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_5133.vcf.gz --id UKB-b:11452 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5133.txt.gz --cohort_controls 84303 --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",
    "file_date": "2019-09-12T23:15:12.383210",
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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-11452/UKB-b-11452_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11452/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11452/UKB-b-11452_data.vcf.gz ...
Read summary statistics for 8887262 SNPs.
Dropped 8243 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, 1286829 SNPs remain.
After merging with regression SNP LD, 1286829 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.3854 (0.021)
Lambda GC: 1.3971
Mean Chi^2: 1.7173
Intercept: 1.0979 (0.013)
Ratio: 0.1364 (0.0181)
Analysis finished at Thu Oct 17 14:41:59 2019
Total time elapsed: 1.0m:40.36s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9474,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 199,
    "n_p_sig": 16047,
    "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": 89248,
    "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": 1286829,
    "ldsc_nsnp_merge_regression_ld": 1286829,
    "ldsc_observed_scale_h2_beta": 0.3854,
    "ldsc_observed_scale_h2_se": 0.021,
    "ldsc_intercept_beta": 1.0979,
    "ldsc_intercept_se": 0.013,
    "ldsc_lambda_gc": 1.3971,
    "ldsc_mean_chisq": 1.7173,
    "ldsc_ratio": 0.1365
}
 

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 8879058 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 8887262 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 8.646363e+00 5.759728e+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 7.877882e+07 5.634575e+07 828.0000000 3.241416e+07 6.933239e+07 1.145492e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 6.920000e-05 1.574490e-02 -0.2135250 -6.637600e-03 1.730000e-05 6.707600e-03 3.688600e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.174250e-02 8.396100e-03 0.0043784 5.218500e-03 7.892800e-03 1.605480e-02 1.004750e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.578186e-01 3.016279e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.578173e-01 3.016033e-01 0.0000000 1.856841e-01 4.447785e-01 7.195724e-01 9.999996e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.229324e-01 2.588377e-01 0.0041520 2.190300e-02 1.054090e-01 3.518930e-01 9.958480e-01 ▇▂▁▁▁
numeric AF_reference 89248 0.9899578 NA NA NA NA NA NA NA 2.230286e-01 2.507842e-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 0.0198923 0.0080986 0.0140001 0.0140396 0.623328 0.7821490 NA
1 54676 rs2462492 C T -0.0119091 0.0080437 0.1400000 0.1387270 0.399068 NA NA
1 86028 rs114608975 T C -0.0250926 0.0127405 0.0490004 0.0488940 0.104087 0.0277556 NA
1 91536 rs6702460 G T 0.0131576 0.0078964 0.0959997 0.0956576 0.455590 0.4207270 NA
1 234313 rs8179466 C T 0.0107953 0.0154489 0.4799997 0.4846929 0.074857 NA NA
1 534192 rs6680723 C T 0.0006107 0.0090359 0.9500000 0.9461180 0.240530 NA NA
1 546697 rs12025928 A G -0.0094698 0.0111886 0.4000000 0.3973412 0.912604 NA NA
1 693731 rs12238997 A G 0.0085158 0.0075055 0.2599998 0.2565360 0.117886 0.1417730 NA
1 705882 rs72631875 G A -0.0068038 0.0110266 0.5400003 0.5372091 0.067380 0.0315495 NA
1 706368 rs55727773 A G -0.0035740 0.0055669 0.5199996 0.5208693 0.514497 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0006509 0.0067777 0.9199999 0.9234911 0.137315 0.2052720 NA
22 51219387 rs9616832 T C 0.0124348 0.0088471 0.1600000 0.1598664 0.072445 0.0654952 NA
22 51219704 rs147475742 G A 0.0247831 0.0117570 0.0350002 0.0350358 0.041844 0.0473243 NA
22 51221190 rs369304721 G A 0.0196809 0.0118299 0.0959997 0.0961809 0.049027 NA NA
22 51221731 rs115055839 T C 0.0122911 0.0088490 0.1600000 0.1648359 0.071981 0.0625000 NA
22 51222100 rs114553188 G T -0.0166911 0.0103165 0.1100001 0.1056834 0.054759 0.0880591 NA
22 51223637 rs375798137 G A -0.0170554 0.0103697 0.1000000 0.1000246 0.054381 0.0788738 NA
22 51229805 rs9616985 T C 0.0120982 0.0088832 0.1700000 0.1732210 0.071827 0.0730831 NA
22 51232488 rs376461333 A G -0.0448458 0.0208842 0.0320000 0.0317650 0.020127 NA NA
22 51237063 rs3896457 T C -0.0072747 0.0053894 0.1800002 0.1770791 0.298658 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623328 ES:SE:LP:AF:ID  0.0198923:0.00809865:1.85387:0.623328:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399068 ES:SE:LP:AF:ID  -0.0119091:0.00804371:0.853872:0.399068:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104087 ES:SE:LP:AF:ID  -0.0250926:0.0127405:1.3098:0.104087:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45559  ES:SE:LP:AF:ID  0.0131576:0.00789639:1.01773:0.45559:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074857 ES:SE:LP:AF:ID  0.0107953:0.0154489:0.318759:0.074857:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24053  ES:SE:LP:AF:ID  0.000610666:0.00903587:0.0222764:0.24053:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912604 