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_102530.vcf.gz --id UKB-b:19931 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_102530.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-19931/UKB-b-19931_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19931/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19931/UKB-b-19931_data.vcf.gz ...
Read summary statistics for 8624970 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, 1285748 SNPs remain.
After merging with regression SNP LD, 1285748 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0036 (0.0079)
Lambda GC: 1.0064
Mean Chi^2: 1.0068
Intercept: 1.0022 (0.0067)
Ratio: 0.3174 (0.9923)
Analysis finished at Thu Oct 17 14:43:33 2019
Total time elapsed: 1.0m:38.18s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": -7.2934e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 4,
    "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": 83094,
    "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": 1285748,
    "ldsc_nsnp_merge_regression_ld": 1285748,
    "ldsc_observed_scale_h2_beta": 0.0036,
    "ldsc_observed_scale_h2_se": 0.0079,
    "ldsc_intercept_beta": 1.0022,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0064,
    "ldsc_mean_chisq": 1.0068,
    "ldsc_ratio": 0.3235
}

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 8617633 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 8624970 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 8.650343e+00 5.760989e+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 7.877020e+07 5.637177e+07 828.0000000 3.238540e+07 6.929172e+07 1.145691e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -7.300000e-06 4.981400e-03 -0.0438034 -2.102200e-03 -3.100000e-05 2.037900e-03 6.827770e-02 ▁▇▅▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.126000e-03 2.816400e-03 0.0016386 1.929700e-03 2.845200e-03 5.577400e-03 2.825200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.996558e-01 2.888574e-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 4.996559e-01 2.888333e-01 0.0000000 2.494204e-01 4.994730e-01 7.499869e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291173e-01 2.594879e-01 0.0053900 2.519100e-02 1.138975e-01 3.626260e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83094 0.9903659 NA NA NA NA NA NA NA 2.288663e-01 2.514586e-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 -0.0035889 0.0030200 0.2300001 0.2346847 0.623806 0.7821490 NA
1 54676 rs2462492 C T 0.0020266 0.0030112 0.5000000 0.5009363 0.399153 NA NA
1 86028 rs114608975 T C 0.0056353 0.0047936 0.2399999 0.2397568 0.103529 0.0277556 NA
1 91536 rs6702460 G T 0.0000926 0.0029619 0.9800000 0.9750487 0.455911 0.4207270 NA
1 234313 rs8179466 C T 0.0014340 0.0058570 0.8100000 0.8065889 0.074458 NA NA
1 534192 rs6680723 C T -0.0056973 0.0033733 0.0909997 0.0912295 0.242059 NA NA
1 546697 rs12025928 A G 0.0035957 0.0041853 0.3900004 0.3902680 0.912857 NA NA
1 693731 rs12238997 A G 0.0006503 0.0028130 0.8200001 0.8171779 0.117304 0.1417730 NA
1 705882 rs72631875 G A -0.0019444 0.0040997 0.6400000 0.6353074 0.067704 0.0315495 NA
1 706368 rs55727773 A G 0.0026049 0.0020878 0.2099999 0.2121481 0.513312 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0023539 0.0025394 0.3500000 0.3539599 0.136313 0.2052720 NA
22 51219387 rs9616832 T C 0.0058351 0.0033099 0.0779992 0.0779170 0.071790 0.0654952 NA
22 51219704 rs147475742 G A 0.0064838 0.0044031 0.1400000 0.1408736 0.041187 0.0473243 NA
22 51221190 rs369304721 G A 0.0037758 0.0044340 0.3900004 0.3944537 0.048378 NA NA
22 51221731 rs115055839 T C 0.0057422 0.0033107 0.0830004 0.0828389 0.071340 0.0625000 NA
22 51222100 rs114553188 G T -0.0025032 0.0038360 0.5099998 0.5140506 0.054856 0.0880591 NA
22 51223637 rs375798137 G A -0.0023739 0.0038560 0.5400003 0.5381388 0.054476 0.0788738 NA
22 51229805 rs9616985 T C 0.0052095 0.0033209 0.1199999 0.1167158 0.071245 0.0730831 NA
22 51232488 rs376461333 A G -0.0020428 0.0076480 0.7899998 0.7893945 0.020462 NA NA
22 51237063 rs3896457 T C -0.0010832 0.0020047 0.5900000 0.5889746 0.298387 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623806 ES:SE:LP:AF:ID  -0.0035889:0.00302:0.638272:0.623806:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399153 ES:SE:LP:AF:ID  0.00202661:0.00301123:0.30103:0.399153:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103529 ES:SE:LP:AF:ID  0.00563532:0.00479359:0.619789:0.103529:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455911 ES:SE:LP:AF:ID  9.26383e-05:0.00296188:0.00877392:0.455911:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074458 ES:SE:LP:AF:ID  0.00143397:0.00585703:0.091515:0.074458:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242059 ES:SE:LP:AF:ID  -0.00569731:0.00337329:1.04096:0.242059:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912857 ES:SE:LP:AF:ID  0.00359574:0.00418532:0.408935:0.912857:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117304 