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-7138/UKB-b-7138_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7138/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-7138/UKB-b-7138_data.vcf.gz ...
Read summary statistics for 9119096 SNPs.
Dropped 9270 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, 1287471 SNPs remain.
After merging with regression SNP LD, 1287471 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0469 (0.0044)
Lambda GC: 1.095
Mean Chi^2: 1.1097
Intercept: 1.0048 (0.0064)
Ratio: 0.0437 (0.0582)
Analysis finished at Thu Oct 17 14:42:52 2019
Total time elapsed: 2.0m:35.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.948,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 99455,
    "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": 1287471,
    "ldsc_nsnp_merge_regression_ld": 1287471,
    "ldsc_observed_scale_h2_beta": 0.0469,
    "ldsc_observed_scale_h2_se": 0.0044,
    "ldsc_intercept_beta": 1.0048,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.095,
    "ldsc_mean_chisq": 1.1097,
    "ldsc_ratio": 0.0438
}

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 9109869 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 9119096 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 8.639829e+00 5.756603e+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 7.879655e+07 5.632512e+07 828.0000000 3.246035e+07 6.937113e+07 1.145272e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.000000e-05 1.410770e-02 -0.1589310 -5.429200e-03 4.420000e-05 5.523900e-03 1.639240e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.110970e-02 8.362300e-03 0.0039175 4.689800e-03 7.264800e-03 1.524510e-02 9.242210e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.878945e-01 2.923305e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.878948e-01 2.923053e-01 0.0000000 2.311222e-01 4.840259e-01 7.411637e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.177010e-01 2.582629e-01 0.0030590 1.928800e-02 9.800900e-02 3.428850e-01 9.969410e-01 ▇▂▁▁▁
numeric AF_reference 99455 0.9890938 NA NA NA NA NA NA NA 2.182110e-01 2.501292e-01 0.0000000 1.637380e-02 1.158150e-01 3.416530e-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 -0.0063578 0.0072280 0.3800004 0.3790711 0.624893 0.7821490 NA
1 54676 rs2462492 C T 0.0129726 0.0071420 0.0690001 0.0693130 0.400556 NA NA
1 86028 rs114608975 T C -0.0288448 0.0114011 0.0109999 0.0114062 0.103686 0.0277556 NA
1 91536 rs6702460 G T 0.0065311 0.0070279 0.3500000 0.3527292 0.457693 0.4207270 NA
1 234313 rs8179466 C T 0.0005083 0.0137948 0.9699999 0.9706080 0.074871 NA NA
1 534192 rs6680723 C T 0.0022814 0.0080713 0.7800007 0.7774404 0.240594 NA NA
1 546697 rs12025928 A G 0.0009037 0.0100257 0.9299999 0.9281739 0.913473 NA NA
1 693731 rs12238997 A G 0.0017467 0.0067612 0.8000000 0.7961372 0.115610 0.1417730 NA
1 705882 rs72631875 G A 0.0026633 0.0098980 0.7899998 0.7878691 0.066978 0.0315495 NA
1 706368 rs55727773 A G 0.0005212 0.0049992 0.9199999 0.9169692 0.515491 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0029984 0.0060258 0.6200004 0.6187687 0.138281 0.2052720 NA
22 51219387 rs9616832 T C 0.0021338 0.0078088 0.7800007 0.7846577 0.073889 0.0654952 NA
22 51219704 rs147475742 G A 0.0015996 0.0104650 0.8800001 0.8785170 0.042017 0.0473243 NA
22 51221190 rs369304721 G A -0.0064691 0.0104735 0.5400003 0.5367971 0.049651 NA NA
22 51221731 rs115055839 T C 0.0026069 0.0078144 0.7400005 0.7386834 0.073347 0.0625000 NA
22 51222100 rs114553188 G T 0.0041600 0.0091963 0.6499995 0.6510147 0.054536 0.0880591 NA
22 51223637 rs375798137 G A 0.0033056 0.0092406 0.7199992 0.7205465 0.054162 0.0788738 NA
22 51229805 rs9616985 T C 0.0026704 0.0078420 0.7300002 0.7334612 0.073210 0.0730831 NA
22 51232488 rs376461333 A G 0.0011824 0.0185528 0.9500000 0.9491835 0.020036 NA NA
22 51237063 rs3896457 T C 0.0003995 0.0047966 0.9299999 0.9336194 0.299074 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624893 ES:SE:LP:AF:ID  -0.00635778:0.00722796:0.420216:0.624893:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400556 ES:SE:LP:AF:ID  0.0129726:0.00714203:1.16115:0.400556:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103686 ES:SE:LP:AF:ID  -0.0288448:0.0114011:1.95861:0.103686:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457693 ES:SE:LP:AF:ID  0.00653106:0.00702787:0.455932:0.457693:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074871 ES:SE:LP:AF:ID  0.000508279:0.0137948:0.0132283:0.074871:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240594 ES:SE:LP:AF:ID  0.0022814:0.00807129:0.107905:0.240594:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913473 ES:SE:LP:AF:ID  0.000903743:0.0100257:0.0315171:0.913473:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11561  ES:SE:LP:AF:ID  