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-17241/UKB-b-17241_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17241/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17241/UKB-b-17241_data.vcf.gz ...
Read summary statistics for 9063994 SNPs.
Dropped 9017 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, 1287321 SNPs remain.
After merging with regression SNP LD, 1287321 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.065 (0.0038)
Lambda GC: 1.4046
Mean Chi^2: 1.694
Intercept: 1.0928 (0.0125)
Ratio: 0.1337 (0.018)
Analysis finished at Thu Oct 17 14:42:04 2019
Total time elapsed: 1.0m:45.34s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -1.7165e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 151,
    "n_p_sig": 21269,
    "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": 96382,
    "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": 1287321,
    "ldsc_nsnp_merge_regression_ld": 1287321,
    "ldsc_observed_scale_h2_beta": 0.065,
    "ldsc_observed_scale_h2_se": 0.0038,
    "ldsc_intercept_beta": 1.0928,
    "ldsc_intercept_se": 0.0125,
    "ldsc_lambda_gc": 1.4046,
    "ldsc_mean_chisq": 1.694,
    "ldsc_ratio": 0.1337
}

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 9055018 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 9063994 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 8.641836e+00 5.757725e+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 7.879345e+07 5.633252e+07 828.0000000 3.244571e+07 6.936180e+07 1.145321e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.700000e-06 3.200600e-03 -0.0545964 -1.313800e-03 -7.000000e-06 1.298300e-03 5.325370e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.342100e-03 1.739700e-03 0.0008388 1.001300e-03 1.542700e-03 3.213500e-03 1.943000e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.557257e-01 3.011288e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.557268e-01 3.011053e-01 0.0000000 1.839094e-01 4.408071e-01 7.166445e-01 9.999994e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.189173e-01 2.584093e-01 0.0032960 1.986200e-02 9.967500e-02 3.451160e-01 9.967040e-01 ▇▂▁▁▁
numeric AF_reference 96382 0.9893665 NA NA NA NA NA NA NA 2.193081e-01 2.502898e-01 0.0000000 1.697280e-02 1.172120e-01 3.436500e-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 -0.0002830 0.0015422 0.8499999 0.8544004 0.623775 0.7821490 NA
1 54676 rs2462492 C T -0.0007739 0.0015276 0.6100002 0.6124149 0.400400 NA NA
1 86028 rs114608975 T C -0.0006491 0.0024425 0.7899998 0.7904321 0.103554 0.0277556 NA
1 91536 rs6702460 G T -0.0010639 0.0015041 0.4799997 0.4793694 0.456851 0.4207270 NA
1 234313 rs8179466 C T 0.0022314 0.0029658 0.4500005 0.4518187 0.074510 NA NA
1 534192 rs6680723 C T -0.0002279 0.0017183 0.8900000 0.8944910 0.240953 NA NA
1 546697 rs12025928 A G 0.0009529 0.0021431 0.6600001 0.6565851 0.913457 NA NA
1 693731 rs12238997 A G -0.0008442 0.0014399 0.5600000 0.5576960 0.116345 0.1417730 NA
1 705882 rs72631875 G A -0.0002667 0.0021100 0.9000000 0.8994133 0.067291 0.0315495 NA
1 706368 rs55727773 A G 0.0008267 0.0010667 0.4400003 0.4383473 0.515623 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0004529 0.0012886 0.7300002 0.7252577 0.137929 0.2052720 NA
22 51219387 rs9616832 T C 0.0012511 0.0016727 0.4500005 0.4545087 0.073728 0.0654952 NA
22 51219704 rs147475742 G A 0.0034979 0.0022413 0.1199999 0.1186107 0.041951 0.0473243 NA
22 51221190 rs369304721 G A 0.0013517 0.0022378 0.5500004 0.5458262 0.049721 NA NA
22 51221731 rs115055839 T C 0.0010543 0.0016738 0.5300002 0.5287474 0.073218 0.0625000 NA
22 51222100 rs114553188 G T -0.0017927 0.0019702 0.3599996 0.3628678 0.054458 0.0880591 NA
22 51223637 rs375798137 G A -0.0018113 0.0019798 0.3599996 0.3602337 0.054087 0.0788738 NA
22 51229805 rs9616985 T C 0.0011204 0.0016798 0.5000000 0.5047797 0.073054 0.0730831 NA
22 51232488 rs376461333 A G -0.0006288 0.0039567 0.8700001 0.8737240 0.020042 NA NA
22 51237063 rs3896457 T C -0.0024392 0.0010273 0.0179999 0.0175741 0.297980 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623775 ES:SE:LP:AF:ID  -0.000282995:0.00154215:0.0705811:0.623775:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.4004   ES:SE:LP:AF:ID  -0.000773927:0.0015276:0.21467:0.4004:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103554 ES:SE:LP:AF:ID  -0.000649096:0.00244251:0.102373:0.103554:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -0.00106389:0.00150412:0.318759:0.456851:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07451  ES:SE:LP:AF:ID  0.00223139:0.00296575:0.346787:0.07451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240953 ES:SE:LP:AF:ID  -0.000227886:0.00171829:0.05061:0.240953:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913457 ES:SE:LP:AF:ID  