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.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_100720.vcf.gz --id UKB-b:9524 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_100720.txt.gz --cohort_controls 64942 --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-9524/UKB-b-9524_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9524/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9524/UKB-b-9524_data.vcf.gz ...
Read summary statistics for 8624941 SNPs.
Dropped 7371 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, 1285749 SNPs remain.
After merging with regression SNP LD, 1285749 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0025 (0.0065)
Lambda GC: 1.0079
Mean Chi^2: 1.0064
Intercept: 1.0032 (0.0056)
Ratio: 0.4946 (0.8798)
Analysis finished at Thu Oct 17 14:44:11 2019
Total time elapsed: 1.0m:24.9s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 83095,
    "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": 1285749,
    "ldsc_nsnp_merge_regression_ld": 1285749,
    "ldsc_observed_scale_h2_beta": 0.0025,
    "ldsc_observed_scale_h2_se": 0.0065,
    "ldsc_intercept_beta": 1.0032,
    "ldsc_intercept_se": 0.0056,
    "ldsc_lambda_gc": 1.0079,
    "ldsc_mean_chisq": 1.0064,
    "ldsc_ratio": 0.5
}

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 8617604 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 8624941 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 8.650354e+00 5.760991e+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 7.877000e+07 5.637171e+07 828.0000000 3.238531e+07 6.929160e+07 1.145687e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.890000e-05 4.537100e-03 -0.0444527 -1.930400e-03 -4.700000e-05 1.823000e-03 5.914530e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.735300e-03 2.549700e-03 0.0014835 1.747000e-03 2.575900e-03 5.049300e-03 2.557350e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.992130e-01 2.887390e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.992151e-01 2.887123e-01 0.0000000 2.487815e-01 4.985479e-01 7.492454e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291188e-01 2.594887e-01 0.0053900 2.519000e-02 1.138990e-01 3.626270e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83095 0.9903657 NA NA NA NA NA NA NA 2.288678e-01 2.514594e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 0.0054441 0.0027342 0.0460002 0.0464733 0.623812 0.7821490 NA
1 54676 rs2462492 C T -0.0016441 0.0027262 0.5500004 0.5464542 0.399150 NA NA
1 86028 rs114608975 T C 0.0041987 0.0043399 0.3300000 0.3333117 0.103534 0.0277556 NA
1 91536 rs6702460 G T 0.0019679 0.0026815 0.4600002 0.4630172 0.455913 0.4207270 NA
1 234313 rs8179466 C T -0.0028755 0.0053027 0.5900000 0.5876353 0.074456 NA NA
1 534192 rs6680723 C T -0.0076498 0.0030539 0.0120000 0.0122483 0.242054 NA NA
1 546697 rs12025928 A G -0.0034870 0.0037894 0.3599996 0.3574785 0.912863 NA NA
1 693731 rs12238997 A G -0.0027998 0.0025465 0.2700001 0.2715740 0.117318 0.1417730 NA
1 705882 rs72631875 G A -0.0041029 0.0037119 0.2700001 0.2690086 0.067698 0.0315495 NA
1 706368 rs55727773 A G 0.0040707 0.0018903 0.0309999 0.0312784 0.513304 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0010066 0.0022990 0.6600001 0.6614841 0.136320 0.2052720 NA
22 51219387 rs9616832 T C -0.0022701 0.0029963 0.4500005 0.4486824 0.071805 0.0654952 NA
22 51219704 rs147475742 G A -0.0009212 0.0039859 0.8200001 0.8172326 0.041195 0.0473243 NA
22 51221190 rs369304721 G A -0.0025963 0.0040142 0.5199996 0.5177740 0.048378 NA NA
22 51221731 rs115055839 T C -0.0023546 0.0029970 0.4299995 0.4320638 0.071356 0.0625000 NA
22 51222100 rs114553188 G T -0.0000013 0.0034728 1.0000000 0.9997103 0.054855 0.0880591 NA
22 51223637 rs375798137 G A -0.0000128 0.0034910 1.0000000 0.9970827 0.054475 0.0788738 NA
22 51229805 rs9616985 T C -0.0025631 0.0030062 0.3900004 0.3938904 0.071260 0.0730831 NA
22 51232488 rs376461333 A G 0.0089219 0.0069239 0.2000000 0.1975532 0.020461 NA NA
22 51237063 rs3896457 T C -0.0030881 0.0018150 0.0890000 0.0888540 0.298387 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  0.00544408:0.00273425:1.33724:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39915  ES:SE:LP:AF:ID  -0.00164414:0.00272623:0.259637:0.39915:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103534 ES:SE:LP:AF:ID  0.00419873:0.00433993:0.481486:0.103534:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455913 ES:SE:LP:AF:ID  0.00196792:0.0026815:0.337242:0.455913:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074456 ES:SE:LP:AF:ID  -0.00287549:0.00530273:0.229148:0.074456:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242054 ES:SE:LP:AF:ID  -0.00764984:0.00305394:1.92082:0.242054:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912863 ES:SE:LP:AF:ID  -0.00348695:0.00378942:0.443698:0.912863:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117318 