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.3": "<ID=AF,Number=A,Type=Float,Description=\"Alternate allele frequency in the association study\">",
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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_20127.vcf.gz --id UKB-b:4630 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20127.txt.gz --cohort_controls 374323 --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-4630/UKB-b-4630_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4630/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4630/UKB-b-4630_data.vcf.gz ...
Read summary statistics for 9851824 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: 0.1112 (0.0044)
Lambda GC: 1.6335
Mean Chi^2: 1.8986
Intercept: 1.0455 (0.0103)
Ratio: 0.0506 (0.0115)
Analysis finished at Thu Oct 17 14:46:15 2019
Total time elapsed: 1.0m:44.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.4295,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 116,
    "n_p_sig": 13184,
    "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": 0.1112,
    "ldsc_observed_scale_h2_se": 0.0044,
    "ldsc_intercept_beta": 1.0455,
    "ldsc_intercept_se": 0.0103,
    "ldsc_lambda_gc": 1.6335,
    "ldsc_mean_chisq": 1.8986,
    "ldsc_ratio": 0.0506
}

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 9837154 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 9851824 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 8.622814e+00 5.748296e+00 1.000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.886018e+07 5.628341e+07 828.000000 3.259056e+07 6.948807e+07 1.145914e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.139000e-04 3.719070e-02 -0.521344 -1.286470e-02 1.330000e-04 1.313460e-02 5.230110e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.550470e-02 2.419430e-02 0.007131 8.727700e-03 1.463680e-02 3.377570e-02 3.765940e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.426081e-01 3.037436e-01 0.000000 1.700000e-01 4.199997e-01 7.099994e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.426087e-01 3.037181e-01 0.000000 1.655300e-01 4.211646e-01 7.050910e-01 9.999998e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035063e-01 2.568729e-01 0.000936 1.316300e-02 7.789700e-02 3.164270e-01 9.990620e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812371 NA NA NA NA NA NA NA 2.068395e-01 2.482927e-01 0.000000 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 -0.0011361 0.0131149 0.9299999 0.9309683 0.623607 0.7821490 NA
1 54676 rs2462492 C T -0.0261620 0.0129856 0.0439997 0.0439368 0.400501 NA NA
1 86028 rs114608975 T C -0.0004558 0.0207743 0.9800000 0.9824934 0.103491 0.0277556 NA
1 91536 rs6702460 G T -0.0249984 0.0127842 0.0510000 0.0505343 0.456817 0.4207270 NA
1 234313 rs8179466 C T -0.0237585 0.0252579 0.3500000 0.3468912 0.074395 NA NA
1 534192 rs6680723 C T 0.0019376 0.0146010 0.8900000 0.8944259 0.241174 NA NA
1 546697 rs12025928 A G 0.0070446 0.0181990 0.6999999 0.6986912 0.913355 NA NA
1 693731 rs12238997 A G 0.0092720 0.0122353 0.4500005 0.4485688 0.116380 0.1417730 NA
1 705882 rs72631875 G A 0.0241606 0.0179160 0.1800002 0.1774819 0.067428 0.0315495 NA
1 706368 rs55727773 A G -0.0250964 0.0090646 0.0056000 0.0056293 0.515985 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0043269 0.0190822 0.8200001 0.8206161 0.041864 0.0473243 NA
22 51219766 rs182321900 C T -0.0291352 0.0899050 0.7499995 0.7458877 0.001902 NA NA
22 51220146 rs868950473 C T -0.0153765 0.0891188 0.8600001 0.8630135 0.001950 NA NA
22 51221190 rs369304721 G A -0.0011472 0.0190226 0.9500000 0.9519114 0.049747 NA NA
22 51221731 rs115055839 T C -0.0078723 0.0142302 0.5800000 0.5801201 0.073232 0.0625000 NA
22 51222100 rs114553188 G T 0.0304841 0.0167947 0.0700003 0.0695082 0.054236 0.0880591 NA
22 51223637 rs375798137 G A 0.0292887 0.0168748 0.0830004 0.0826262 0.053874 0.0788738 NA
22 51229805 rs9616985 T C -0.0079059 0.0142816 0.5800000 0.5798696 0.073055 0.0730831 NA
22 51232488 rs376461333 A G 0.0513521 0.0336866 0.1299999 0.1274070 0.020009 NA NA
22 51237063 rs3896457 T C -0.0094357 0.0087262 0.2800000 0.2795638 0.298168 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623607 ES:SE:LP:AF:ID  -0.0011361:0.0131149:0.0315171:0.623607:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400501 ES:SE:LP:AF:ID  -0.026162:0.0129856:1.35655:0.400501:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103491 ES:SE:LP:AF:ID  -0.00045585:0.0207743:0.00877392:0.103491:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456817 ES:SE:LP:AF:ID  -0.0249984:0.0127842:1.29243:0.456817:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074395 ES:SE:LP:AF:ID  -0.0237585:0.0252579:0.455932:0.074395:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241174 ES:SE:LP:AF:ID  0.00193764:0.014601:0.05061:0.241174:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913355 ES:SE:LP:AF:ID  