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-8476/UKB-b-8476_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8476/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8476/UKB-b-8476_data.vcf.gz ...
Read summary statistics for 8862761 SNPs.
Dropped 8140 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, 1286623 SNPs remain.
After merging with regression SNP LD, 1286623 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0373 (0.002)
Lambda GC: 1.3182
Mean Chi^2: 1.3742
Intercept: 1.0404 (0.0079)
Ratio: 0.1079 (0.0212)
Analysis finished at Thu Oct 17 14:44:14 2019
Total time elapsed: 2.0m:19.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9471,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 16,
    "n_p_sig": 754,
    "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": 88615,
    "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": 1286623,
    "ldsc_nsnp_merge_regression_ld": 1286623,
    "ldsc_observed_scale_h2_beta": 0.0373,
    "ldsc_observed_scale_h2_se": 0.002,
    "ldsc_intercept_beta": 1.0404,
    "ldsc_intercept_se": 0.0079,
    "ldsc_lambda_gc": 1.3182,
    "ldsc_mean_chisq": 1.3742,
    "ldsc_ratio": 0.108
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 8854660 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 8862761 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 8.647177e+00 5.759848e+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 7.878189e+07 5.634467e+07 828.0000000 3.241542e+07 6.933902e+07 1.145580e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.670000e-05 2.664000e-03 -0.0271811 -1.117100e-03 1.530000e-05 1.173600e-03 3.214280e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.060500e-03 1.467300e-03 0.0007750 9.196000e-04 1.388200e-03 2.813900e-03 1.795110e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.646567e-01 2.980581e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.646597e-01 2.980335e-01 0.0000000 1.977211e-01 4.519042e-01 7.226897e-01 9.999996e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.234336e-01 2.588955e-01 0.0042460 2.215200e-02 1.060460e-01 3.529150e-01 9.957540e-01 ▇▂▁▁▁
numeric AF_reference 88615 0.9900014 NA NA NA NA NA NA NA 2.234743e-01 2.508341e-01 0.0000000 1.956870e-02 1.232030e-01 3.508390e-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 0.0005435 0.0014255 0.6999999 0.7030087 0.623770 0.7821490 NA
1 54676 rs2462492 C T -0.0002973 0.0014122 0.8300000 0.8332608 0.400428 NA NA
1 86028 rs114608975 T C 0.0012729 0.0022578 0.5700002 0.5728991 0.103558 0.0277556 NA
1 91536 rs6702460 G T -0.0008518 0.0013904 0.5400003 0.5401428 0.456864 0.4207270 NA
1 234313 rs8179466 C T 0.0013656 0.0027426 0.6200004 0.6185418 0.074476 NA NA
1 534192 rs6680723 C T 0.0015762 0.0015886 0.3200000 0.3211211 0.240955 NA NA
1 546697 rs12025928 A G 0.0003779 0.0019816 0.8499999 0.8487575 0.913478 NA NA
1 693731 rs12238997 A G 0.0016153 0.0013312 0.2200002 0.2249729 0.116349 0.1417730 NA
1 705882 rs72631875 G A 0.0005109 0.0019508 0.7899998 0.7933998 0.067288 0.0315495 NA
1 706368 rs55727773 A G -0.0021595 0.0009862 0.0290001 0.0285387 0.515677 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0001845 0.0011901 0.8800001 0.8768194 0.137908 0.2052720 NA
22 51219387 rs9616832 T C -0.0025280 0.0015449 0.1000000 0.1017794 0.073735 0.0654952 NA
22 51219704 rs147475742 G A -0.0011725 0.0020706 0.5700002 0.5712070 0.041935 0.0473243 NA
22 51221190 rs369304721 G A -0.0023774 0.0020668 0.2500000 0.2500251 0.049734 NA NA
22 51221731 rs115055839 T C -0.0024138 0.0015459 0.1199999 0.1184308 0.073223 0.0625000 NA
22 51222100 rs114553188 G T 0.0026576 0.0018208 0.1400000 0.1444023 0.054417 0.0880591 NA
22 51223637 rs375798137 G A 0.0027026 0.0018296 0.1400000 0.1396469 0.054045 0.0788738 NA
22 51229805 rs9616985 T C -0.0023115 0.0015515 0.1400000 0.1362683 0.073059 0.0730831 NA
22 51232488 rs376461333 A G 0.0030512 0.0036574 0.4000000 0.4041444 0.020018 NA NA
22 51237063 rs3896457 T C -0.0010280 0.0009489 0.2800000 0.2786221 0.298006 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62377  ES:SE:LP:AF:ID  0.000543474:0.00142546:0.154902:0.62377:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400428 ES:SE:LP:AF:ID  -0.000297294:0.00141218:0.0809219:0.400428:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103558 ES:SE:LP:AF:ID  0.00127289:0.00225775:0.244125:0.103558:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456864 ES:SE:LP:AF:ID  -0.000851761:0.00139041:0.267606:0.456864:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074476 ES:SE:LP:AF:ID  0.00136559:0.0027426:0.207608:0.074476:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240955 ES:SE:LP:AF:ID  0.00157617:0.00158863:0.49485:0.240955:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913478 ES:SE:LP:AF:ID  0.000377901:0.00198161:0.0705811:0.913478:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116349 