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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}
 

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-12477/UKB-b-12477_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12477/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:58 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12477/UKB-b-12477_data.vcf.gz ...
Read summary statistics for 8893604 SNPs.
Dropped 8260 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, 1286763 SNPs remain.
After merging with regression SNP LD, 1286763 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0161 (0.0016)
Lambda GC: 1.16
Mean Chi^2: 1.1851
Intercept: 1.0498 (0.0066)
Ratio: 0.2693 (0.0358)
Analysis finished at Thu Oct 17 14:43:41 2019
Total time elapsed: 1.0m:42.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9472,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -4.9188e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 9,
    "n_p_sig": 429,
    "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": 89576,
    "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": 1286763,
    "ldsc_nsnp_merge_regression_ld": 1286763,
    "ldsc_observed_scale_h2_beta": 0.0161,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0498,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.16,
    "ldsc_mean_chisq": 1.1851,
    "ldsc_ratio": 0.269
}
 

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 1.000000 3 58 0 8885383 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 8893604 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.646415e+00 5.759639e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.878561e+07 5.634305e+07 828.0000000 3.242226e+07 6.934426e+07 1.145592e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -4.900000e-06 2.869600e-03 -0.0316196 -1.169100e-03 -4.100000e-06 1.160800e-03 4.497680e-02 ▁▃▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 2.238800e-03 1.603900e-03 0.0008358 9.928000e-04 1.503300e-03 3.061500e-03 1.931470e-02 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.797752e-01 2.946096e-01 0.0000000 2.200002e-01 4.700002e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.797753e-01 2.945854e-01 0.0000000 2.192480e-01 4.726475e-01 7.354034e-01 9.999999e-01 ▇▇▇▆▆
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.227285e-01 2.588267e-01 0.0040880 2.177900e-02 1.050900e-01 3.516350e-01 9.959120e-01 ▇▂▁▁▁
numeric AF_reference 89576 0.989928 NA NA NA NA NA NA NA 2.228142e-01 2.507545e-01 0.0000000 1.916930e-02 1.222040e-01 3.496410e-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 -0.0005918 0.0015388 0.6999999 0.7005357 0.623849 0.7821490 NA
1 54676 rs2462492 C T 0.0023380 0.0015233 0.1199999 0.1248398 0.400441 NA NA
1 86028 rs114608975 T C -0.0009004 0.0024356 0.7099994 0.7116189 0.103559 0.0277556 NA
1 91536 rs6702460 G T 0.0005695 0.0015003 0.6999999 0.7042814 0.456992 0.4207270 NA
1 234313 rs8179466 C T 0.0003038 0.0029594 0.9199999 0.9182315 0.074520 NA NA
1 534192 rs6680723 C T -0.0020853 0.0017142 0.2200002 0.2237905 0.240977 NA NA
1 546697 rs12025928 A G -0.0024783 0.0021365 0.2500000 0.2460482 0.913389 NA NA
1 693731 rs12238997 A G 0.0005145 0.0014367 0.7199992 0.7202466 0.116241 0.1417730 NA
1 705882 rs72631875 G A -0.0009292 0.0021033 0.6600001 0.6586332 0.067391 0.0315495 NA
1 706368 rs55727773 A G -0.0008688 0.0010640 0.4100001 0.4142080 0.515846 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0001709 0.0012841 0.8900000 0.8940954 0.137842 0.2052720 NA
22 51219387 rs9616832 T C 0.0007165 0.0016668 0.6700003 0.6672984 0.073701 0.0654952 NA
22 51219704 rs147475742 G A -0.0003052 0.0022341 0.8900000 0.8913382 0.041921 0.0473243 NA
22 51221190 rs369304721 G A 0.0009831 0.0022296 0.6600001 0.6592460 0.049703 NA NA
22 51221731 rs115055839 T C 0.0007270 0.0016677 0.6600001 0.6628992 0.073196 0.0625000 NA
22 51222100 rs114553188 G T -0.0018864 0.0019630 0.3400001 0.3365531 0.054424 0.0880591 NA
22 51223637 rs375798137 G A -0.0019534 0.0019724 0.3200000 0.3219971 0.054053 0.0788738 NA
22 51229805 rs9616985 T C 0.0006704 0.0016738 0.6899999 0.6887500 0.073029 0.0730831 NA
22 51232488 rs376461333 A G -0.0050531 0.0039401 0.2000000 0.1996726 0.020033 NA NA
22 51237063 rs3896457 T C 0.0006677 0.0010234 0.5099998 0.5140988 0.298167 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623849 ES:SE:LP:AF:ID  -0.000591834:0.00153884:0.154902:0.623849:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400441 ES:SE:LP:AF:ID  0.00233798:0.00152334:0.920819:0.400441:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103559 ES:SE:LP:AF:ID  -0.000900392:0.00243558:0.148742:0.103559:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456992 ES:SE:LP:AF:ID  0.000569454:0.00150035:0.154902:0.456992:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07452  ES:SE:LP:AF:ID  0.000303819:0.00295942:0.0362122:0.07452:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240977 ES:SE:LP:AF:ID  -0.00208533:0.00171419:0.657577:0.240977:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913389 