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.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_3526.vcf.gz --id UKB-b:12687 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_3526.txt.gz --cohort_controls 273111 --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-12687/UKB-b-12687_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12687/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12687/UKB-b-12687_data.vcf.gz ...
Read summary statistics for 9685739 SNPs.
Dropped 13247 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, 1288763 SNPs remain.
After merging with regression SNP LD, 1288763 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0239 (0.0024)
Lambda GC: 1.2106
Mean Chi^2: 1.226
Intercept: 1.0968 (0.0074)
Ratio: 0.4285 (0.0329)
Analysis finished at Thu Oct 17 14:43:45 2019
Total time elapsed: 1.0m:39.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9494,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 12,
    "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": 162015,
    "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": 1288763,
    "ldsc_nsnp_merge_regression_ld": 1288763,
    "ldsc_observed_scale_h2_beta": 0.0239,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0968,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.2106,
    "ldsc_mean_chisq": 1.226,
    "ldsc_ratio": 0.4283
}

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 9672557 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 9685739 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 8.625773e+00 5.749929e+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 7.884022e+07 5.628687e+07 828.0000000 3.256929e+07 6.944890e+07 1.145700e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.215000e-04 1.233280e-02 -0.1758250 -4.145700e-03 -7.730000e-05 3.935700e-03 2.787460e-01 ▁▇▂▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 8.734600e-03 7.810800e-03 0.0025918 3.156200e-03 5.196000e-03 1.174290e-02 1.404320e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.750790e-01 2.952518e-01 0.0000000 2.099999e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.750786e-01 2.952266e-01 0.0000000 2.130978e-01 4.666006e-01 7.305113e-01 9.999998e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.062700e-01 2.569305e-01 0.0012820 1.432900e-02 8.197400e-02 3.219590e-01 9.987180e-01 ▇▂▁▁▁
numeric AF_reference 162015 0.9832728 NA NA NA NA NA NA NA 2.087830e-01 2.485743e-01 0.0000000 1.238020e-02 1.028350e-01 3.244810e-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 -0.0067876 0.0047650 0.1499999 0.1543114 0.623702 0.7821490 NA
1 54676 rs2462492 C T -0.0061225 0.0047191 0.1900002 0.1944949 0.400662 NA NA
1 86028 rs114608975 T C 0.0132545 0.0075298 0.0779992 0.0783636 0.103876 0.0277556 NA
1 91536 rs6702460 G T -0.0061682 0.0046493 0.1800002 0.1846089 0.457231 0.4207270 NA
1 234313 rs8179466 C T -0.0097890 0.0092062 0.2900000 0.2876411 0.074229 NA NA
1 534192 rs6680723 C T 0.0031116 0.0053041 0.5600000 0.5574494 0.241022 NA NA
1 546697 rs12025928 A G 0.0071369 0.0066225 0.2800000 0.2811796 0.913421 NA NA
1 693731 rs12238997 A G 0.0008155 0.0044545 0.8499999 0.8547429 0.116359 0.1417730 NA
1 705882 rs72631875 G A 0.0003911 0.0065184 0.9500000 0.9521526 0.067440 0.0315495 NA
1 706368 rs55727773 A G -0.0011552 0.0032997 0.7300002 0.7262738 0.515602 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0157262 0.0069091 0.0230001 0.0228358 0.042075 0.0473243 NA
22 51219766 rs182321900 C T -0.0060860 0.0324489 0.8499999 0.8512244 0.001920 NA NA
22 51220146 rs868950473 C T -0.0114796 0.0321115 0.7199992 0.7207236 0.001969 NA NA
22 51221190 rs369304721 G A -0.0131833 0.0068992 0.0560003 0.0560235 0.049910 NA NA
22 51221731 rs115055839 T C -0.0082324 0.0051575 0.1100001 0.1104458 0.073525 0.0625000 NA
22 51222100 rs114553188 G T -0.0029726 0.0060954 0.6300007 0.6257736 0.054259 0.0880591 NA
22 51223637 rs375798137 G A -0.0028106 0.0061261 0.6499995 0.6463785 0.053869 0.0788738 NA
22 51229805 rs9616985 T C -0.0083676 0.0051753 0.1100001 0.1059156 0.073365 0.0730831 NA
22 51232488 rs376461333 A G 0.0016174 0.0122664 0.9000000 0.8950994 0.019931 NA NA
22 51237063 rs3896457 T C -0.0017867 0.0031728 0.5700002 0.5733500 0.298593 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623702 ES:SE:LP:AF:ID  -0.00678757:0.00476499:0.823909:0.623702:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400662 ES:SE:LP:AF:ID  -0.00612253:0.00471909:0.721246:0.400662:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103876 ES:SE:LP:AF:ID  0.0132545:0.00752985:1.10791:0.103876:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457231 ES:SE:LP:AF:ID  -0.00616824:0.00464932:0.744727:0.457231:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074229 ES:SE:LP:AF:ID  -0.00978905:0.0092062:0.537602:0.074229:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241022 ES:SE:LP:AF:ID  0.00311159:0.00530414:0.251812:0.241022:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913421 ES:SE:LP:AF:ID  