsnp_merge_regression_ld": 1286828,
    "ldsc_observed_scale_h2_beta": 0.047,
    "ldsc_observed_scale_h2_se": 0.0057,
    "ldsc_intercept_beta": 1.0039,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0797,
    "ldsc_mean_chisq": 1.0806,
    "ldsc_ratio": 0.0484
}

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 8878846 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 8887049 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 8.646389e+00 5.759741e+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 7.877895e+07 5.634585e+07 828.0000000 3.241417e+07 6.933268e+07 1.145495e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.620000e-05 1.558070e-02 -0.1659720 -6.366200e-03 -2.480000e-05 6.287700e-03 1.610020e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.256570e-02 8.984400e-03 0.0047002 5.583900e-03 8.445900e-03 1.718140e-02 1.074890e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.906498e-01 2.910276e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.906503e-01 2.910022e-01 0.0000000 2.363073e-01 4.876397e-01 7.426315e-01 9.999994e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.229371e-01 2.588379e-01 0.0041530 2.190600e-02 1.054140e-01 3.518960e-01 9.958470e-01 ▇▂▁▁▁
numeric AF_reference 89243 0.9899581 NA NA NA NA NA NA NA 2.230330e-01 2.507847e-01 0.0000000 1.936900e-02 1.224040e-01 3.500400e-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 0.0068011 0.0086909 0.4299995 0.4338874 0.623316 0.7821490 NA
1 54676 rs2462492 C T -0.0050077 0.0086319 0.5600000 0.5618192 0.399069 NA NA
1 86028 rs114608975 T C 0.0064220 0.0136730 0.6400000 0.6385802 0.104085 0.0277556 NA
1 91536 rs6702460 G T 0.0024034 0.0084743 0.7800007 0.7767053 0.455597 0.4207270 NA
1 234313 rs8179466 C T -0.0071568 0.0165850 0.6700003 0.6660898 0.074847 NA NA
1 534192 rs6680723 C T -0.0017080 0.0096974 0.8600001 0.8601874 0.240525 NA NA
1 546697 rs12025928 A G -0.0144395 0.0120081 0.2300001 0.2291776 0.912605 NA NA
1 693731 rs12238997 A G 0.0020502 0.0080543 0.8000000 0.7990723 0.117892 0.1417730 NA
1 705882 rs72631875 G A 0.0033769 0.0118332 0.7800007 0.7753549 0.067383 0.0315495 NA
1 706368 rs55727773 A G -0.0043538 0.0059744 0.4700002 0.4661599 0.514491 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0006547 0.0072372 0.9299999 0.9279186 0.137302 0.2052720 NA
22 51219387 rs9616832 T C 0.0034937 0.0094463 0.7099994 0.7114964 0.072443 0.0654952 NA
22 51219704 rs147475742 G A 0.0082404 0.0125532 0.5099998 0.5115402 0.041844 0.0473243 NA
22 51221190 rs369304721 G A 0.0019032 0.0126311 0.8800001 0.8802284 0.049027 NA NA
22 51221731 rs115055839 T C 0.0039056 0.0094483 0.6800001 0.6793368 0.071978 0.0625000 NA
22 51222100 rs114553188 G T -0.0117012 0.0110177 0.2900000 0.2882191 0.054745 0.0880591 NA
22 51223637 rs375798137 G A -0.0112568 0.0110746 0.3100002 0.3094142 0.054368 0.0788738 NA
22 51229805 rs9616985 T C 0.0044573 0.0094848 0.6400000 0.6383995 0.071825 0.0730831 NA
22 51232488 rs376461333 A G -0.0505301 0.0223000 0.0230001 0.0234561 0.020125 NA NA
22 51237063 rs3896457 T C -0.0072401 0.0057544 0.2099999 0.2083255 0.298653 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623316 ES:SE:LP:AF:ID  0.0068011:0.00869087:0.366532:0.623316:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399069 ES:SE:LP:AF:ID  -0.0050077:0.00863186:0.251812:0.399069:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104085 ES:SE:LP:AF:ID  0.006422:0.013673:0.19382:0.104085:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455597 ES:SE:LP:AF:ID  0.00240344:0.0084743:0.107905:0.455597:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074847 ES:SE:LP:AF:ID  -0.00715677:0.016585:0.173925:0.074847:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240525 ES:SE:LP:AF:ID  -0.00170805:0.00969736:0.0655015:0.240525:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912605 ES:SE:LP:AF:ID  -0.0144395:0.0120081:0.638272:0.912605:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117892 ES:SE:LP:AF:ID  0.0020502:0.00805428:0.09691:0.117892:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067383 ES:SE:LP:AF:ID  0.00337693:0.0118332:0.107905:0.067383:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514491 ES:SE:LP:AF:ID  -0.00435377:0.00597437:0.327902:0.514491:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033635 ES:SE:LP:AF:ID  0.0242431:0.0149352:1:0.033635:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037338 