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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}

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-5192/UKB-b-5192_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5192/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:03 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5192/UKB-b-5192_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0937 (0.0031)
Lambda GC: 1.6992
Mean Chi^2: 1.9148
Intercept: 1.0903 (0.0103)
Ratio: 0.0987 (0.0113)
Analysis finished at Thu Oct 17 14:46:41 2019
Total time elapsed: 1.0m:38.41s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.4921,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 113,
    "n_p_sig": 8107,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.0937,
    "ldsc_observed_scale_h2_se": 0.0031,
    "ldsc_intercept_beta": 1.0903,
    "ldsc_intercept_se": 0.0103,
    "ldsc_lambda_gc": 1.6992,
    "ldsc_mean_chisq": 1.9148,
    "ldsc_ratio": 0.0987
}

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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.470000e-05 8.160000e-03 -0.1276870 -2.786300e-03 3.540000e-05 2.876300e-03 1.120350e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.483800e-03 5.194900e-03 0.0015343 1.877800e-03 3.148800e-03 7.265800e-03 8.029910e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.375032e-01 3.044116e-01 0.0000000 1.600000e-01 4.100001e-01 6.999999e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.375041e-01 3.043880e-01 0.0000000 1.585926e-01 4.130993e-01 7.006843e-01 9.999999e-01 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035071e-01 2.568657e-01 0.0009310 1.316900e-02 7.791000e-02 3.164250e-01 9.990310e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 -0.0050914 0.0028210 0.0710003 0.0711011 0.623762 0.7821490 NA
1 54676 rs2462492 C T 0.0003435 0.0027950 0.9000000 0.9021822 0.400452 NA NA
1 86028 rs114608975 T C 0.0004281 0.0044681 0.9199999 0.9236778 0.103528 0.0277556 NA
1 91536 rs6702460 G T -0.0009200 0.0027518 0.7400005 0.7381245 0.456842 0.4207270 NA
1 234313 rs8179466 C T -0.0009394 0.0054223 0.8600001 0.8624579 0.074551 NA NA
1 534192 rs6680723 C T 0.0009848 0.0031422 0.7499995 0.7539756 0.240993 NA NA
1 546697 rs12025928 A G -0.0007758 0.0039209 0.8400000 0.8431449 0.913509 NA NA
1 693731 rs12238997 A G 0.0060078 0.0026331 0.0230001 0.0225123 0.116357 0.1417730 NA
1 705882 rs72631875 G A -0.0041376 0.0038615 0.2800000 0.2839408 0.067258 0.0315495 NA
1 706368 rs55727773 A G -0.0042236 0.0019507 0.0299999 0.0303764 0.515739 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0003260 0.0041020 0.9400001 0.9366591 0.041942 0.0473243 NA
22 51219766 rs182321900 C T 0.0000369 0.0192843 1.0000000 0.9984721 0.001906 NA NA
22 51220146 rs868950473 C T -0.0021006 0.0190861 0.9100000 0.9123645 0.001956 NA NA
22 51221190 rs369304721 G A -0.0030577 0.0040972 0.4600002 0.4554940 0.049706 NA NA
22 51221731 rs115055839 T C -0.0000906 0.0030622 0.9800000 0.9763930 0.073259 0.0625000 NA
22 51222100 rs114553188 G T -0.0028811 0.0036035 0.4199997 0.4239893 0.054527 0.0880591 NA
22 51223637 rs375798137 G A -0.0030072 0.0036210 0.4100001 0.4062575 0.054156 0.0788738 NA
22 51229805 rs9616985 T C 0.0000902 0.0030731 0.9800000 0.9765905 0.073098 0.0730831 NA
22 51232488 rs376461333 A G -0.0047666 0.0072471 0.5099998 0.5107097 0.020036 NA NA
22 51237063 rs3896457 T C 0.0017644 0.0018795 0.3500000 0.3478593 0.298017 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  -0.00509141:0.00282099:1.14874:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400452 ES:SE:LP:AF:ID  0.000343525:0.00279504:0.0457575:0.400452:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103528 ES:SE:LP:AF:ID  0.000428052:0.00446809:0.0362122:0.103528:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456842 ES:SE:LP:AF:ID  -0.000920028:0.00275179:0.130768:0.456842:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074551 ES:SE:LP:AF:ID  -0.0009394:0.00542234:0.0655015:0.074551:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240993 ES:SE:LP:AF:ID  0.000984758:0.00314216:0.124939:0.240993:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913509 ES:SE:LP:AF:ID  -0.000775846:0.00392094:0.0757207:0.913509:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116357 ES:SE:LP:AF:ID  0.00600778:0.00263313:1.63827:0.116357:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067258 ES:SE:LP:AF:ID  -0.00413762:0.00386149:0.552842:0.067258:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515739 ES:SE:LP:AF:ID  -0.00422364:0.00195074:1.52288:0.515739:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032952 