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-19520/UKB-b-19520_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19520/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19520/UKB-b-19520_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2524 (0.0081)
Lambda GC: 2.4803
Mean Chi^2: 3.6388
Intercept: 1.2762 (0.0216)
Ratio: 0.1046 (0.0082)
Analysis finished at Thu Oct 17 14:43:07 2019
Total time elapsed: 1.0m:44.39s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.92,
    "mean_EFFECT": -1.4596e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 517,
    "n_p_sig": 92402,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.2524,
    "ldsc_observed_scale_h2_se": 0.0081,
    "ldsc_intercept_beta": 1.2762,
    "ldsc_intercept_se": 0.0216,
    "ldsc_lambda_gc": 2.4803,
    "ldsc_mean_chisq": 3.6388,
    "ldsc_ratio": 0.1047
}

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 TRUE
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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.500000e-06 6.867300e-03 -0.2548450 -2.613600e-03 4.000000e-07 2.607300e-03 1.611520e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.256900e-03 4.029000e-03 0.0011893 1.458300e-03 2.445400e-03 5.642100e-03 6.247040e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 3.946296e-01 3.117869e-01 0.0000000 9.900110e-02 3.500000e-01 6.600001e-01 1.000000e+00 ▇▅▃▃▃
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 3.946321e-01 3.117656e-01 0.0000000 9.886490e-02 3.488832e-01 6.614658e-01 9.999998e-01 ▇▅▃▃▃
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035078e-01 2.568614e-01 0.0009850 1.316900e-02 7.791400e-02 3.164550e-01 9.990060e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 0.0024501 0.0021849 0.2599998 0.2621304 0.623739 0.7821490 NA
1 54676 rs2462492 C T 0.0020208 0.0021650 0.3500000 0.3506045 0.400346 NA NA
1 86028 rs114608975 T C -0.0015967 0.0034609 0.6400000 0.6445386 0.103558 0.0277556 NA
1 91536 rs6702460 G T 0.0045186 0.0021312 0.0340001 0.0339929 0.456846 0.4207270 NA
1 234313 rs8179466 C T -0.0067626 0.0042041 0.1100001 0.1077144 0.074494 NA NA
1 534192 rs6680723 C T -0.0045379 0.0024348 0.0619998 0.0623485 0.240935 NA NA
1 546697 rs12025928 A G 0.0059809 0.0030373 0.0490004 0.0489370 0.913461 NA NA
1 693731 rs12238997 A G -0.0040367 0.0020415 0.0479999 0.0480049 0.116211 0.1417730 NA
1 705882 rs72631875 G A -0.0063017 0.0029891 0.0350002 0.0350141 0.067326 0.0315495 NA
1 706368 rs55727773 A G -0.0009034 0.0015116 0.5500004 0.5500654 0.515779 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0045907 0.0031954 0.1499999 0.1508209 0.041968 0.0473243 NA
22 51219766 rs182321900 C T -0.0093015 0.0148716 0.5300002 0.5316723 0.001942 NA NA
22 51220146 rs868950473 C T -0.0112465 0.0147300 0.4500005 0.4451594 0.001991 NA NA
22 51221190 rs369304721 G A -0.0002783 0.0031897 0.9299999 0.9304809 0.049762 NA NA
22 51221731 rs115055839 T C 0.0008512 0.0023860 0.7199992 0.7212920 0.073280 0.0625000 NA
22 51222100 rs114553188 G T 0.0008678 0.0028092 0.7600007 0.7573709 0.054489 0.0880591 NA
22 51223637 rs375798137 G A 0.0009152 0.0028227 0.7499995 0.7457719 0.054119 0.0788738 NA
22 51229805 rs9616985 T C 0.0009264 0.0023946 0.6999999 0.6988470 0.073113 0.0730831 NA
22 51232488 rs376461333 A G 0.0023905 0.0056404 0.6700003 0.6717017 0.020056 NA NA
22 51237063 rs3896457 T C -0.0001991 0.0014653 0.8900000 0.8919347 0.297905 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623739 ES:SE:LP:AF:ID  0.00245007:0.00218489:0.585027:0.623739:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400346 ES:SE:LP:AF:ID  0.00202083:0.00216498:0.455932:0.400346:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103558 ES:SE:LP:AF:ID  -0.00159672:0.00346088:0.19382:0.103558:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  0.00451856:0.00213124:1.46852:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074494 ES:SE:LP:AF:ID  -0.00676256:0.00420413:0.958607:0.074494:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240935 ES:SE:LP:AF:ID  -0.00453791:0.00243475:1.20761:0.240935:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913461 ES:SE:LP:AF:ID  0.00598087:0.0030373:1.3098:0.913461:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116211 ES:SE:LP:AF:ID  -0.00403667:0.00204148:1.31876:0.116211:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067326 ES:SE:LP:AF:ID  -0.00630169:0.00298914:1.45593:0.067326:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515779 ES:SE:LP:AF:ID  -0.00090345:0.00151164:0.259637:0.515779:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032987 