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-12777/UKB-b-12777_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12777/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12777/UKB-b-12777_data.vcf.gz ...
Read summary statistics for 8572562 SNPs.
Dropped 7274 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, 1285543 SNPs remain.
After merging with regression SNP LD, 1285543 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0052 (0.0012)
Lambda GC: 1.0841
Mean Chi^2: 1.0858
Intercept: 1.045 (0.0059)
Ratio: 0.5249 (0.0686)
Analysis finished at Thu Oct 17 14:43:43 2019
Total time elapsed: 1.0m:36.05s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9459,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -4.2557e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 10,
    "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": 82226,
    "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": 1285543,
    "ldsc_nsnp_merge_regression_ld": 1285543,
    "ldsc_observed_scale_h2_beta": 0.0052,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.045,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0841,
    "ldsc_mean_chisq": 1.0858,
    "ldsc_ratio": 0.5245
}

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 TRUE
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 8565321 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 8572562 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 8.651789e+00 5.761503e+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 7.875973e+07 5.637463e+07 828.0000000 3.237126e+07 6.927275e+07 1.145570e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.300000e-06 2.400600e-03 -0.0248779 -1.024800e-03 -7.000000e-06 1.005600e-03 2.572020e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.944100e-03 1.314800e-03 0.0007800 9.183000e-04 1.347300e-03 2.622300e-03 1.387240e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.889880e-01 2.915184e-01 0.0000000 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.889896e-01 2.914913e-01 0.0000000 2.339630e-01 4.851065e-01 7.417116e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.303922e-01 2.596302e-01 0.0055730 2.591100e-02 1.156210e-01 3.646258e-01 9.944270e-01 ▇▂▁▁▁
numeric AF_reference 82226 0.9904082 NA NA NA NA NA NA NA 2.300802e-01 2.515813e-01 0.0000000 2.416130e-02 1.319890e-01 3.616210e-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 0.0009441 0.0014364 0.5099998 0.5110190 0.623732 0.7821490 NA
1 54676 rs2462492 C T 0.0010793 0.0014227 0.4500005 0.4480941 0.400445 NA NA
1 86028 rs114608975 T C 0.0026751 0.0022753 0.2399999 0.2397019 0.103497 0.0277556 NA
1 91536 rs6702460 G T 0.0013133 0.0014018 0.3500000 0.3488192 0.457072 0.4207270 NA
1 234313 rs8179466 C T -0.0012958 0.0027668 0.6400000 0.6395452 0.074423 NA NA
1 534192 rs6680723 C T -0.0030056 0.0016006 0.0599998 0.0604085 0.241064 NA NA
1 546697 rs12025928 A G 0.0018018 0.0019955 0.3700002 0.3665747 0.913427 NA NA
1 693731 rs12238997 A G -0.0017427 0.0013400 0.1900002 0.1934284 0.116308 0.1417730 NA
1 705882 rs72631875 G A 0.0005834 0.0019640 0.7700005 0.7664338 0.067386 0.0315495 NA
1 706368 rs55727773 A G -0.0001464 0.0009933 0.8800001 0.8827847 0.515623 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0004350 0.0011992 0.7199992 0.7167717 0.137819 0.2052720 NA
22 51219387 rs9616832 T C -0.0007155 0.0015560 0.6499995 0.6456260 0.073769 0.0654952 NA
22 51219704 rs147475742 G A -0.0003300 0.0020872 0.8700001 0.8743652 0.041892 0.0473243 NA
22 51221190 rs369304721 G A -0.0020207 0.0020815 0.3300000 0.3316506 0.049712 NA NA
22 51221731 rs115055839 T C -0.0008204 0.0015569 0.5999997 0.5982483 0.073255 0.0625000 NA
22 51222100 rs114553188 G T 0.0012232 0.0018344 0.5000000 0.5049119 0.054338 0.0880591 NA
22 51223637 rs375798137 G A 0.0010932 0.0018433 0.5500004 0.5531351 0.053972 0.0788738 NA
22 51229805 rs9616985 T C -0.0005884 0.0015624 0.7099994 0.7064893 0.073093 0.0730831 NA
22 51232488 rs376461333 A G 0.0035328 0.0036861 0.3400001 0.3378662 0.019973 NA NA
22 51237063 rs3896457 T C 0.0006299 0.0009554 0.5099998 0.5097264 0.297923 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623732 ES:SE:LP:AF:ID  0.000944083:0.00143641:0.29243:0.623732:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400445 ES:SE:LP:AF:ID  0.00107927:0.00142272:0.346787:0.400445:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103497 ES:SE:LP:AF:ID  0.00267512:0.00227528:0.619789:0.103497:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457072 ES:SE:LP:AF:ID  0.00131334:0.00140182:0.455932:0.457072:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074423 ES:SE:LP:AF:ID  -0.00129577:0.00276676:0.19382:0.074423:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241064 ES:SE:LP:AF:ID  -0.00300557:0.00160058:1.22185:0.241064:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913427 ES:SE:LP:AF:ID  0.00180178:0.00199553:0.431798:0.913427:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116308 