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-4077/UKB-b-4077_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4077/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4077/UKB-b-4077_data.vcf.gz ...
Read summary statistics for 9032127 SNPs.
Dropped 8863 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, 1287224 SNPs remain.
After merging with regression SNP LD, 1287224 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0223 (0.0014)
Lambda GC: 1.2262
Mean Chi^2: 1.2489
Intercept: 1.0492 (0.0065)
Ratio: 0.1977 (0.0262)
Analysis finished at Thu Oct 17 14:45:43 2019
Total time elapsed: 1.0m:42.0s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9477,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 216,
    "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": 94809,
    "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": 1287224,
    "ldsc_nsnp_merge_regression_ld": 1287224,
    "ldsc_observed_scale_h2_beta": 0.0223,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0492,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.2262,
    "ldsc_mean_chisq": 1.2489,
    "ldsc_ratio": 0.1977
}

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 9023305 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 9032127 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 8.642477e+00 5.757751e+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 7.879189e+07 5.633776e+07 828.0000000 3.243789e+07 6.935656e+07 1.145362e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.860000e-05 2.961100e-03 -0.0338813 -1.207000e-03 -5.500000e-06 1.182200e-03 3.491600e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.290100e-03 1.688800e-03 0.0008266 9.860000e-04 1.514300e-03 3.141100e-03 1.917300e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.750645e-01 2.954008e-01 0.0000000 2.099999e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.750649e-01 2.953741e-01 0.0000000 2.130687e-01 4.663273e-01 7.307207e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.196186e-01 2.584872e-01 0.0034380 2.020900e-02 1.006840e-01 3.463530e-01 9.965620e-01 ▇▂▁▁▁
numeric AF_reference 94809 0.9895031 NA NA NA NA NA NA NA 2.199481e-01 2.503761e-01 0.0000000 1.737220e-02 1.182110e-01 3.448480e-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 0.0006993 0.0015210 0.6499995 0.6456895 0.623739 0.7821490 NA
1 54676 rs2462492 C T 0.0008773 0.0015066 0.5600000 0.5603748 0.400447 NA NA
1 86028 rs114608975 T C -0.0034510 0.0024091 0.1499999 0.1520035 0.103563 0.0277556 NA
1 91536 rs6702460 G T 0.0022580 0.0014837 0.1299999 0.1280253 0.456854 0.4207270 NA
1 234313 rs8179466 C T -0.0043234 0.0029249 0.1400000 0.1393814 0.074518 NA NA
1 534192 rs6680723 C T 0.0003434 0.0016946 0.8400000 0.8393890 0.240965 NA NA
1 546697 rs12025928 A G -0.0008678 0.0021141 0.6800001 0.6814311 0.913474 NA NA
1 693731 rs12238997 A G 0.0009077 0.0014200 0.5199996 0.5226975 0.116340 0.1417730 NA
1 705882 rs72631875 G A 0.0007674 0.0020813 0.7099994 0.7123255 0.067265 0.0315495 NA
1 706368 rs55727773 A G 0.0015460 0.0010520 0.1400000 0.1416663 0.515686 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0003634 0.0012693 0.7700005 0.7746545 0.137953 0.2052720 NA
22 51219387 rs9616832 T C -0.0004583 0.0016477 0.7800007 0.7808952 0.073751 0.0654952 NA
22 51219704 rs147475742 G A -0.0006721 0.0022082 0.7600007 0.7608587 0.041948 0.0473243 NA
22 51221190 rs369304721 G A -0.0015832 0.0022046 0.4700002 0.4726806 0.049729 NA NA
22 51221731 rs115055839 T C -0.0004745 0.0016487 0.7700005 0.7735098 0.073243 0.0625000 NA
22 51222100 rs114553188 G T 0.0010601 0.0019410 0.5800000 0.5849766 0.054458 0.0880591 NA
22 51223637 rs375798137 G A 0.0010601 0.0019504 0.5900000 0.5867710 0.054088 0.0788738 NA
22 51229805 rs9616985 T C -0.0006079 0.0016547 0.7099994 0.7133243 0.073077 0.0730831 NA
22 51232488 rs376461333 A G 0.0006516 0.0038980 0.8700001 0.8672435 0.020040 NA NA
22 51237063 rs3896457 T C 0.0003988 0.0010121 0.6899999 0.6935303 0.297987 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623739 ES:SE:LP:AF:ID  0.000699279:0.00152097:0.187087:0.623739:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400447 ES:SE:LP:AF:ID  0.000877253:0.00150657:0.251812:0.400447:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103563 ES:SE:LP:AF:ID  -0.00345097:0.00240907:0.823909:0.103563:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456854 ES:SE:LP:AF:ID  0.00225805:0.00148367:0.886057:0.456854:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074518 ES:SE:LP:AF:ID  -0.00432335:0.00292494:0.853872:0.074518:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  0.000343445:0.00169456:0.0757207:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913474 ES:SE:LP:AF:ID  -0.000867845:0.00211406:0.167491:0.913474:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11634  ES:SE:LP:AF:ID  0.000907673:0.00142003:0.283997:0.11634:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067265 ES:SE:LP:AF:ID  0.000767429:0.00208125:0.148742:0.067265:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515686 ES:SE:LP:AF:ID  0.00154599:0.00105197:0.853872:0.515686:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032994 ES:SE:LP:AF:ID  0.00252861:0.00265251:0.468521:0.032994:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036606 ES:SE:LP:AF:ID  0.00220394:0.00240945:0.443698:0.036606:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  0.00212176:0.00240033:0.420216:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036422 ES:SE:LP:AF:ID  0.00215085:0.00241762:0.431798:0.036422:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016422 ES:SE:LP:AF:ID  -0.0060063:0.00371993:0.958607:0.016422:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036962 ES:SE:LP:AF:ID  0.00198893:0.00239079:0.387216:0.036962:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037058 ES:SE:LP:AF:ID  0.00204785:0.00238265:0.408935:0.037058:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10117  ES:SE:LP:AF:ID  0.00117154:0.00173586:0.30103:0.10117:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959116 ES:SE:LP:AF:ID  -0.00206655:0.00229817:0.431798:0.959116:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031456 ES:SE:LP:AF:ID  -0.00225901:0.00417042:0.229148:0.031456:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053258 ES:SE:LP:AF:ID  -0.00382532:0.00331795:0.60206:0.053258:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036575 ES:SE:LP:AF:ID  0.00214339:0.00239811:0.431798:0.036575:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  0.00230365:0.00237628:0.481486:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843218 ES:SE:LP:AF:ID  -0.00106498:0.00123081:0.408935:0.843218:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055922 ES:SE:LP:AF:ID  0.00136753:0.00199268:0.309804:0.055922:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122325 ES:SE:LP:AF:ID  0.000490618:0.00134708:0.142668:0.122325:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  -0.00139035:0.00331355:0.173925:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121567 ES:SE:LP:AF:ID  0.000590839:0.00134765:0.180456:0.121567:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132324 ES:SE:LP:AF:ID  0.00190245:0.00132836:0.823909:0.132324:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  0.000234724:0.00483008:0.0177288:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005703 ES:SE:LP:AF:ID  -0.00471391:0.00623252:0.346787:0.005703:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  0.00134049:0.00235219:0.244125:0.036808:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838956 ES:SE:LP:AF:ID  -0.000790236:0.00119195:0.29243:0.838956:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838586 ES:SE:LP:AF:ID  -0.000845407:0.00119067:0.318759:0.838586:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86977  ES:SE:LP:AF:ID  -0.000327336:0.00127758:0.09691:0.86977:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129879 ES:SE:LP:AF:ID  0.000283192:0.0012802:0.0861861:0.129879:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037318 ES:SE:LP:AF:ID  0.00170864:0.00231237:0.337242:0.037318:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  0.00178664:0.00229779:0.356547:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  -0.000366331:0.0012751:0.113509:0.869116:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -0.000298996:0.00127561:0.091515:0.869214:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037519 ES:SE:LP:AF:ID  0.00161394:0.00230772:0.318759:0.037519:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  -0.000373384:0.00127508:0.113509:0.869119:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005117 ES:SE:LP:AF:ID  0.00691903:0.00655009:0.537602:0.005117:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005083 ES:SE:LP:AF:ID  0.00651493:0.0065673:0.49485:0.005083:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83804  ES:SE:LP:AF:ID  -0.000797606:0.00118738:0.30103:0.83804:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.00152821:0.00231101:0.29243:0.03753:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838671 ES:SE:LP:AF:ID  -0.000684128:0.00119071:0.244125:0.838671:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013766 ES:SE:LP:AF:ID  0.000188778:0.00415745:0.0177288:0.013766:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005545 ES:SE:LP:AF:ID  -0.0181083:0.00641388:2.31876:0.005545:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839782 ES:SE:LP:AF:ID  -0.000775583:0.0012068:0.283997:0.839782:rs3131965