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-6848/UKB-b-6848_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6848/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6848/UKB-b-6848_data.vcf.gz ...
Read summary statistics for 8846533 SNPs.
Dropped 8082 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, 1286619 SNPs remain.
After merging with regression SNP LD, 1286619 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0609 (0.0044)
Lambda GC: 1.1657
Mean Chi^2: 1.1832
Intercept: 1.0018 (0.0066)
Ratio: 0.0097 (0.0363)
Analysis finished at Thu Oct 17 14:41:48 2019
Total time elapsed: 1.0m:30.67s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9472,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 9.2279e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 6,
    "n_p_sig": 643,
    "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": 88106,
    "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": 1286619,
    "ldsc_nsnp_merge_regression_ld": 1286619,
    "ldsc_observed_scale_h2_beta": 0.0609,
    "ldsc_observed_scale_h2_se": 0.0044,
    "ldsc_intercept_beta": 1.0018,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.1657,
    "ldsc_mean_chisq": 1.1832,
    "ldsc_ratio": 0.0098
}

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 8838490 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 8846533 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 8.647793e+00 5.760085e+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 7.877558e+07 5.634741e+07 828.0000000 3.240817e+07 6.932496e+07 1.145515e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.200000e-06 5.796600e-03 -0.0749254 -2.406200e-03 3.500000e-06 2.424400e-03 6.671140e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.608500e-03 3.271000e-03 0.0017406 2.064100e-03 3.109700e-03 6.290900e-03 4.011250e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.803569e-01 2.934539e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.803564e-01 2.934291e-01 0.0000000 2.220894e-01 4.734421e-01 7.340734e-01 9.999999e-01 ▇▇▇▇▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.238437e-01 2.589403e-01 0.0043420 2.236800e-02 1.066480e-01 3.535320e-01 9.956580e-01 ▇▂▁▁▁
numeric AF_reference 88106 0.9900406 NA NA NA NA NA NA NA 2.238710e-01 2.508909e-01 0.0000000 1.976840e-02 1.236020e-01 3.514380e-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 -0.0053741 0.0032077 0.0940005 0.0938634 0.623658 0.7821490 NA
1 54676 rs2462492 C T 0.0018270 0.0031863 0.5700002 0.5663803 0.399273 NA NA
1 86028 rs114608975 T C 0.0114177 0.0050749 0.0239999 0.0244601 0.103854 0.0277556 NA
1 91536 rs6702460 G T -0.0003467 0.0031396 0.9100000 0.9120793 0.456191 0.4207270 NA
1 234313 rs8179466 C T 0.0032416 0.0062014 0.5999997 0.6011624 0.074497 NA NA
1 534192 rs6680723 C T 0.0003094 0.0035882 0.9299999 0.9312832 0.241144 NA NA
1 546697 rs12025928 A G -0.0033623 0.0044509 0.4500005 0.4499965 0.913070 NA NA
1 693731 rs12238997 A G -0.0049293 0.0029902 0.0990011 0.0992516 0.116954 0.1417730 NA
1 705882 rs72631875 G A 0.0012726 0.0043724 0.7700005 0.7710071 0.067636 0.0315495 NA
1 706368 rs55727773 A G -0.0000835 0.0022152 0.9699999 0.9699360 0.514890 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0012876 0.0026842 0.6300007 0.6314345 0.136970 0.2052720 NA
22 51219387 rs9616832 T C -0.0013534 0.0034916 0.6999999 0.6982952 0.072649 0.0654952 NA
22 51219704 rs147475742 G A -0.0062168 0.0046600 0.1800002 0.1821816 0.041641 0.0473243 NA
22 51221190 rs369304721 G A -0.0026763 0.0046735 0.5700002 0.5668792 0.049048 NA NA
22 51221731 rs115055839 T C -0.0014031 0.0034942 0.6899999 0.6880182 0.072125 0.0625000 NA
22 51222100 rs114553188 G T 0.0052179 0.0040890 0.2000000 0.2019197 0.054415 0.0880591 NA
22 51223637 rs375798137 G A 0.0048252 0.0041100 0.2399999 0.2403899 0.054025 0.0788738 NA
22 51229805 rs9616985 T C -0.0014274 0.0035069 0.6800001 0.6839984 0.071986 0.0730831 NA
22 51232488 rs376461333 A G 0.0078873 0.0082200 0.3400001 0.3372917 0.020135 NA NA
22 51237063 rs3896457 T C -0.0003986 0.0021303 0.8499999 0.8515653 0.297770 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623658 ES:SE:LP:AF:ID  -0.00537409:0.00320772:1.02687:0.623658:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399273 ES:SE:LP:AF:ID  0.001827:0.00318631:0.244125:0.399273:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103854 ES:SE:LP:AF:ID  0.0114177:0.00507493:1.61979:0.103854:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456191 ES:SE:LP:AF:ID  -0.000346667:0.00313964:0.0409586:0.456191:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074497 ES:SE:LP:AF:ID  0.00324165:0.00620139:0.221849:0.074497:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241144 ES:SE:LP:AF:ID  0.000309414:0.00358822:0.0315171:0.241144:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91307  ES:SE:LP:AF:ID  -0.00336228:0.00445087:0.346787:0.91307:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116954 