0.000952906:0.00214313:0.180456:0.913457:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116345 ES:SE:LP:AF:ID  -0.000844166:0.0014399:0.251812:0.116345:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067291 ES:SE:LP:AF:ID  -0.000266703:0.00210995:0.0457575:0.067291:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515623 ES:SE:LP:AF:ID  0.000826671:0.00106669:0.356547:0.515623:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032997 ES:SE:LP:AF:ID  0.0032104:0.00268944:0.638272:0.032997:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036613 ES:SE:LP:AF:ID  0.0025866:0.00244283:0.537602:0.036613:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03673  ES:SE:LP:AF:ID  0.00270155:0.0024336:0.568636:0.03673:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036429 ES:SE:LP:AF:ID  0.00265463:0.00245115:0.552842:0.036429:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016412 ES:SE:LP:AF:ID  -0.00143125:0.00377308:0.154902:0.016412:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036969 ES:SE:LP:AF:ID  0.00273618:0.00242394:0.585027:0.036969:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  0.00270238:0.00241564:0.585027:0.037066:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101232 ES:SE:LP:AF:ID  -0.000634952:0.0017596:0.142668:0.101232:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959107 ES:SE:LP:AF:ID  -0.00250554:0.00233002:0.552842:0.959107:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  -0.00115537:0.00422885:0.107905:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.000401568:0.00336379:0.0457575:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036585 ES:SE:LP:AF:ID  0.0021333:0.00243124:0.420216:0.036585:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.0369   ES:SE:LP:AF:ID  0.00231574:0.00240914:0.468521:0.0369:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843205 ES:SE:LP:AF:ID  0.000329301:0.00124795:0.102373:0.843205:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055924 ES:SE:LP:AF:ID  -0.00291277:0.0020204:0.823909:0.055924:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122325 ES:SE:LP:AF:ID  -0.000856304:0.00136591:0.275724:0.122325:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025712 ES:SE:LP:AF:ID  -0.00100918:0.0033601:0.119186:0.025712:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121569 ES:SE:LP:AF:ID  -0.000926417:0.00136648:0.30103:0.121569:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  -0.000340057:0.00134688:0.09691:0.132336:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011128 ES:SE:LP:AF:ID  0.010312:0.00489814:1.45593:0.011128:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005703 ES:SE:LP:AF:ID  -0.00384589:0.00631959:0.267606:0.005703:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036813 ES:SE:LP:AF:ID  0.0019022:0.00238484:0.366532:0.036813:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83894  ES:SE:LP:AF:ID  6.85752e-05:0.00120856:0.0222764:0.83894:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838567 ES:SE:LP:AF:ID  8.26549e-05:0.00120725:0.0222764:0.838567:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869759 ES:SE:LP:AF:ID  0.000442204:0.00129541:0.136677:0.869759:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  -0.000712623:0.00129805:0.236572:0.129892:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037324 ES:SE:LP:AF:ID  0.00192628:0.00234441:0.387216:0.037324:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037568 ES:SE:LP:AF:ID  0.00197363:0.0023296:0.39794:0.037568:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  0.00051113:0.00129287:0.161151:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869199 ES:SE:LP:AF:ID  0.000452629:0.00129339:0.136677:0.869199:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  0.00208821:0.00233967:0.431798:0.037526:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  0.000522585:0.00129284:0.161151:0.869104:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005127 ES:SE:LP:AF:ID  7.11438e-06:0.00663421:-0:0.005127:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005093 ES:SE:LP:AF:ID  -6.40881e-06:0.00665158:-0:0.005093:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83802  ES:SE:LP:AF:ID  7.91296e-05:0.0012039:0.0222764:0.83802:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  0.00213442:0.00234297:0.443698:0.037539:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83865  ES:SE:LP:AF:ID  6.63925e-05:0.00120729:0.0177288:0.83865:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013773 ES:SE:LP:AF:ID  0.00635945:0.00421392:0.886057:0.013773:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005545 ES:SE:LP:AF:ID  -0.00125526:0.00650264:0.0705811:0.005545:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839764 ES:SE:LP:AF:ID  0.000198476:0.00122361:0.0604807:0.839764:rs3131965