ES:SE:LP:AF:ID  0.00161528:0.00133119:0.657577:0.116349:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067288 ES:SE:LP:AF:ID  0.000510906:0.00195078:0.102373:0.067288:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515677 ES:SE:LP:AF:ID  -0.0021595:0.000986163:1.5376:0.515677:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032979 ES:SE:LP:AF:ID  0.000472956:0.00248693:0.0705811:0.032979:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036588 ES:SE:LP:AF:ID  0.00141634:0.00225914:0.275724:0.036588:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036702 ES:SE:LP:AF:ID  0.00154323:0.00225067:0.309804:0.036702:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036402 ES:SE:LP:AF:ID  0.00132214:0.00226686:0.251812:0.036402:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016415 ES:SE:LP:AF:ID  0.00589467:0.00348774:1.04096:0.016415:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036942 ES:SE:LP:AF:ID  0.00158182:0.00224175:0.318759:0.036942:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037042 ES:SE:LP:AF:ID  0.00136895:0.00223394:0.267606:0.037042:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101196 ES:SE:LP:AF:ID  0.00168185:0.00162696:0.522879:0.101196:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959141 ES:SE:LP:AF:ID  -0.00108327:0.00215485:0.207608:0.959141:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  0.00413617:0.00390933:0.537602:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  -0.000344157:0.00310935:0.0409586:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036558 ES:SE:LP:AF:ID  0.00150085:0.00224845:0.30103:0.036558:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036874 ES:SE:LP:AF:ID  0.00146268:0.00222795:0.29243:0.036874:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843223 ES:SE:LP:AF:ID  -0.00140719:0.00115378:0.657577:0.843223:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055933 ES:SE:LP:AF:ID  0.000120861:0.00186774:0.0222764:0.055933:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122339 ES:SE:LP:AF:ID  0.00148653:0.00126268:0.619789:0.122339:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  9.86019e-05:0.00310453:0.0132283:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121582 ES:SE:LP:AF:ID  0.00159265:0.00126322:0.677781:0.121582:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132337 ES:SE:LP:AF:ID  0.000499209:0.00124508:0.161151:0.132337:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011132 ES:SE:LP:AF:ID  -0.00307405:0.00452736:0.30103:0.011132:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005714 ES:SE:LP:AF:ID  0.00668004:0.00583632:0.60206:0.005714:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036789 ES:SE:LP:AF:ID  0.00171828:0.00220549:0.356547:0.036789:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838953 ES:SE:LP:AF:ID  -0.00094639:0.00111737:0.39794:0.838953:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838579 ES:SE:LP:AF:ID  -0.000907876:0.00111615:0.376751:0.838579:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86976  ES:SE:LP:AF:ID  -0.000877423:0.0011976:0.337242:0.86976:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129893 ES:SE:LP:AF:ID  0.00107124:0.00120002:0.431798:0.129893:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037294 ES:SE:LP:AF:ID  0.00163658:0.00216828:0.346787:0.037294:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  0.00164824:0.00215452:0.356547:0.03754:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000861322:0.00119524:0.327902:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869198 ES:SE:LP:AF:ID  -0.000869461:0.00119571:0.327902:0.869198:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037499 ES:SE:LP:AF:ID  0.00162749:0.00216385:0.346787:0.037499:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.000874173:0.00119522:0.337242:0.869104:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005126 ES:SE:LP:AF:ID  -0.00938777:0.00613423:0.886057:0.005126:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005093 ES:SE:LP:AF:ID  -0.00939454:0.00615019:0.886057:0.005093:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83804  ES:SE:LP:AF:ID  -0.000916231:0.00111312:0.387216:0.83804:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037512 ES:SE:LP:AF:ID  0.00157189:0.0021669:0.327902:0.037512:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83867  ES:SE:LP:AF:ID  -0.000896735:0.00111625:0.376751:0.83867:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013791 ES:SE:LP:AF:ID  0.00629952:0.00389276:0.958607:0.013791:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005551 ES:SE:LP:AF:ID  -0.00796392:0.00600919:0.721246:0.005551:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.83979  ES:SE:LP:AF:ID  -0.000877112:0.00113133:0.356547:0.83979:rs3131965