ES:SE:LP:AF:ID  -0.00492929:0.00299018:1.00436:0.116954:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067636 ES:SE:LP:AF:ID  0.00127263:0.00437243:0.113509:0.067636:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51489  ES:SE:LP:AF:ID  -8.34887e-05:0.00221523:0.0132283:0.51489:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033635 ES:SE:LP:AF:ID  0.00474779:0.00552943:0.408935:0.033635:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037358 ES:SE:LP:AF:ID  0.00349841:0.00502059:0.309804:0.037358:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037484 ES:SE:LP:AF:ID  0.0044162:0.00500119:0.420216:0.037484:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037132 ES:SE:LP:AF:ID  0.00393738:0.00503978:0.366532:0.037132:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016379 ES:SE:LP:AF:ID  -0.0117212:0.00786852:0.853872:0.016379:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037724 ES:SE:LP:AF:ID  0.004361:0.0049813:0.420216:0.037724:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037814 ES:SE:LP:AF:ID  0.00411557:0.00496567:0.387216:0.037814:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101496 ES:SE:LP:AF:ID  -0.00130288:0.00364864:0.142668:0.101496:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958223 ES:SE:LP:AF:ID  -0.00587054:0.00479104:0.657577:0.958223:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031689 ES:SE:LP:AF:ID  0.00366893:0.0087719:0.167491:0.031689:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052682 ES:SE:LP:AF:ID  -0.00644215:0.0070723:0.443698:0.052682:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037284 ES:SE:LP:AF:ID  0.00466061:0.00500025:0.455932:0.037284:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037618 ES:SE:LP:AF:ID  0.00445498:0.0049554:0.431798:0.037618:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841862 ES:SE:LP:AF:ID  0.00199509:0.00258782:0.356547:0.841862:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056081 ES:SE:LP:AF:ID  0.00126044:0.00420472:0.119186:0.056081:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122885 ES:SE:LP:AF:ID  -0.00387319:0.00283801:0.769551:0.122885:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025798 ES:SE:LP:AF:ID  0.000113936:0.00697252:0.00436481:0.025798:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122104 ES:SE:LP:AF:ID  -0.00381609:0.00283938:0.744727:0.122104:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133451 ES:SE:LP:AF:ID  -0.00205673:0.00279278:0.337242:0.133451:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011257 ES:SE:LP:AF:ID  -0.00970976:0.0101191:0.468521:0.011257:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005876 ES:SE:LP:AF:ID  -0.00591912:0.0129071:0.187087:0.005876:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037552 ES:SE:LP:AF:ID  0.00385729:0.00490515:0.366532:0.037552:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837647 ES:SE:LP:AF:ID  0.00166419:0.00250649:0.29243:0.837647:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837256 ES:SE:LP:AF:ID  0.0018511:0.00250368:0.337242:0.837256:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869028 ES:SE:LP:AF:ID  0.00227765:0.00268797:0.39794:0.869028:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130675 ES:SE:LP:AF:ID  -0.00253616:0.00269334:0.455932:0.130675:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038039 ES:SE:LP:AF:ID  0.004205:0.00482529:0.420216:0.038039:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038293 ES:SE:LP:AF:ID  0.00473592:0.0047946:0.49485:0.038293:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868348 ES:SE:LP:AF:ID  0.00232753:0.0026826:0.408935:0.868348:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868456 ES:SE:LP:AF:ID  0.00226499:0.00268382:0.39794:0.868456:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038227 ES:SE:LP:AF:ID  0.00469528:0.00481525:0.481486:0.038227:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868345 ES:SE:LP:AF:ID  0.00232837:0.00268243:0.408935:0.868345:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005108 ES:SE:LP:AF:ID  -0.0120908:0.0138515:0.420216:0.005108:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005078 ES:SE:LP:AF:ID  -0.0122745:0.013882:0.420216:0.005078:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.836752 ES:SE:LP:AF:ID  0.00168923:0.00249748:0.30103:0.836752:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038237 ES:SE:LP:AF:ID  0.00472491:0.00482202:0.481486:0.038237:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837386 ES:SE:LP:AF:ID  0.00171377:0.00250445:0.309804:0.837386:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013275 ES:SE:LP:AF:ID  -0.00229993:0.00895554:0.09691:0.013275:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005453 ES:SE:LP:AF:ID  -0.000280741:0.0136168:0.00877392:0.005453:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838633 ES:SE:LP:AF:ID  0.000877403:0.00253882:0.136677:0.838633:rs3131965