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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_1960.vcf.gz --id UKB-b:19809 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_1960.txt.gz --cohort_cases 184258 --cohort_controls 268813 --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-19809/UKB-b-19809_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19809/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:39 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19809/UKB-b-19809_data.vcf.gz ...
Read summary statistics for 9448148 SNPs.
Dropped 11241 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, 1288257 SNPs remain.
After merging with regression SNP LD, 1288257 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0683 (0.0027)
Lambda GC: 1.5024
Mean Chi^2: 1.6546
Intercept: 1.0312 (0.0094)
Ratio: 0.0476 (0.0144)
Analysis finished at Thu Oct 17 14:43:23 2019
Total time elapsed: 1.0m:44.03s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.949,
    "inflation_factor": 1.369,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 59,
    "n_p_sig": 7210,
    "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": 127029,
    "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": 1288257,
    "ldsc_nsnp_merge_regression_ld": 1288257,
    "ldsc_observed_scale_h2_beta": 0.0683,
    "ldsc_observed_scale_h2_se": 0.0027,
    "ldsc_intercept_beta": 1.0312,
    "ldsc_intercept_se": 0.0094,
    "ldsc_lambda_gc": 1.5024,
    "ldsc_mean_chisq": 1.6546,
    "ldsc_ratio": 0.0477
}
 

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 9436966 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 9448148 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 8.629748e+00 5.752472e+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 7.883654e+07 5.631238e+07 828.0000000 3.253349e+07 6.941936e+07 1.145696e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.380000e-05 4.246300e-03 -0.0701698 -1.629800e-03 1.450000e-05 1.675200e-03 5.460630e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.081400e-03 2.539300e-03 0.0009904 1.196600e-03 1.918900e-03 4.203400e-03 3.428430e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.511547e-01 3.017663e-01 0.0000000 1.800002e-01 4.299995e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.511554e-01 3.017428e-01 0.0000000 1.774569e-01 4.331788e-01 7.124382e-01 9.999990e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.108444e-01 2.574397e-01 0.0019000 1.620900e-02 8.828100e-02 3.302672e-01 9.981000e-01 ▇▂▁▁▁
numeric AF_reference 127029 0.9865551 NA NA NA NA NA NA NA 2.123251e-01 2.491847e-01 0.0000000 1.377800e-02 1.076280e-01 3.312700e-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 0.0027992 0.0018215 0.1199999 0.1243655 0.623773 0.7821490 NA
1 54676 rs2462492 C T -0.0017515 0.0018044 0.3300000 0.3317144 0.400425 NA NA
1 86028 rs114608975 T C -0.0012942 0.0028847 0.6499995 0.6536960 0.103562 0.0277556 NA
1 91536 rs6702460 G T -0.0035264 0.0017766 0.0470002 0.0471558 0.456789 0.4207270 NA
1 234313 rs8179466 C T -0.0008915 0.0035044 0.8000000 0.7991790 0.074487 NA NA
1 534192 rs6680723 C T 0.0036084 0.0020292 0.0749998 0.0753607 0.240967 NA NA
1 546697 rs12025928 A G 0.0027951 0.0025313 0.2700001 0.2695089 0.913441 NA NA
1 693731 rs12238997 A G 0.0016172 0.0017011 0.3400001 0.3417732 0.116259 0.1417730 NA
1 705882 rs72631875 G A -0.0009041 0.0024921 0.7199992 0.7167758 0.067300 0.0315495 NA
1 706368 rs55727773 A G -0.0035560 0.0012599 0.0048000 0.0047652 0.515816 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0013095 0.0026466 0.6200004 0.6207526 0.041940 0.0473243 NA
22 51219766 rs182321900 C T -0.0171333 0.0123782 0.1700000 0.1663122 0.001923 NA NA
22 51220146 rs868950473 C T -0.0170914 0.0122599 0.1600000 0.1632905 0.001972 NA NA
22 51221190 rs369304721 G A 0.0006245 0.0026420 0.8100000 0.8131335 0.049711 NA NA
22 51221731 rs115055839 T C -0.0003712 0.0019761 0.8499999 0.8509965 0.073210 0.0625000 NA
22 51222100 rs114553188 G T 0.0041741 0.0023285 0.0729995 0.0730345 0.054361 0.0880591 NA
22 51223637 rs375798137 G A 0.0042991 0.0023398 0.0659994 0.0661509 0.053992 0.0788738 NA
22 51229805 rs9616985 T C -0.0003399 0.0019832 0.8600001 0.8639341 0.073047 0.0730831 NA
22 51232488 rs376461333 A G 0.0093370 0.0046766 0.0460002 0.0458763 0.020003 NA NA
22 51237063 rs3896457 T C -0.0001871 0.0012130 0.8800001 0.8774066 0.297987 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623773 ES:SE:LP:AF:ID  0.00279917:0.00182154:0.920819:0.623773:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400425 ES:SE:LP:AF:ID  -0.00175149:0.00180442:0.481486:0.400425:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103562 ES:SE:LP:AF:ID  -0.00129416:0.00288467:0.187087:0.103562:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456789 ES:SE:LP:AF:ID  -0.00352645:0.00177664:1.3279:0.456789:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074487 ES:SE:LP:AF:ID  -0.000891546:0.00350437:0.09691:0.074487:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240967 ES:SE:LP:AF:ID  