ES:SE:LP:AF:ID  0.0267084:0.013571:1.3098:0.037338:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037423 ES:SE:LP:AF:ID  0.026922:0.013528:1.3279:0.037423:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03712  ES:SE:LP:AF:ID  0.0256566:0.0136211:1.22185:0.03712:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016863 ES:SE:LP:AF:ID  0.0498225:0.0209162:1.76955:0.016863:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037672 ES:SE:LP:AF:ID  0.0256808:0.013471:1.24413:0.037672:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037768 ES:SE:LP:AF:ID  0.0251265:0.0134269:1.21467:0.037768:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100713 ES:SE:LP:AF:ID  0.00104928:0.00993035:0.0362122:0.100713:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95799  ES:SE:LP:AF:ID  -0.0240291:0.0129048:1.20066:0.95799:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031751 ES:SE:LP:AF:ID  0.00375506:0.0236773:0.0604807:0.031751:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05256  ES:SE:LP:AF:ID  -0.0284014:0.0190731:0.853872:0.05256:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037255 ES:SE:LP:AF:ID  0.02423:0.0135138:1.13668:0.037255:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037555 ES:SE:LP:AF:ID  0.023589:0.0134038:1.10791:0.037555:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84076  ES:SE:LP:AF:ID  -0.0088136:0.00697833:0.677781:0.84076:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05616  ES:SE:LP:AF:ID  -0.00520434:0.0113606:0.187087:0.05616:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12376  ES:SE:LP:AF:ID  0.00151707:0.00764988:0.0757207:0.12376:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025774 ES:SE:LP:AF:ID  -0.0331422:0.0188465:1.10237:0.025774:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122952 ES:SE:LP:AF:ID  0.00208386:0.00765419:0.102373:0.122952:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133621 ES:SE:LP:AF:ID  0.00384952:0.00754836:0.21467:0.133621:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011343 ES:SE:LP:AF:ID  0.0172293:0.027209:0.275724:0.011343:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006118 ES:SE:LP:AF:ID  -0.021499:0.0340926:0.275724:0.006118:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.0279454:0.0132568:1.45593:0.03753:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.8367   ES:SE:LP:AF:ID  -0.00856256:0.00675383:0.69897:0.8367:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83625  ES:SE:LP:AF:ID  -0.00919901:0.00674546:0.769551:0.83625:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868088 ES:SE:LP:AF:ID  -0.00131717:0.00723916:0.0655015:0.868088:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131598 ES:SE:LP:AF:ID  0.00240604:0.00725317:0.130768:0.131598:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037978 ES:SE:LP:AF:ID  0.0251739:0.0130472:1.26761:0.037978:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038237 ES:SE:LP:AF:ID  0.0244531:0.0129648:1.22915:0.038237:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867387 ES:SE:LP:AF:ID  -0.00202104:0.0072242:0.107905:0.867387:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867482 ES:SE:LP:AF:ID  -0.0022237:0.00722782:0.119186:0.867482:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038167 ES:SE:LP:AF:ID  0.0250847:0.0130187:1.26761:0.038167:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867376 ES:SE:LP:AF:ID  -0.0020094:0.00722364:0.107905:0.867376:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005059 ES:SE:LP:AF:ID  -0.019001:0.0376274:0.21467:0.005059:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005025 ES:SE:LP:AF:ID  -0.0189299:0.0377337:0.207608:0.005025:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835803 ES:SE:LP:AF:ID  -0.00884474:0.00673128:0.721246:0.835803:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038185 ES:SE:LP:AF:ID  0.0251875:0.0130361:1.27572:0.038185:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836415 ES:SE:LP:AF:ID  -0.00856473:0.00674982:0.69897:0.836415:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013198 ES:SE:LP:AF:ID  -0.0276713:0.0242321:0.60206:0.013198:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005533 ES:SE:LP:AF:ID  0.0192061:0.0365102:0.221849:0.005533:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837735 ES:SE:LP:AF:ID  -0.0057483:0.00684322:0.39794:0.837735:rs3131965