ES:SE:LP:AF:ID  0.000650301:0.00281301:0.0861861:0.117304:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067704 ES:SE:LP:AF:ID  -0.00194436:0.00409969:0.19382:0.067704:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513312 ES:SE:LP:AF:ID  0.00260492:0.00208781:0.677781:0.513312:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033681 ES:SE:LP:AF:ID  0.00281902:0.00520371:0.229148:0.033681:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037461 ES:SE:LP:AF:ID  0.00166328:0.00471951:0.142668:0.037461:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037648 ES:SE:LP:AF:ID  0.00126997:0.00469482:0.102373:0.037648:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037224 ES:SE:LP:AF:ID  0.00070096:0.00473772:0.0555173:0.037224:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016283 ES:SE:LP:AF:ID  0.0112654:0.0074314:0.886057:0.016283:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037864 ES:SE:LP:AF:ID  0.00116555:0.00467877:0.09691:0.037864:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037959 ES:SE:LP:AF:ID  0.00110735:0.00466393:0.091515:0.037959:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102733 ES:SE:LP:AF:ID  -0.00147558:0.00340704:0.180456:0.102733:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958085 ES:SE:LP:AF:ID  -0.000565965:0.00450465:0.0457575:0.958085:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031692 ES:SE:LP:AF:ID  -0.00373018:0.00824875:0.187087:0.031692:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052726 ES:SE:LP:AF:ID  0.00757545:0.00664417:0.60206:0.052726:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037453 ES:SE:LP:AF:ID  0.0012486:0.00469455:0.102373:0.037453:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037721 ES:SE:LP:AF:ID  0.00146753:0.00465566:0.124939:0.037721:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  0.000418504:0.00243251:0.0655015:0.841441:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056327 ES:SE:LP:AF:ID  -0.000775668:0.00395164:0.0757207:0.056327:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123068 ES:SE:LP:AF:ID  -0.000837687:0.00267204:0.124939:0.123068:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02513  ES:SE:LP:AF:ID  0.00883687:0.00665344:0.744727:0.02513:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12232  ES:SE:LP:AF:ID  -0.000737569:0.0026729:0.107905:0.12232:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134131 ES:SE:LP:AF:ID  -0.00207465:0.00262386:0.366532:0.134131:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011559 ES:SE:LP:AF:ID  -0.00841737:0.00935026:0.431798:0.011559:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006101 ES:SE:LP:AF:ID  -0.0181187:0.0118737:0.886057:0.006101:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037604 ES:SE:LP:AF:ID  0.00113379:0.00461252:0.091515:0.037604:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837035 ES:SE:LP:AF:ID  0.00101689:0.00235329:0.173925:0.837035:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836739 ES:SE:LP:AF:ID  0.00122022:0.00235156:0.221849:0.836739:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868571 ES:SE:LP:AF:ID  0.00109799:0.00252693:0.180456:0.868571:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130995 ES:SE:LP:AF:ID  -0.00135067:0.00253342:0.229148:0.130995:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038049 ES:SE:LP:AF:ID  0.00173125:0.00454017:0.154902:0.038049:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038296 ES:SE:LP:AF:ID  0.00173152:0.00451203:0.154902:0.038296:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867985 ES:SE:LP:AF:ID  0.00127224:0.00252287:0.21467:0.867985:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868059 ES:SE:LP:AF:ID  0.0014144:0.0025239:0.236572:0.868059:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038204 ES:SE:LP:AF:ID  0.00141334:0.00453287:0.119186:0.038204:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867996 ES:SE:LP:AF:ID  0.0012652:0.0025228:0.207608:0.867996:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  -0.00916434:0.0126425:0.327902:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836165 ES:SE:LP:AF:ID  0.00118714:0.00234468:0.21467:0.836165:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038207 ES:SE:LP:AF:ID  0.00142309:0.00453948:0.124939:0.038207:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836799 ES:SE:LP:AF:ID  0.00103204:0.00235111:0.180456:0.836799:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013031 ES:SE:LP:AF:ID  -0.0056183:0.00850511:0.29243:0.013031:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005656 ES:SE:LP:AF:ID  -0.00713179:0.0126328:0.244125:0.005656:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838115 ES:SE:LP:AF:ID  0.00151117:0.00238421:0.275724:0.838115:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868237 ES:SE:LP:AF:ID  0.00124402:0.00251955:0.207608:0.868237:rs3115858