0.00174674:0.00676115:0.09691:0.11561:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.066978 ES:SE:LP:AF:ID  0.00266333:0.00989796:0.102373:0.066978:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515491 ES:SE:LP:AF:ID  0.000521179:0.00499921:0.0362122:0.515491:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033012 ES:SE:LP:AF:ID  -0.00851073:0.0125781:0.30103:0.033012:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036639 ES:SE:LP:AF:ID  -0.00740999:0.0114266:0.283997:0.036639:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036771 ES:SE:LP:AF:ID  -0.0071714:0.0113795:0.275724:0.036771:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036449 ES:SE:LP:AF:ID  -0.00808784:0.0114649:0.318759:0.036449:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016453 ES:SE:LP:AF:ID  -0.0354699:0.0175505:1.36653:0.016453:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037002 ES:SE:LP:AF:ID  -0.00884759:0.0113338:0.356547:0.037002:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037103 ES:SE:LP:AF:ID  -0.00837932:0.0112959:0.337242:0.037103:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101325 ES:SE:LP:AF:ID  -0.00886054:0.00822691:0.552842:0.101325:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959009 ES:SE:LP:AF:ID  0.011816:0.0108956:0.552842:0.959009:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031592 ES:SE:LP:AF:ID  0.00180556:0.0196399:0.0315171:0.031592:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053152 ES:SE:LP:AF:ID  0.00704372:0.0158:0.180456:0.053152:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03663  ES:SE:LP:AF:ID  -0.00830475:0.0113698:0.327902:0.03663:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036875 ES:SE:LP:AF:ID  -0.00658421:0.011278:0.251812:0.036875:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843708 ES:SE:LP:AF:ID  0.00255767:0.00584569:0.180456:0.843708:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05529  ES:SE:LP:AF:ID  0.0039548:0.00952252:0.167491:0.05529:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121886 ES:SE:LP:AF:ID  0.00134063:0.00639798:0.0809219:0.121886:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025771 ES:SE:LP:AF:ID  -0.00586229:0.0157121:0.148742:0.025771:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121141 ES:SE:LP:AF:ID  0.001563:0.0064002:0.091515:0.121141:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.131861 ES:SE:LP:AF:ID  0.00149756:0.00631948:0.091515:0.131861:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.010984 ES:SE:LP:AF:ID  0.0199361:0.0230992:0.408935:0.010984:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005872 ES:SE:LP:AF:ID  0.0082238:0.0292331:0.107905:0.005872:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036857 ES:SE:LP:AF:ID  -0.0048607:0.0111508:0.180456:0.036857:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839485 ES:SE:LP:AF:ID  0.00130257:0.00566676:0.0861861:0.839485:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.839139 ES:SE:LP:AF:ID  0.00163426:0.0056606:0.113509:0.839139:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.870131 ES:SE:LP:AF:ID  -0.000359486:0.00606915:0.0222764:0.870131:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129518 ES:SE:LP:AF:ID  0.000208505:0.00608111:0.0132283:0.129518:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037336 ES:SE:LP:AF:ID  -0.0052896:0.0109668:0.200659:0.037336:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037595 ES:SE:LP:AF:ID  -0.00583345:0.0108938:0.229148:0.037595:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869467 ES:SE:LP:AF:ID  -6.66881e-06:0.00605688:-0:0.869467:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869571 ES:SE:LP:AF:ID  0.000138064:0.00605909:0.00877392:0.869571:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.00541318:0.010943:0.207608:0.037545:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869475 ES:SE:LP:AF:ID  -8.97517e-05:0.00605713:0.00436481:0.869475:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005022 ES:SE:LP:AF:ID  0.0160276:0.0313787:0.21467:0.005022:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00499  ES:SE:LP:AF:ID  0.0157199:0.0314435:0.207608:0.00499:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838572 ES:SE:LP:AF:ID  0.00163254:0.00564484:0.113509:0.838572:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037552 ES:SE:LP:AF:ID  -0.00543289:0.0109599:0.207608:0.037552:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.839175 ES:SE:LP:AF:ID  0.00151836:0.00566024:0.102373:0.839175:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013836 ES:SE:LP:AF:ID  -0.00273571:0.0196497:0.05061:0.013836:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005523 ES:SE:LP:AF:ID  0.00865243:0.0305028:0.107905:0.005523:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.840241 ES:SE:LP:AF:ID  0.00139438:0.00573543:0.091515:0.840241:rs3131965