0.00360838:0.00202916:1.12494:0.240967:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913441 ES:SE:LP:AF:ID  0.00279508:0.00253133:0.568636:0.913441:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116259 ES:SE:LP:AF:ID  0.00161719:0.00170111:0.468521:0.116259:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0673   ES:SE:LP:AF:ID  -0.000904062:0.0024921:0.142668:0.0673:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515816 ES:SE:LP:AF:ID  -0.00355603:0.00125989:2.31876:0.515816:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033002 ES:SE:LP:AF:ID  0.00410602:0.00317617:0.69897:0.033002:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03662  ES:SE:LP:AF:ID  0.00333937:0.00288502:0.60206:0.03662:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036732 ES:SE:LP:AF:ID  0.00362253:0.0028743:0.677781:0.036732:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036433 ES:SE:LP:AF:ID  0.00361613:0.00289494:0.677781:0.036433:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016409 ES:SE:LP:AF:ID  0.00586013:0.00445618:0.721246:0.016409:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036974 ES:SE:LP:AF:ID  0.0036703:0.00286284:0.69897:0.036974:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037068 ES:SE:LP:AF:ID  0.00347551:0.00285318:0.657577:0.037068:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101155 ES:SE:LP:AF:ID  0.00254131:0.00207934:0.657577:0.101155:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959105 ES:SE:LP:AF:ID  -0.00315414:0.0027521:0.60206:0.959105:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031465 ES:SE:LP:AF:ID  0.00128869:0.00499244:0.09691:0.031465:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053261 ES:SE:LP:AF:ID  -0.0045322:0.00397259:0.60206:0.053261:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036586 ES:SE:LP:AF:ID  0.00353412:0.00287148:0.657577:0.036586:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036902 ES:SE:LP:AF:ID  0.0035073:0.00284538:0.657577:0.036902:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843304 ES:SE:LP:AF:ID  -0.00179763:0.00147423:0.657577:0.843304:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055866 ES:SE:LP:AF:ID  0.00178171:0.00238763:0.337242:0.055866:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12222  ES:SE:LP:AF:ID  0.00158165:0.00161378:0.481486:0.12222:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025701 ES:SE:LP:AF:ID  0.000848698:0.00396975:0.0809219:0.025701:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12146  ES:SE:LP:AF:ID  0.00174937:0.00161449:0.552842:0.12146:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132265 ES:SE:LP:AF:ID  0.00140212:0.00159085:0.420216:0.132265:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011125 ES:SE:LP:AF:ID  -0.00189498:0.00578476:0.130768:0.011125:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005707 ES:SE:LP:AF:ID  -0.00743599:0.00746058:0.49485:0.005707:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002265 ES:SE:LP:AF:ID  -0.0142248:0.012558:0.585027:0.002265:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036817 ES:SE:LP:AF:ID  0.00406518:0.00281665:0.823909:0.036817:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839028 ES:SE:LP:AF:ID  -0.00240844:0.00142763:1.03621:0.839028:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838659 ES:SE:LP:AF:ID  -0.00225701:0.00142609:0.958607:0.838659:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869865 ES:SE:LP:AF:ID  -0.00196456:0.00153045:0.69897:0.869865:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129786 ES:SE:LP:AF:ID  0.00198654:0.00153358:0.69897:0.129786:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037322 ES:SE:LP:AF:ID  0.00404318:0.00276921:0.853872:0.037322:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037565 ES:SE:LP:AF:ID  0.00421801:0.0027517:0.886057:0.037565:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869212 ES:SE:LP:AF:ID  -0.0018782:0.00152747:0.657577:0.869212:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869311 ES:SE:LP:AF:ID  -0.00185791:0.00152808:0.657577:0.869311:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037524 ES:SE:LP:AF:ID  0.00404141:0.00276357:0.853872:0.037524:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  -0.00186984:0.00152743:0.657577:0.869215:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005122 ES:SE:LP:AF:ID  0.00465372:0.0078378:0.259637:0.005122:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  0.00478623:0.0078585:0.267606:0.005088:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838116 ES:SE:LP:AF:ID  -0.00229506:0.00142218:0.958607:0.838116:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037537 ES:SE:LP:AF:ID  0.003947:0.00276743:0.823909:0.037537:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838745 ES:SE:LP:AF:ID  -0.00225088:0.00142617:0.958607:0.838745:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013781 ES:SE:LP:AF:ID  0.00383934:0.00497482:0.356547:0.013781:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005556 ES:SE:LP:AF:ID  -0.000549734:0.00766968:0.0268721:0.005556:rs184270342