ES:SE:LP:AF:ID  -0.00174274:0.00134005:0.721246:0.116308:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067386 ES:SE:LP:AF:ID  0.000583404:0.00196404:0.113509:0.067386:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515623 ES:SE:LP:AF:ID  -0.00014645:0.000993285:0.0555173:0.515623:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033047 ES:SE:LP:AF:ID  0.00463765:0.00250259:1.19382:0.033047:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036666 ES:SE:LP:AF:ID  0.0038562:0.00227333:1.04576:0.036666:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036777 ES:SE:LP:AF:ID  0.00396817:0.00226493:1.09691:0.036777:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036477 ES:SE:LP:AF:ID  0.00414048:0.0022812:1.1549:0.036477:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016433 ES:SE:LP:AF:ID  -0.00376542:0.00351054:0.552842:0.016433:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037018 ES:SE:LP:AF:ID  0.00393101:0.00225595:1.09151:0.037018:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037113 ES:SE:LP:AF:ID  0.00401626:0.00224827:1.13077:0.037113:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101351 ES:SE:LP:AF:ID  0.000588047:0.00163695:0.142668:0.101351:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959132 ES:SE:LP:AF:ID  -0.00280271:0.00217063:0.69897:0.959132:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031522 ES:SE:LP:AF:ID  -0.00405998:0.00392464:0.522879:0.031522:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053262 ES:SE:LP:AF:ID  -0.000795762:0.0031321:0.09691:0.053262:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036623 ES:SE:LP:AF:ID  0.00423596:0.00226285:1.21467:0.036623:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036945 ES:SE:LP:AF:ID  0.00408145:0.00224212:1.16115:0.036945:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84325  ES:SE:LP:AF:ID  0.000545789:0.00116154:0.19382:0.84325:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055923 ES:SE:LP:AF:ID  -0.00144701:0.00188043:0.356547:0.055923:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122331 ES:SE:LP:AF:ID  -0.00123962:0.00127088:0.481486:0.122331:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025686 ES:SE:LP:AF:ID  -0.00346798:0.00313045:0.568636:0.025686:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121566 ES:SE:LP:AF:ID  -0.00115049:0.00127142:0.431798:0.121566:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132389 ES:SE:LP:AF:ID  0.000513216:0.00125323:0.167491:0.132389:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011033 ES:SE:LP:AF:ID  0.00507333:0.00458743:0.568636:0.011033:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005761 ES:SE:LP:AF:ID  0.00210453:0.00585014:0.142668:0.005761:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036864 ES:SE:LP:AF:ID  0.00414577:0.00221925:1.20761:0.036864:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838893 ES:SE:LP:AF:ID  0.000100132:0.00112466:0.0315171:0.838893:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838548 ES:SE:LP:AF:ID  0.000128393:0.00112351:0.0409586:0.838548:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869755 ES:SE:LP:AF:ID  0.00108991:0.00120557:0.431798:0.869755:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129864 ES:SE:LP:AF:ID  -0.00105331:0.00120809:0.420216:0.129864:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037387 ES:SE:LP:AF:ID  0.0040846:0.00218127:1.21467:0.037387:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037622 ES:SE:LP:AF:ID  0.00411278:0.00216788:1.23657:0.037622:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869128 ES:SE:LP:AF:ID  0.00117081:0.00120331:0.481486:0.869128:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869232 ES:SE:LP:AF:ID  0.00121222:0.00120378:0.508638:0.869232:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037586 ES:SE:LP:AF:ID  0.0040229:0.00217698:1.18709:0.037586:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869129 ES:SE:LP:AF:ID  0.00116627:0.00120328:0.481486:0.869129:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837997 ES:SE:LP:AF:ID  0.000185134:0.00112038:0.0604807:0.837997:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037599 ES:SE:LP:AF:ID  0.00407685:0.00218011:1.21467:0.037599:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838634 ES:SE:LP:AF:ID  0.000315163:0.00112355:0.107905:0.838634:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013792 ES:SE:LP:AF:ID  -0.0050261:0.00392366:0.69897:0.013792:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005575 ES:SE:LP:AF:ID  -0.00110045:0.00603968:0.0655015:0.005575:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839709 ES:SE:LP:AF:ID  0.000373193:0.00113855:0.130768:0.839709:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869381 ES:SE:LP:AF:ID  0.00107717:0.00120179:0.431798:0.869381:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868922 ES:SE:LP:AF:ID  0.00105232:0.00119872:0.420216:0.868922:rs3131962