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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}

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-5764/UKB-b-5764_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5764/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:36 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5764/UKB-b-5764_data.vcf.gz ...
Read summary statistics for 8714070 SNPs.
Dropped 7620 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, 1286136 SNPs remain.
After merging with regression SNP LD, 1286136 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0127 (0.0062)
Lambda GC: 1.032
Mean Chi^2: 1.0311
Intercept: 1.0134 (0.006)
Ratio: 0.4308 (0.192)
Analysis finished at Thu Oct 17 14:47:02 2019
Total time elapsed: 1.0m:26.15s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9468,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 84783,
    "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": 1286136,
    "ldsc_nsnp_merge_regression_ld": 1286136,
    "ldsc_observed_scale_h2_beta": 0.0127,
    "ldsc_observed_scale_h2_se": 0.0062,
    "ldsc_intercept_beta": 1.0134,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.032,
    "ldsc_mean_chisq": 1.0311,
    "ldsc_ratio": 0.4309
}

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 8706485 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 8714070 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 8.649483e+00 5.760914e+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 7.877019e+07 5.635897e+07 828.0000000 3.239339e+07 6.929995e+07 1.145647e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.890000e-05 5.852200e-03 -0.0509009 -2.412400e-03 -1.460000e-05 2.382200e-03 8.809140e-02 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.755800e-03 3.296500e-03 0.0018520 2.187200e-03 3.252500e-03 6.454800e-03 3.326140e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.947052e-01 2.899692e-01 0.0000001 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.947069e-01 2.899433e-01 0.0000001 2.417416e-01 4.928029e-01 7.457366e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.269976e-01 2.592660e-01 0.0050340 2.408100e-02 1.109260e-01 3.588720e-01 9.949660e-01 ▇▂▁▁▁
numeric AF_reference 84783 0.9902706 NA NA NA NA NA NA NA 2.268546e-01 2.512533e-01 0.0000000 2.176520e-02 1.277960e-01 3.562300e-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 0.0025072 0.0034198 0.4600002 0.4634766 0.623917 0.7821490 NA
1 54676 rs2462492 C T -0.0055774 0.0033977 0.1000000 0.1006850 0.399212 NA NA
1 86028 rs114608975 T C 0.0076163 0.0053854 0.1600000 0.1572918 0.104023 0.0277556 NA
1 91536 rs6702460 G T 0.0012003 0.0033438 0.7199992 0.7196194 0.456271 0.4207270 NA
1 234313 rs8179466 C T 0.0075845 0.0065329 0.2500000 0.2456546 0.074930 NA NA
1 534192 rs6680723 C T -0.0054536 0.0038238 0.1499999 0.1538025 0.240426 NA NA
1 546697 rs12025928 A G 0.0076282 0.0047431 0.1100001 0.1077793 0.912563 NA NA
1 693731 rs12238997 A G -0.0047537 0.0031817 0.1400000 0.1351547 0.117206 0.1417730 NA
1 705882 rs72631875 G A -0.0023798 0.0046377 0.6100002 0.6078510 0.067977 0.0315495 NA
1 706368 rs55727773 A G 0.0015047 0.0023576 0.5199996 0.5233207 0.513916 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0006686 0.0028507 0.8100000 0.8145661 0.136749 0.2052720 NA
22 51219387 rs9616832 T C 0.0021597 0.0037169 0.5600000 0.5612055 0.072414 0.0654952 NA
22 51219704 rs147475742 G A -0.0035757 0.0049718 0.4700002 0.4720260 0.041167 0.0473243 NA
22 51221190 rs369304721 G A 0.0045738 0.0049928 0.3599996 0.3596250 0.048648 NA NA
22 51221731 rs115055839 T C 0.0021222 0.0037178 0.5700002 0.5681157 0.071924 0.0625000 NA
22 51222100 rs114553188 G T -0.0045883 0.0043491 0.2900000 0.2914264 0.054179 0.0880591 NA
22 51223637 rs375798137 G A -0.0044883 0.0043719 0.2999998 0.3045961 0.053789 0.0788738 NA
22 51229805 rs9616985 T C 0.0022008 0.0037314 0.5600000 0.5553246 0.071798 0.0730831 NA
22 51232488 rs376461333 A G -0.0134070 0.0088299 0.1299999 0.1289245 0.019912 NA NA
22 51237063 rs3896457 T C 0.0021280 0.0022664 0.3500000 0.3477600 0.297729 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623917 ES:SE:LP:AF:ID  0.00250715:0.00341977:0.337242:0.623917:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399212 ES:SE:LP:AF:ID  -0.00557745:0.00339769:1:0.399212:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104023 ES:SE:LP:AF:ID  0.00761627:0.00538542:0.79588:0.104023:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456271 ES:SE:LP:AF:ID  0.00120033:0.00334384:0.142668:0.456271:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07493  ES:SE:LP:AF:ID  0.00758454:0.00653294:0.60206:0.07493:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240426 ES:SE:LP:AF:ID  -0.00545364:0.00382382:0.823909:0.240426:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912563 ES:SE:LP:AF:ID  0.00762818:0.00474314:0.958607:0.912563:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117206 