0.00704461:0.018199:0.154902:0.913355:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11638  ES:SE:LP:AF:ID  0.00927195:0.0122353:0.346787:0.11638:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067428 ES:SE:LP:AF:ID  0.0241606:0.017916:0.744727:0.067428:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515985 ES:SE:LP:AF:ID  -0.0250964:0.00906456:2.25181:0.515985:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032954 ES:SE:LP:AF:ID  0.00615139:0.0228769:0.102373:0.032954:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036571 ES:SE:LP:AF:ID  0.0106473:0.0207774:0.21467:0.036571:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036678 ES:SE:LP:AF:ID  0.0110391:0.0207014:0.229148:0.036678:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.03637  ES:SE:LP:AF:ID  0.0123394:0.0208529:0.259637:0.03637:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016491 ES:SE:LP:AF:ID  0.0211906:0.0319891:0.29243:0.016491:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036924 ES:SE:LP:AF:ID  0.0136042:0.0206173:0.29243:0.036924:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037015 ES:SE:LP:AF:ID  0.0124519:0.0205482:0.267606:0.037015:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101061 ES:SE:LP:AF:ID  0.00565537:0.0149748:0.148742:0.101061:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959174 ES:SE:LP:AF:ID  -0.00654925:0.0198259:0.130768:0.959174:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03148  ES:SE:LP:AF:ID  0.0242751:0.0359025:0.30103:0.03148:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053387 ES:SE:LP:AF:ID  0.0144492:0.0284963:0.21467:0.053387:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036551 ES:SE:LP:AF:ID  0.0135911:0.020675:0.29243:0.036551:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036851 ES:SE:LP:AF:ID  0.0124662:0.0204914:0.267606:0.036851:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843251 ES:SE:LP:AF:ID  -0.00823828:0.0106107:0.356547:0.843251:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055722 ES:SE:LP:AF:ID  0.0207438:0.0172095:0.638272:0.055722:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122329 ES:SE:LP:AF:ID  0.0107732:0.0116095:0.455932:0.122329:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025689 ES:SE:LP:AF:ID  -0.00131099:0.028568:0.0177288:0.025689:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121565 ES:SE:LP:AF:ID  0.0114953:0.0116145:0.49485:0.121565:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132297 ES:SE:LP:AF:ID  0.00512881:0.0114485:0.187087:0.132297:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.0111   ES:SE:LP:AF:ID  -0.00481178:0.041695:0.0409586:0.0111:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005777 ES:SE:LP:AF:ID  -0.0627566:0.0533448:0.619789:0.005777:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002244 ES:SE:LP:AF:ID  0.0179:0.0912321:0.0757207:0.002244:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001027 ES:SE:LP:AF:ID  0.0374168:0.148235:0.09691:0.001027:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036777 ES:SE:LP:AF:ID  0.0149974:0.0202833:0.337242:0.036777:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838933 ES:SE:LP:AF:ID  -0.0148257:0.0102742:0.823909:0.838933:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838579 ES:SE:LP:AF:ID  -0.0134303:0.0102633:0.721246:0.838579:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869757 ES:SE:LP:AF:ID  -0.0155994:0.011011:0.79588:0.869757:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129867 ES:SE:LP:AF:ID  0.0143396:0.0110343:0.721246:0.129867:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03728  ES:SE:LP:AF:ID  0.0138152:0.019941:0.309804:0.03728:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037523 ES:SE:LP:AF:ID  0.0143395:0.0198149:0.327902:0.037523:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869128 ES:SE:LP:AF:ID  -0.0147264:0.0109901:0.744727:0.869128:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869232 ES:SE:LP:AF:ID  -0.0145147:0.0109947:0.721246:0.869232:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037488 ES:SE:LP:AF:ID  0.0139238:0.0199001:0.318759:0.037488:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86913  ES:SE:LP:AF:ID  -0.0148675:0.01099:0.744727:0.86913:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005147 ES:SE:LP:AF:ID  0.0319996:0.0562901:0.244125:0.005147:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005112 ES:SE:LP:AF:ID  0.0326577:0.0564401:0.251812:0.005112:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838051 ES:SE:LP:AF:ID  -0.0133894:0.0102364:0.721246:0.838051:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037498 ES:SE:LP:AF:ID  0.0124803:0.0199301:0.275724:0.037498:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838677 ES:SE:LP:AF:ID  -0.0132524:0.0102652:0.69897:0.838677:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013831 ES:SE:LP:AF:ID  0.0284931:0.0357418:0.366532:0.013831:rs181660517