ES:SE:LP:AF:ID  -0.000204018:0.00381126:0.0177288:0.032987:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036598 ES:SE:LP:AF:ID  -9.92911e-05:0.00346223:0.00877392:0.036598:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036717 ES:SE:LP:AF:ID  0.000202946:0.00344888:0.0222764:0.036717:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036414 ES:SE:LP:AF:ID  -0.000481459:0.00347394:0.05061:0.036414:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016392 ES:SE:LP:AF:ID  -0.000186055:0.00535015:0.0132283:0.016392:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036954 ES:SE:LP:AF:ID  -0.000500497:0.00343543:0.0555173:0.036954:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037052 ES:SE:LP:AF:ID  -0.000344066:0.00342357:0.0362122:0.037052:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101245 ES:SE:LP:AF:ID  0.00168409:0.00249347:0.30103:0.101245:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959097 ES:SE:LP:AF:ID  0.00107223:0.00330112:0.124939:0.959097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031462 ES:SE:LP:AF:ID  -0.00176129:0.00598865:0.113509:0.031462:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053252 ES:SE:LP:AF:ID  0.00354717:0.00476454:0.337242:0.053252:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036573 ES:SE:LP:AF:ID  -0.000738904:0.00344556:0.0809219:0.036573:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  -0.00131757:0.00341418:0.154902:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843326 ES:SE:LP:AF:ID  0.0033673:0.00176879:1.24413:0.843326:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055856 ES:SE:LP:AF:ID  -0.00667966:0.00286453:1.69897:0.055856:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122187 ES:SE:LP:AF:ID  -0.00382121:0.00193652:1.31876:0.122187:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025732 ES:SE:LP:AF:ID  0.0033151:0.00475825:0.309804:0.025732:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121427 ES:SE:LP:AF:ID  -0.0037013:0.00193735:1.25181:0.121427:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132212 ES:SE:LP:AF:ID  -0.00380005:0.00190918:1.3279:0.132212:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011123 ES:SE:LP:AF:ID  0.00846709:0.00694525:0.657577:0.011123:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005693 ES:SE:LP:AF:ID  0.00503525:0.00896005:0.244125:0.005693:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002287 ES:SE:LP:AF:ID  0.000835968:0.0149995:0.0177288:0.002287:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001037 ES:SE:LP:AF:ID  -0.00815994:0.0245359:0.130768:0.001037:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036805 ES:SE:LP:AF:ID  -0.000868753:0.00337969:0.09691:0.036805:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839056 ES:SE:LP:AF:ID  0.00341556:0.00171284:1.33724:0.839056:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838682 ES:SE:LP:AF:ID  0.00345166:0.00171096:1.35655:0.838682:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869876 ES:SE:LP:AF:ID  0.0038163:0.00183616:1.42022:0.869876:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129763 ES:SE:LP:AF:ID  -0.00404231:0.00184:1.55284:0.129763:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  -0.00233092:0.0033224:0.318759:0.037317:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037562 ES:SE:LP:AF:ID  -0.00220108:0.00330137:0.30103:0.037562:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  0.00384659:0.00183255:1.4437:0.869221:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869318 ES:SE:LP:AF:ID  0.00383326:0.00183328:1.4318:0.869318:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037515 ES:SE:LP:AF:ID  -0.00228865:0.00331585:0.309804:0.037515:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869223 ES:SE:LP:AF:ID  0.00384954:0.00183251:1.4437:0.869223:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005132 ES:SE:LP:AF:ID  -0.006468:0.00939338:0.309804:0.005132:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005099 ES:SE:LP:AF:ID  -0.00672667:0.0094177:0.318759:0.005099:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838139 ES:SE:LP:AF:ID  0.00344526:0.00170625:1.36653:0.838139:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  -0.00227162:0.00332054:0.309804:0.037527:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838771 ES:SE:LP:AF:ID  0.00355102:0.00171106:1.42022:0.838771:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013775 ES:SE:LP:AF:ID  0.0140141:0.00597012:1.72125:0.013775:rs181660517