ES:SE:LP:AF:ID  -0.00475373:0.00318171:0.853872:0.117206:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067977 ES:SE:LP:AF:ID  -0.0023798:0.00463769:0.21467:0.067977:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513916 ES:SE:LP:AF:ID  0.00150469:0.00235758:0.283997:0.513916:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033782 ES:SE:LP:AF:ID  0.00452636:0.00586235:0.356547:0.033782:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037483 ES:SE:LP:AF:ID  0.00446223:0.00533049:0.39794:0.037483:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037575 ES:SE:LP:AF:ID  0.00468417:0.00531209:0.420216:0.037575:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037256 ES:SE:LP:AF:ID  0.00463804:0.00535056:0.408935:0.037256:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016282 ES:SE:LP:AF:ID  -0.0104315:0.008397:0.677781:0.016282:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037852 ES:SE:LP:AF:ID  0.00421077:0.00528888:0.366532:0.037852:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037934 ES:SE:LP:AF:ID  0.00405029:0.00527249:0.356547:0.037934:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101537 ES:SE:LP:AF:ID  0.00258317:0.00389543:0.29243:0.101537:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.957886 ES:SE:LP:AF:ID  -0.00225228:0.00507645:0.180456:0.957886:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031528 ES:SE:LP:AF:ID  -0.0071275:0.00945017:0.346787:0.031528:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.0526   ES:SE:LP:AF:ID  0.00391444:0.0074982:0.221849:0.0526:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037391 ES:SE:LP:AF:ID  0.00388124:0.00530926:0.337242:0.037391:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037723 ES:SE:LP:AF:ID  0.00434351:0.00526343:0.387216:0.037723:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841078 ES:SE:LP:AF:ID  0.00397998:0.00275062:0.823909:0.841078:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05615  ES:SE:LP:AF:ID  -0.00439202:0.00447158:0.481486:0.05615:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123195 ES:SE:LP:AF:ID  -0.00463565:0.00301825:0.920819:0.123195:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025605 ES:SE:LP:AF:ID  0.00702087:0.00746396:0.455932:0.025605:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122384 ES:SE:LP:AF:ID  -0.00450878:0.00302032:0.853872:0.122384:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133723 ES:SE:LP:AF:ID  -0.00360936:0.00297071:0.657577:0.133723:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011119 ES:SE:LP:AF:ID  -0.0117248:0.0108548:0.552842:0.011119:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006296 ES:SE:LP:AF:ID  -0.0183923:0.0132472:0.769551:0.006296:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03766  ES:SE:LP:AF:ID  0.00472758:0.00520902:0.443698:0.03766:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836969 ES:SE:LP:AF:ID  0.00324097:0.00266192:0.657577:0.836969:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836504 ES:SE:LP:AF:ID  0.00332121:0.00265861:0.677781:0.836504:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868542 ES:SE:LP:AF:ID  0.00465675:0.00285602:1:0.868542:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131164 ES:SE:LP:AF:ID  -0.004643:0.00286176:1:0.131164:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038096 ES:SE:LP:AF:ID  0.00496104:0.00512978:0.481486:0.038096:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038339 ES:SE:LP:AF:ID  0.00542268:0.00509862:0.537602:0.038339:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867831 ES:SE:LP:AF:ID  0.00478932:0.00285037:1.03152:0.867831:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867935 ES:SE:LP:AF:ID  0.0047364:0.00285181:1.01323:0.867935:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038316 ES:SE:LP:AF:ID  0.00519511:0.00511738:0.508638:0.038316:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867852 ES:SE:LP:AF:ID  0.00465712:0.0028503:1:0.867852:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005281 ES:SE:LP:AF:ID  0.000662585:0.0144278:0.0177288:0.005281:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005254 ES:SE:LP:AF:ID  0.000591765:0.0144629:0.0132283:0.005254:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.836056 ES:SE:LP:AF:ID  0.00347014:0.00265349:0.721246:0.836056:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038332 ES:SE:LP:AF:ID  0.0050832:0.00512454:0.49485:0.038332:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836684 ES:SE:LP:AF:ID  0.00341918:0.00266077:0.69897:0.836684:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.012828 ES:SE:LP:AF:ID  0.0235935:0.00967217:1.82391:0.012828:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005505 ES:SE:LP:AF:ID  -0.0194646:0.0144463:0.744727:0.005505:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838092 ES:SE:LP:AF:ID  0.00356637:0.00269862:0.721246:0.838092:rs3131965