0.00713687:0.00662248:0.552842:0.913421:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116359 ES:SE:LP:AF:ID  0.000815483:0.00445448:0.0705811:0.116359:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06744  ES:SE:LP:AF:ID  0.000391126:0.00651835:0.0222764:0.06744:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515602 ES:SE:LP:AF:ID  -0.00115517:0.00329967:0.136677:0.515602:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032762 ES:SE:LP:AF:ID  0.00648844:0.00834423:0.356547:0.032762:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036329 ES:SE:LP:AF:ID  0.00694731:0.00758044:0.443698:0.036329:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036445 ES:SE:LP:AF:ID  0.00642841:0.00755149:0.408935:0.036445:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03617  ES:SE:LP:AF:ID  0.007644:0.00760294:0.508638:0.03617:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016401 ES:SE:LP:AF:ID  -0.000833031:0.0116628:0.0268721:0.016401:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036687 ES:SE:LP:AF:ID  0.00705826:0.00752014:0.455932:0.036687:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036794 ES:SE:LP:AF:ID  0.0069848:0.00749325:0.455932:0.036794:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101204 ES:SE:LP:AF:ID  -0.00271369:0.00543375:0.207608:0.101204:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959512 ES:SE:LP:AF:ID  -0.00409235:0.0072382:0.244125:0.959512:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031325 ES:SE:LP:AF:ID  0.000541409:0.013152:0.0132283:0.031325:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053303 ES:SE:LP:AF:ID  0.00406817:0.0103808:0.154902:0.053303:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036301 ES:SE:LP:AF:ID  0.00570726:0.00754385:0.346787:0.036301:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03663  ES:SE:LP:AF:ID  0.00629155:0.00747414:0.39794:0.03663:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843443 ES:SE:LP:AF:ID  -0.00334017:0.00386387:0.408935:0.843443:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055868 ES:SE:LP:AF:ID  0.00349207:0.00625195:0.236572:0.055868:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122334 ES:SE:LP:AF:ID  0.00208154:0.00422598:0.207608:0.122334:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025803 ES:SE:LP:AF:ID  -0.0220758:0.010361:1.48149:0.025803:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121586 ES:SE:LP:AF:ID  0.00233387:0.00422756:0.236572:0.121586:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132244 ES:SE:LP:AF:ID  0.00452472:0.00416625:0.552842:0.132244:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011306 ES:SE:LP:AF:ID  0.00854494:0.0149799:0.244125:0.011306:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005717 ES:SE:LP:AF:ID  0.00652257:0.0194899:0.130768:0.005717:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002191 ES:SE:LP:AF:ID  -0.0163897:0.0335646:0.200659:0.002191:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036515 ES:SE:LP:AF:ID  0.00617368:0.00740166:0.39794:0.036515:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839193 ES:SE:LP:AF:ID  -0.00165135:0.00374358:0.180456:0.839193:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83883  ES:SE:LP:AF:ID  -0.00164238:0.00373965:0.180456:0.83883:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869815 ES:SE:LP:AF:ID  -0.000393209:0.0040113:0.0362122:0.869815:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129846 ES:SE:LP:AF:ID  -9.88289e-05:0.00401892:0.00877392:0.129846:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037039 ES:SE:LP:AF:ID  0.00668581:0.00727597:0.443698:0.037039:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037282 ES:SE:LP:AF:ID  0.00674784:0.00723007:0.455932:0.037282:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869179 ES:SE:LP:AF:ID  -0.000232817:0.00400378:0.0222764:0.869179:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869279 ES:SE:LP:AF:ID  -0.000409339:0.00400545:0.0362122:0.869279:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037233 ES:SE:LP:AF:ID  0.00680002:0.00726166:0.455932:0.037233:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869182 ES:SE:LP:AF:ID  -0.000182945:0.00400366:0.0177288:0.869182:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005097 ES:SE:LP:AF:ID  -0.00469334:0.020566:0.0861861:0.005097:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005061 ES:SE:LP:AF:ID  -0.00516306:0.0206259:0.09691:0.005061:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838271 ES:SE:LP:AF:ID  -0.00121178:0.00372905:0.124939:0.838271:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03724  ES:SE:LP:AF:ID  0.00708791:0.00727208:0.481486:0.03724:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838888 ES:SE:LP:AF:ID  -0.00116345:0.0037393:0.119186:0.838888:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013809 ES:SE:LP:AF:ID  0.0171742:0.0130244:0.721246:0.013809:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005597 ES:SE:LP:AF:ID  0.0108114:0.0200197:0.229148:0.005597:rs184270342