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-8667/UKB-b-8667_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8667/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8667/UKB-b-8667_data.vcf.gz ...
Read summary statistics for 8783459 SNPs.
Dropped 7844 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, 1286305 SNPs remain.
After merging with regression SNP LD, 1286305 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0271 (0.0016)
Lambda GC: 1.2529
Mean Chi^2: 1.2853
Intercept: 1.0456 (0.0084)
Ratio: 0.1598 (0.0295)
Analysis finished at Thu Oct 17 14:43:34 2019
Total time elapsed: 1.0m:30.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9468,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 228,
    "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": 86407,
    "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": 1286305,
    "ldsc_nsnp_merge_regression_ld": 1286305,
    "ldsc_observed_scale_h2_beta": 0.0271,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0456,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.2529,
    "ldsc_mean_chisq": 1.2853,
    "ldsc_ratio": 0.1598
}

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 8775652 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 8783459 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 8.649606e+00 5.760599e+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 7.876917e+07 5.635156e+07 828.0000000 3.240006e+07 6.931170e+07 1.145501e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.380000e-05 2.539500e-03 -0.0278646 -1.072000e-03 8.900000e-06 1.093200e-03 3.151500e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.985800e-03 1.393700e-03 0.0007606 9.004000e-04 1.348600e-03 2.704100e-03 1.348280e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.713720e-01 2.964302e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.713724e-01 2.964054e-01 0.0000000 2.074581e-01 4.605808e-01 7.284208e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.252925e-01 2.591006e-01 0.0046510 2.314400e-02 1.085470e-01 3.560760e-01 9.953480e-01 ▇▂▁▁▁
numeric AF_reference 86407 0.9901625 NA NA NA NA NA NA NA 2.252137e-01 2.510571e-01 0.0000000 2.056710e-02 1.253990e-01 3.536340e-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 0.0006543 0.0013990 0.6400000 0.6399942 0.623753 0.7821490 NA
1 54676 rs2462492 C T 0.0006518 0.0013861 0.6400000 0.6381686 0.400454 NA NA
1 86028 rs114608975 T C -0.0021259 0.0022162 0.3400001 0.3374440 0.103524 0.0277556 NA
1 91536 rs6702460 G T 0.0027800 0.0013644 0.0420001 0.0416011 0.456846 0.4207270 NA
1 234313 rs8179466 C T 0.0032606 0.0026920 0.2300001 0.2258092 0.074454 NA NA
1 534192 rs6680723 C T 0.0008757 0.0015590 0.5700002 0.5743396 0.240925 NA NA
1 546697 rs12025928 A G -0.0015484 0.0019446 0.4299995 0.4258742 0.913452 NA NA
1 693731 rs12238997 A G -0.0009310 0.0013064 0.4799997 0.4760664 0.116419 0.1417730 NA
1 705882 rs72631875 G A -0.0001412 0.0019147 0.9400001 0.9412314 0.067320 0.0315495 NA
1 706368 rs55727773 A G -0.0012562 0.0009679 0.1900002 0.1943712 0.515716 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0002751 0.0011678 0.8100000 0.8137779 0.138010 0.2052720 NA
22 51219387 rs9616832 T C 0.0014383 0.0015155 0.3400001 0.3426068 0.073785 0.0654952 NA
22 51219704 rs147475742 G A 0.0013041 0.0020310 0.5199996 0.5208265 0.041966 0.0473243 NA
22 51221190 rs369304721 G A 0.0018669 0.0020273 0.3599996 0.3571254 0.049763 NA NA
22 51221731 rs115055839 T C 0.0014002 0.0015165 0.3599996 0.3558318 0.073275 0.0625000 NA
22 51222100 rs114553188 G T -0.0005282 0.0017857 0.7700005 0.7673879 0.054505 0.0880591 NA
22 51223637 rs375798137 G A -0.0006024 0.0017944 0.7400005 0.7370855 0.054131 0.0788738 NA
22 51229805 rs9616985 T C 0.0014280 0.0015220 0.3500000 0.3481279 0.073114 0.0730831 NA
22 51232488 rs376461333 A G -0.0023725 0.0035864 0.5099998 0.5082662 0.020046 NA NA
22 51237063 rs3896457 T C 0.0008347 0.0009309 0.3700002 0.3699302 0.298134 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623753 ES:SE:LP:AF:ID  0.000654322:0.001399:0.19382:0.623753:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400454 ES:SE:LP:AF:ID  0.000651824:0.00138609:0.19382:0.400454:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103524 ES:SE:LP:AF:ID  -0.00212586:0.00221622:0.468521:0.103524:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  0.00277999:0.00136442:1.37675:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074454 ES:SE:LP:AF:ID  0.00326063:0.00269201:0.638272:0.074454:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240925 ES:SE:LP:AF:ID  0.000875652:0.00155901:0.244125:0.240925:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913452 ES:SE:LP:AF:ID  -0.00154839:0.00194455:0.366532:0.913452:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116419 ES:SE:LP:AF:ID  -0.000931033:0.00130645:0.318759:0.116419:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06732  ES:SE:LP:AF:ID  -0.000141159:0.00191474:0.0268721:0.06732:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515716 ES:SE:LP:AF:ID  -0.00125615:0.00096794:0.721246:0.515716:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033039 ES:SE:LP:AF:ID  0.00483195:0.002439:1.31876:0.033039:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036662 ES:SE:LP:AF:ID  0.00446223:0.00221535:1.35655:0.036662:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036776 ES:SE:LP:AF:ID  0.00411442:0.00220709:1.20761:0.036776:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036472 ES:SE:LP:AF:ID  0.00376597:0.00222309:1.04576:0.036472:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016436 ES:SE:LP:AF:ID  -0.00095956:0.00342162:0.107905:0.016436:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037011 ES:SE:LP:AF:ID  0.00408117:0.00219847:1.20066:0.037011:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037111 ES:SE:LP:AF:ID  0.00407069:0.00219075:1.20066:0.037111:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101196 ES:SE:LP:AF:ID  0.000689978:0.00159724:0.173925:0.101196:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959073 ES:SE:LP:AF:ID  -0.00402331:0.00211353:1.24413:0.959073:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  -0.00214714:0.00383651:0.236572:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053304 ES:SE:LP:AF:ID  -0.0032762:0.00304927:0.552842:0.053304:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03662  ES:SE:LP:AF:ID  0.00382165:0.00220528:1.08092:0.03662:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03694  ES:SE:LP:AF:ID  0.00397042:0.00218509:1.16115:0.03694:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843075 ES:SE:LP:AF:ID  -0.000516888:0.00113217:0.187087:0.843075:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055932 ES:SE:LP:AF:ID  -0.0011228:0.00183332:0.267606:0.055932:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122406 ES:SE:LP:AF:ID  -0.000817435:0.00123919:0.29243:0.122406:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02569  ES:SE:LP:AF:ID  -0.00331167:0.00305091:0.552842:0.02569:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12165  ES:SE:LP:AF:ID  -0.000727953:0.0012397:0.251812:0.12165:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13245  ES:SE:LP:AF:ID  0.000549278:0.00122188:0.187087:0.13245:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011146 ES:SE:LP:AF:ID  -0.000990136:0.00443958:0.0861861:0.011146:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005703 ES:SE:LP:AF:ID  -8.30858e-05:0.00573574:0.00436481:0.005703:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036853 ES:SE:LP:AF:ID  0.00413838:0.00216309:1.25181:0.036853:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838787 ES:SE:LP:AF:ID  -0.000729113:0.00109628:0.29243:0.838787:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83841  ES:SE:LP:AF:ID  -0.000715797:0.00109508:0.29243:0.83841:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869649 ES:SE:LP:AF:ID  0.00042011:0.00117504:0.142668:0.869649:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130011 ES:SE:LP:AF:ID  -0.000451935:0.00117738:0.154902:0.130011:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03737  ES:SE:LP:AF:ID  0.00382002:0.00212619:1.14267:0.03737:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037615 ES:SE:LP:AF:ID  0.00366484:0.00211275:1.08092:0.037615:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868989 ES:SE:LP:AF:ID  0.000442093:0.00117272:0.148742:0.868989:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869088 ES:SE:LP:AF:ID  0.000493812:0.00117319:0.173925:0.869088:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037574 ES:SE:LP:AF:ID  0.0039414:0.00212187:1.20066:0.037574:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868993 ES:SE:LP:AF:ID  0.000408506:0.0011727:0.136677:0.868993:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005137 ES:SE:LP:AF:ID  0.00429603:0.00601238:0.327902:0.005137:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005103 ES:SE:LP:AF:ID  0.00435143:0.0060281:0.327902:0.005103:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83786  ES:SE:LP:AF:ID  -0.000597648:0.00109203:0.236572:0.83786:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037588 ES:SE:LP:AF:ID  0.00393509:0.00212481:1.19382:0.037588:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83849  ES:SE:LP:AF:ID  -0.000523716:0.00109509:0.200659:0.83849:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013747 ES:SE:LP:AF:ID  0.00416126:0.00382857:0.552842:0.013747:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005555 ES:SE:LP:AF:ID  -0.00129231:0.00589515:0.0809219:0.005555:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839607 ES:SE:LP:AF:ID  -0.000720789:0.00110996:0.283997:0.839607:rs3131965