ES:SE:LP:AF:ID  -0.00279977:0.00254653:0.568636:0.117318:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067698 ES:SE:LP:AF:ID  -0.00410291:0.00371187:0.568636:0.067698:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  0.0040707:0.00189026:1.50864:0.513304:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033674 ES:SE:LP:AF:ID  -0.0082808:0.00471172:1.10237:0.033674:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037454 ES:SE:LP:AF:ID  -0.00576917:0.0042733:0.744727:0.037454:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03764  ES:SE:LP:AF:ID  -0.00560786:0.00425094:0.721246:0.03764:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037217 ES:SE:LP:AF:ID  -0.00577532:0.00428978:0.744727:0.037217:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016284 ES:SE:LP:AF:ID  -0.00458539:0.00672815:0.30103:0.016284:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037857 ES:SE:LP:AF:ID  -0.0057514:0.00423641:0.769551:0.037857:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037951 ES:SE:LP:AF:ID  -0.00577873:0.00422297:0.769551:0.037951:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102725 ES:SE:LP:AF:ID  -0.0056247:0.00308477:1.16749:0.102725:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958092 ES:SE:LP:AF:ID  0.00597731:0.00407866:0.853872:0.958092:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031693 ES:SE:LP:AF:ID  0.00163626:0.00746815:0.0809219:0.031693:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052726 ES:SE:LP:AF:ID  0.00421767:0.00601539:0.318759:0.052726:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037445 ES:SE:LP:AF:ID  -0.00605387:0.0042507:0.823909:0.037445:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037714 ES:SE:LP:AF:ID  -0.00605045:0.00421549:0.823909:0.037714:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841439 ES:SE:LP:AF:ID  0.00354301:0.00220228:0.958607:0.841439:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056333 ES:SE:LP:AF:ID  0.000567291:0.00357757:0.0604807:0.056333:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123083 ES:SE:LP:AF:ID  -0.00246556:0.0024189:0.508638:0.123083:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025133 ES:SE:LP:AF:ID  0.0114376:0.00602369:1.23657:0.025133:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122336 ES:SE:LP:AF:ID  -0.0023944:0.00241968:0.49485:0.122336:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13414  ES:SE:LP:AF:ID  -0.00325991:0.00237533:0.769551:0.13414:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01155  ES:SE:LP:AF:ID  0.00203732:0.00846814:0.091515:0.01155:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006101 ES:SE:LP:AF:ID  -0.0182708:0.01075:1.05061:0.006101:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037596 ES:SE:LP:AF:ID  -0.00656809:0.00417642:0.920819:0.037596:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837027 ES:SE:LP:AF:ID  0.00344019:0.00213044:0.958607:0.837027:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836731 ES:SE:LP:AF:ID  0.00350296:0.00212888:1:0.836731:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868556 ES:SE:LP:AF:ID  0.00206409:0.00228757:0.431798:0.868556:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131011 ES:SE:LP:AF:ID  -0.00234024:0.00229344:0.508638:0.131011:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038042 ES:SE:LP:AF:ID  -0.00623807:0.0041109:0.886057:0.038042:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038288 ES:SE:LP:AF:ID  -0.00632202:0.00408543:0.920819:0.038288:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867969 ES:SE:LP:AF:ID  0.00220741:0.00228389:0.481486:0.867969:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868043 ES:SE:LP:AF:ID  0.00218665:0.00228483:0.468521:0.868043:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038196 ES:SE:LP:AF:ID  -0.00639217:0.00410429:0.920819:0.038196:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86798  ES:SE:LP:AF:ID  0.00220684:0.00228383:0.481486:0.86798:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  -0.00813207:0.0114461:0.318759:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836157 ES:SE:LP:AF:ID  0.00333498:0.00212265:0.920819:0.836157:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038199 ES:SE:LP:AF:ID  -0.00641198:0.00411028:0.920819:0.038199:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836791 ES:SE:LP:AF:ID  0.00331083:0.00212846:0.920819:0.836791:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013031 ES:SE:LP:AF:ID  0.00397318:0.00770024:0.21467:0.013031:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005662 ES:SE:LP:AF:ID  0.0285988:0.0114311:1.92082:0.005662:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838106 ES:SE:LP:AF:ID  0.00310039:0.00215842:0.823909:0.838106:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868221 ES:SE:LP:AF:ID  0.00209468:0.00228089:0.443698:0.868221:rs3115858