ES:SE:LP:AF:ID  -0.0094698:0.0111886:0.39794:0.912604:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117886 ES:SE:LP:AF:ID  0.00851583:0.00750547:0.585027:0.117886:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06738  ES:SE:LP:AF:ID  -0.00680384:0.0110266:0.267606:0.06738:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514497 ES:SE:LP:AF:ID  -0.00357397:0.00556688:0.283997:0.514497:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033641 ES:SE:LP:AF:ID  0.014066:0.0139155:0.508638:0.033641:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037343 ES:SE:LP:AF:ID  0.016298:0.0126451:0.69897:0.037343:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037429 ES:SE:LP:AF:ID  0.0153751:0.0126049:0.657577:0.037429:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037126 ES:SE:LP:AF:ID  0.0183:0.0126917:0.823909:0.037126:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016858 ES:SE:LP:AF:ID  0.0027039:0.0194929:0.05061:0.016858:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037677 ES:SE:LP:AF:ID  0.0176466:0.0125519:0.79588:0.037677:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037773 ES:SE:LP:AF:ID  0.017044:0.0125107:0.769551:0.037773:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10073  ES:SE:LP:AF:ID  0.00335702:0.00925208:0.142668:0.10073:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.957986 ES:SE:LP:AF:ID  -0.0111762:0.0120245:0.455932:0.957986:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031745 ES:SE:LP:AF:ID  -0.0496679:0.022066:1.61979:0.031745:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052556 ES:SE:LP:AF:ID  -0.00211628:0.0177738:0.0409586:0.052556:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037261 ES:SE:LP:AF:ID  0.0177091:0.0125917:0.79588:0.037261:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03756  ES:SE:LP:AF:ID  0.0196201:0.0124892:0.920819:0.03756:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840764 ES:SE:LP:AF:ID  -0.00920509:0.00650276:0.79588:0.840764:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056161 ES:SE:LP:AF:ID  -0.00207372:0.010586:0.0757207:0.056161:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123753 ES:SE:LP:AF:ID  0.00852645:0.00712858:0.638272:0.123753:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025786 ES:SE:LP:AF:ID  -0.00899742:0.0175571:0.21467:0.025786:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122943 ES:SE:LP:AF:ID  0.00780183:0.00713265:0.568636:0.122943:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133622 ES:SE:LP:AF:ID  0.0117612:0.00703386:1.02228:0.133622:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01134  ES:SE:LP:AF:ID  -0.0271048:0.0253576:0.537602:0.01134:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006117 ES:SE:LP:AF:ID  0.0487882:0.0317729:0.920819:0.006117:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  0.0161024:0.0123523:0.721246:0.037535:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.8367   ES:SE:LP:AF:ID  -0.0082495:0.0062935:0.721246:0.8367:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836251 ES:SE:LP:AF:ID  -0.0081441:0.00628573:0.69897:0.836251:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868092 ES:SE:LP:AF:ID  -0.00551072:0.0067458:0.387216:0.868092:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131595 ES:SE:LP:AF:ID  0.0066357:0.00675885:0.481486:0.131595:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037984 ES:SE:LP:AF:ID  0.0163004:0.0121567:0.744727:0.037984:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038243 ES:SE:LP:AF:ID  0.0164022:0.01208:0.769551:0.038243:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867391 ES:SE:LP:AF:ID  -0.00531173:0.00673187:0.366532:0.867391:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867486 ES:SE:LP:AF:ID  -0.00553588:0.00673524:0.387216:0.867486:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038174 ES:SE:LP:AF:ID  0.0168764:0.0121301:0.79588:0.038174:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86738  ES:SE:LP:AF:ID  -0.00520999:0.00673135:0.356547:0.86738:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005063 ES:SE:LP:AF:ID  0.0104971:0.0350444:0.119186:0.005063:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00503  ES:SE:LP:AF:ID  0.00930563:0.0351438:0.102373:0.00503:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835803 ES:SE:LP:AF:ID  -0.00819609:0.00627248:0.721246:0.835803:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038191 ES:SE:LP:AF:ID  0.0171905:0.0121464:0.79588:0.038191:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836415 ES:SE:LP:AF:ID  -0.00826147:0.00628975:0.721246:0.836415:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013196 ES:SE:LP:AF:ID  0.0156596:0.0225831:0.309804:0.013196:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005531 ES:SE:LP:AF:ID  0.00260587:0.034026:0.0268721:0.005531:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837734 ES:SE:LP:AF:ID  -0.00849626:0.00637678:0.744727:0.837734:rs3131965