ES:SE:LP:AF:ID  -0.00247832:0.00213648:0.60206:0.913389:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116241 ES:SE:LP:AF:ID  0.00051451:0.00143666:0.142668:0.116241:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067391 ES:SE:LP:AF:ID  -0.00092924:0.0021033:0.180456:0.067391:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515846 ES:SE:LP:AF:ID  -0.000868784:0.00106402:0.387216:0.515846:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033    ES:SE:LP:AF:ID  -0.000775861:0.00268205:0.113509:0.033:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036629 ES:SE:LP:AF:ID  -0.00129806:0.00243554:0.229148:0.036629:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036738 ES:SE:LP:AF:ID  -0.00136111:0.00242663:0.244125:0.036738:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036441 ES:SE:LP:AF:ID  -0.00141887:0.00244404:0.251812:0.036441:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016425 ES:SE:LP:AF:ID  0.00338413:0.00376133:0.431798:0.016425:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036979 ES:SE:LP:AF:ID  -0.00115727:0.002417:0.200659:0.036979:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037075 ES:SE:LP:AF:ID  -0.00136877:0.00240871:0.244125:0.037075:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101242 ES:SE:LP:AF:ID  -0.000693226:0.00175472:0.161151:0.101242:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959115 ES:SE:LP:AF:ID  0.00173919:0.00232397:0.346787:0.959115:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031476 ES:SE:LP:AF:ID  -0.00403832:0.00421439:0.468521:0.031476:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053304 ES:SE:LP:AF:ID  -6.40164e-05:0.00335148:0.00877392:0.053304:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036592 ES:SE:LP:AF:ID  -0.00170799:0.00242438:0.318759:0.036592:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036906 ES:SE:LP:AF:ID  -0.00112338:0.00240242:0.19382:0.036906:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843277 ES:SE:LP:AF:ID  0.000167414:0.00124468:0.05061:0.843277:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055857 ES:SE:LP:AF:ID  -0.00170769:0.0020164:0.39794:0.055857:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12223  ES:SE:LP:AF:ID  0.000485334:0.00136273:0.142668:0.12223:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025726 ES:SE:LP:AF:ID  -0.00612821:0.00334848:1.17393:0.025726:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121477 ES:SE:LP:AF:ID  0.000492659:0.00136329:0.142668:0.121477:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132287 ES:SE:LP:AF:ID  -0.000522535:0.00134353:0.154902:0.132287:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011092 ES:SE:LP:AF:ID  0.00637401:0.00489423:0.721246:0.011092:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005697 ES:SE:LP:AF:ID  -0.00303763:0.00630507:0.200659:0.005697:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03683  ES:SE:LP:AF:ID  -0.00130441:0.0023778:0.236572:0.03683:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838993 ES:SE:LP:AF:ID  -0.000214305:0.00120549:0.0655015:0.838993:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838621 ES:SE:LP:AF:ID  -0.00010714:0.00120414:0.0315171:0.838621:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86987  ES:SE:LP:AF:ID  -0.000664572:0.00129247:0.21467:0.86987:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129784 ES:SE:LP:AF:ID  0.000423022:0.00129509:0.130768:0.129784:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037334 ES:SE:LP:AF:ID  -0.000891594:0.00233778:0.154902:0.037334:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037575 ES:SE:LP:AF:ID  -0.000818442:0.00232315:0.142668:0.037575:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -0.000484655:0.0012899:0.148742:0.869214:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86931  ES:SE:LP:AF:ID  -0.000486948:0.00129039:0.148742:0.86931:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  -0.000992119:0.00233304:0.173925:0.037535:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  -0.000477664:0.00128987:0.148742:0.869215:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005118 ES:SE:LP:AF:ID  -0.00190987:0.00662431:0.113509:0.005118:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005083 ES:SE:LP:AF:ID  -0.00152844:0.00664187:0.0861861:0.005083:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83807  ES:SE:LP:AF:ID  -0.000118522:0.00120078:0.0362122:0.83807:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.000990629:0.00233643:0.173925:0.037545:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838704 ES:SE:LP:AF:ID  -8.40573e-05:0.00120418:0.0268721:0.838704:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013752 ES:SE:LP:AF:ID  -0.00200242:0.00420571:0.200659:0.013752:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005552 ES:SE:LP:AF:ID  0.00660854:0.00647922:0.508638:0.005552:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839813 ES:SE:LP:AF:ID  -0.000235603:0.00122047:0.0705811:0.839813:rs3131965