ES:SE:LP:AF:ID  -0.0105045:0.00492166:1.48149:0.032952:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036553 ES:SE:LP:AF:ID  -0.00896553:0.00447112:1.34679:0.036553:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036672 ES:SE:LP:AF:ID  -0.00934038:0.0044538:1.4437:0.036672:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036368 ES:SE:LP:AF:ID  -0.00900046:0.00448629:1.34679:0.036368:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016418 ES:SE:LP:AF:ID  -3.18611e-05:0.00689967:-0:0.016418:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036901 ES:SE:LP:AF:ID  -0.0090274:0.00443695:1.37675:0.036901:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036999 ES:SE:LP:AF:ID  -0.00917994:0.00442154:1.42022:0.036999:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101101 ES:SE:LP:AF:ID  0.000813794:0.00321864:0.09691:0.101101:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959173 ES:SE:LP:AF:ID  0.00720468:0.00426464:1.04096:0.959173:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031435 ES:SE:LP:AF:ID  -0.0021504:0.00774023:0.107905:0.031435:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05322  ES:SE:LP:AF:ID  -0.00500909:0.00615861:0.376751:0.05322:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036516 ES:SE:LP:AF:ID  -0.00886166:0.0044504:1.33724:0.036516:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03683  ES:SE:LP:AF:ID  -0.0092293:0.00440996:1.4437:0.03683:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843226 ES:SE:LP:AF:ID  -0.00397992:0.00228225:1.09151:0.843226:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055938 ES:SE:LP:AF:ID  0.00881237:0.00369389:1.76955:0.055938:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122356 ES:SE:LP:AF:ID  0.00683433:0.00249746:2.20761:0.122356:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025694 ES:SE:LP:AF:ID  -0.00961276:0.00614836:0.920819:0.025694:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121599 ES:SE:LP:AF:ID  0.00693236:0.00249848:2.25964:0.121599:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132331 ES:SE:LP:AF:ID  0.00318142:0.0024628:0.69897:0.132331:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011163 ES:SE:LP:AF:ID  0.00119881:0.00894012:0.05061:0.011163:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005707 ES:SE:LP:AF:ID  0.0101585:0.0115486:0.420216:0.005707:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002266 ES:SE:LP:AF:ID  0.0208506:0.0194549:0.552842:0.002266:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.00103  ES:SE:LP:AF:ID  -0.0674247:0.0318412:1.46852:0.00103:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036746 ES:SE:LP:AF:ID  -0.00834685:0.00436546:1.25181:0.036746:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838967 ES:SE:LP:AF:ID  -0.00324622:0.00221014:0.853872:0.838967:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838596 ES:SE:LP:AF:ID  -0.00322556:0.00220776:0.853872:0.838596:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869737 ES:SE:LP:AF:ID  -0.00579327:0.0023687:1.85387:0.869737:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129909 ES:SE:LP:AF:ID  0.00575004:0.00237345:1.82391:0.129909:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037246 ES:SE:LP:AF:ID  -0.00809865:0.00429188:1.22915:0.037246:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037491 ES:SE:LP:AF:ID  -0.0082269:0.00426463:1.26761:0.037491:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869082 ES:SE:LP:AF:ID  -0.00579686:0.00236405:1.85387:0.869082:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869183 ES:SE:LP:AF:ID  -0.00581316:0.00236499:1.85387:0.869183:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037451 ES:SE:LP:AF:ID  -0.00857421:0.00428301:1.34679:0.037451:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869084 ES:SE:LP:AF:ID  -0.00580177:0.002364:1.85387:0.869084:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005132 ES:SE:LP:AF:ID  0.00324379:0.0121235:0.102373:0.005132:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005097 ES:SE:LP:AF:ID  0.00283378:0.012156:0.0861861:0.005097:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838058 ES:SE:LP:AF:ID  -0.00318193:0.00220176:0.823909:0.838058:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03746  ES:SE:LP:AF:ID  -0.00914028:0.00428935:1.48149:0.03746:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838682 ES:SE:LP:AF:ID  -0.00322454:0.00220789:0.853872:0.838682:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013815 ES:SE:LP:AF:ID  0.0128661:0.00769498:1.02228:0.013815:rs181660517