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_20133.vcf.gz --id UKB-b:10412 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20133.txt.gz --cohort_controls 110323 --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-10412/UKB-b-10412_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10412/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-10412/UKB-b-10412_data.vcf.gz ...
Read summary statistics for 9093791 SNPs.
Dropped 9136 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, 1287410 SNPs remain.
After merging with regression SNP LD, 1287410 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0855 (0.0067)
Lambda GC: 1.1713
Mean Chi^2: 1.1929
Intercept: 1.0043 (0.0074)
Ratio: 0.0221 (0.0382)
Analysis finished at Thu Oct 17 14:41:55 2019
Total time elapsed: 1.0m:37.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.948,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 7.2014e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 74,
    "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": 97791,
    "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": 1287410,
    "ldsc_nsnp_merge_regression_ld": 1287410,
    "ldsc_observed_scale_h2_beta": 0.0855,
    "ldsc_observed_scale_h2_se": 0.0067,
    "ldsc_intercept_beta": 1.0043,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.1713,
    "ldsc_mean_chisq": 1.1929,
    "ldsc_ratio": 0.0223
}

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 9084698 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 9093791 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 8.640942e+00 5.757162e+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 7.879160e+07 5.632950e+07 828.0000000 3.244965e+07 6.935744e+07 1.145288e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.200000e-06 1.470380e-02 -0.1506890 -5.853600e-03 -1.910000e-05 5.830600e-03 1.983190e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.147790e-02 8.584500e-03 0.0040818 4.874100e-03 7.533400e-03 1.575270e-02 9.309440e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.801190e-01 2.937996e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.801197e-01 2.937750e-01 0.0000000 2.208810e-01 4.731019e-01 7.343474e-01 9.999998e-01 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.182518e-01 2.583270e-01 0.0031730 1.955200e-02 9.876300e-02 3.439640e-01 9.968270e-01 ▇▂▁▁▁
numeric AF_reference 97791 0.9892464 NA NA NA NA NA NA NA 2.187121e-01 2.501961e-01 0.0000000 1.677320e-02 1.164140e-01 3.426520e-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 -0.0025719 0.0075030 0.7300002 0.7317598 0.624112 0.7821490 NA
1 54676 rs2462492 C T 0.0059269 0.0074323 0.4299995 0.4251919 0.399420 NA NA
1 86028 rs114608975 T C 0.0001959 0.0119187 0.9900000 0.9868873 0.103289 0.0277556 NA
1 91536 rs6702460 G T -0.0070399 0.0073196 0.3400001 0.3361624 0.456436 0.4207270 NA
1 234313 rs8179466 C T -0.0217326 0.0145330 0.1299999 0.1348109 0.074052 NA NA
1 534192 rs6680723 C T -0.0067382 0.0083480 0.4199997 0.4195715 0.241034 NA NA
1 546697 rs12025928 A G -0.0069494 0.0103961 0.5000000 0.5038355 0.913045 NA NA
1 693731 rs12238997 A G 0.0033119 0.0070001 0.6400000 0.6361252 0.116923 0.1417730 NA
1 705882 rs72631875 G A 0.0059517 0.0102103 0.5600000 0.5599556 0.067605 0.0315495 NA
1 706368 rs55727773 A G -0.0002200 0.0051912 0.9699999 0.9661902 0.515635 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0004809 0.0062941 0.9400001 0.9390906 0.136586 0.2052720 NA
22 51219387 rs9616832 T C 0.0070444 0.0081783 0.3900004 0.3890448 0.072740 0.0654952 NA
22 51219704 rs147475742 G A 0.0071568 0.0110008 0.5199996 0.5153253 0.041185 0.0473243 NA
22 51221190 rs369304721 G A 0.0025847 0.0109322 0.8100000 0.8131019 0.049192 NA NA
22 51221731 rs115055839 T C 0.0067789 0.0081843 0.4100001 0.4075093 0.072196 0.0625000 NA
22 51222100 rs114553188 G T -0.0106103 0.0096199 0.2700001 0.2700495 0.054228 0.0880591 NA
22 51223637 rs375798137 G A -0.0110974 0.0096686 0.2500000 0.2510580 0.053864 0.0788738 NA
22 51229805 rs9616985 T C 0.0071021 0.0082141 0.3900004 0.3872421 0.072020 0.0730831 NA
22 51232488 rs376461333 A G -0.0020975 0.0194060 0.9100000 0.9139265 0.019798 NA NA
22 51237063 rs3896457 T C 0.0025266 0.0049783 0.6100002 0.6117854 0.298248 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624112 ES:SE:LP:AF:ID  -0.00257193:0.00750303:0.136677:0.624112:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39942  ES:SE:LP:AF:ID  0.00592686:0.0074323:0.366532:0.39942:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103289 ES:SE:LP:AF:ID  0.000195884:0.0119187:0.00436481:0.103289:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456436 ES:SE:LP:AF:ID  -0.00703986:0.00731965:0.468521:0.456436:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074052 ES:SE:LP:AF:ID  -0.0217326:0.014533:0.886057:0.074052:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241034 ES:SE:LP:AF:ID  -0.00673818:0.00834796:0.376751:0.241034:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913045 ES:SE:LP:AF:ID  -0.00694945:0.0103961:0.30103:0.913045:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116923 ES:SE:LP:AF:ID  0.00331192:0.00700012:0.19382:0.116923:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067605 ES:SE:LP:AF:ID  0.00595166:0.0102103:0.251812:0.067605:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515635 ES:SE:LP:AF:ID  -0.000220038:0.00519117:0.0132283:0.515635:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032866 ES:SE:LP:AF:ID  0.012783:0.0131233:0.481486:0.032866:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036495 ES:SE:LP:AF:ID  0.0107561:0.0119112:0.431798:0.036495:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036605 ES:SE:LP:AF:ID  0.0107683:0.0118656:0.443698:0.036605:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036301 ES:SE:LP:AF:ID  0.0108594:0.011953:0.443698:0.036301:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016582 ES:SE:LP:AF:ID  0.00926808:0.0182692:0.21467:0.016582:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036845 ES:SE:LP:AF:ID  0.010993:0.0118175:0.455932:0.036845:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036962 ES:SE:LP:AF:ID  0.00967362:0.0117755:0.387216:0.036962:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101798 ES:SE:LP:AF:ID  0.00593438:0.00854405:0.309804:0.101798:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959395 ES:SE:LP:AF:ID  -0.0132907:0.0113784:0.619789:0.959395:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031238 ES:SE:LP:AF:ID  0.0279433:0.0208359:0.744727:0.031238:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053354 ES:SE:LP:AF:ID  -0.0189058:0.0163396:0.60206:0.053354:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036472 ES:SE:LP:AF:ID  0.0108737:0.0118484:0.443698:0.036472:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036763 ES:SE:LP:AF:ID  0.010283:0.0117444:0.420216:0.036763:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843095 ES:SE:LP:AF:ID  -0.00316693:0.00607844:0.221849:0.843095:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055862 ES:SE:LP:AF:ID  -0.0167141:0.00985033:1.04576:0.055862:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122867 ES:SE:LP:AF:ID  -0.000676088:0.00664565:0.0362122:0.122867:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.024842 ES:SE:LP:AF:ID  -0.0338302:0.0166271:1.37675:0.024842:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122092 ES:SE:LP:AF:ID  1.68418e-05:0.00664946:-0:0.122092:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132542 ES:SE:LP:AF:ID  0.00181487:0.00655444:0.107905:0.132542:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011108 ES:SE:LP:AF:ID  0.0010647:0.0239144:0.0177288:0.011108:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005668 ES:SE:LP:AF:ID  0.0422771:0.0309626:0.769551:0.005668:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036682 ES:SE:LP:AF:ID  0.00952091:0.0116254:0.387216:0.036682:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838797 ES:SE:LP:AF:ID  -0.00252511:0.00588693:0.173925:0.838797:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838465 ES:SE:LP:AF:ID  -0.00232524:0.00588122:0.161151:0.838465:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869304 ES:SE:LP:AF:ID  -0.000314669:0.00630413:0.0177288:0.869304:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.13035  ES:SE:LP:AF:ID  -0.000597703:0.00631775:0.0362122:0.13035:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037153 ES:SE:LP:AF:ID  0.00925557:0.0114337:0.376751:0.037153:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.0374   ES:SE:LP:AF:ID  0.00945609:0.0113589:0.387216:0.0374:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868666 ES:SE:LP:AF:ID  -0.000271483:0.00629282:0.0132283:0.868666:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868779 ES:SE:LP:AF:ID  -0.000550348:0.00629608:0.0315171:0.868779:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037359 ES:SE:LP:AF:ID  0.0092159:0.0114103:0.376751:0.037359:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868674 ES:SE:LP:AF:ID  -0.000343006:0.00629272:0.0177288:0.868674:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005163 ES:SE:LP:AF:ID  0.00464214:0.0321439:0.05061:0.005163:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005136 ES:SE:LP:AF:ID  0.00352052:0.0321968:0.0409586:0.005136:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.8379   ES:SE:LP:AF:ID  -0.00235221:0.00586514:0.161151:0.8379:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037404 ES:SE:LP:AF:ID  0.010428:0.0114222:0.443698:0.037404:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838501 ES:SE:LP:AF:ID  -0.00239972:0.00588106:0.167491:0.838501:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013571 ES:SE:LP:AF:ID  -0.00254871:0.0206511:0.0457575:0.013571:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005483 ES:SE:LP:AF:ID  0.0185931:0.0317281:0.251812:0.005483:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839606 ES:SE:LP:AF:ID  -0.00229639:0.0059591:0.154902:0.839606:rs3131965