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-14280/UKB-b-14280_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14280/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14280/UKB-b-14280_data.vcf.gz ...
Read summary statistics for 9339222 SNPs.
Dropped 10516 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, 1288021 SNPs remain.
After merging with regression SNP LD, 1288021 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0043 (0.0013)
Lambda GC: 1.1045
Mean Chi^2: 1.1054
Intercept: 1.0667 (0.0069)
Ratio: 0.6331 (0.0652)
Analysis finished at Thu Oct 17 14:45:06 2019
Total time elapsed: 1.0m:42.85s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9487,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 115726,
    "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": 1288021,
    "ldsc_nsnp_merge_regression_ld": 1288021,
    "ldsc_observed_scale_h2_beta": 0.0043,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0667,
    "ldsc_intercept_se": 0.0069,
    "ldsc_lambda_gc": 1.1045,
    "ldsc_mean_chisq": 1.1054,
    "ldsc_ratio": 0.6328
}

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 9328758 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 9339222 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 8.633509e+00 5.753609e+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 7.881543e+07 5.630704e+07 828.0000000 3.250767e+07 6.939755e+07 1.145445e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.290000e-05 3.792400e-03 -0.0475263 -1.328800e-03 1.540000e-05 1.394700e-03 5.684040e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.869000e-03 2.288100e-03 0.0009527 1.147400e-03 1.818500e-03 3.929400e-03 3.303210e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.871752e-01 2.921186e-01 0.0000002 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 4.871765e-01 2.920945e-01 0.0000002 2.311539e-01 4.826424e-01 7.403480e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.130621e-01 2.577177e-01 0.0022420 1.717500e-02 9.148400e-02 3.344110e-01 9.977580e-01 ▇▂▁▁▁
numeric AF_reference 115726 0.9876086 NA NA NA NA NA NA NA 2.141611e-01 2.495052e-01 0.0000000 1.457670e-02 1.100240e-01 3.344650e-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 -0.0013010 0.0017532 0.4600002 0.4580484 0.623772 0.7821490 NA
1 54676 rs2462492 C T 0.0012007 0.0017368 0.4899999 0.4893617 0.400415 NA NA
1 86028 rs114608975 T C -0.0005369 0.0027768 0.8499999 0.8466981 0.103540 0.0277556 NA
1 91536 rs6702460 G T 0.0014540 0.0017102 0.4000000 0.3952173 0.456897 0.4207270 NA
1 234313 rs8179466 C T 0.0037212 0.0033720 0.2700001 0.2697751 0.074504 NA NA
1 534192 rs6680723 C T -0.0015460 0.0019538 0.4299995 0.4287804 0.240946 NA NA
1 546697 rs12025928 A G 0.0008990 0.0024366 0.7099994 0.7121480 0.913460 NA NA
1 693731 rs12238997 A G 0.0003097 0.0016373 0.8499999 0.8499996 0.116282 0.1417730 NA
1 705882 rs72631875 G A -0.0019958 0.0023990 0.4100001 0.4054442 0.067283 0.0315495 NA
1 706368 rs55727773 A G 0.0013326 0.0012127 0.2700001 0.2718365 0.515651 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0024435 0.0014628 0.0949992 0.0948404 0.137942 0.2052720 NA
22 51219387 rs9616832 T C 0.0014544 0.0018989 0.4400003 0.4437083 0.073739 0.0654952 NA
22 51219704 rs147475742 G A 0.0023308 0.0025444 0.3599996 0.3596246 0.041962 0.0473243 NA
22 51221190 rs369304721 G A 0.0004732 0.0025404 0.8499999 0.8522456 0.049724 NA NA
22 51221731 rs115055839 T C 0.0011805 0.0019001 0.5300002 0.5344069 0.073230 0.0625000 NA
22 51222100 rs114553188 G T 0.0038013 0.0022369 0.0890000 0.0892503 0.054471 0.0880591 NA
22 51223637 rs375798137 G A 0.0039385 0.0022477 0.0800000 0.0797316 0.054100 0.0788738 NA
22 51229805 rs9616985 T C 0.0013943 0.0019070 0.4600002 0.4646672 0.073064 0.0730831 NA
22 51232488 rs376461333 A G 0.0086198 0.0044908 0.0549997 0.0549282 0.020051 NA NA
22 51237063 rs3896457 T C -0.0029448 0.0011664 0.0120000 0.0115806 0.298011 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  -0.00130095:0.00175315:0.337242:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400415 ES:SE:LP:AF:ID  0.00120072:0.00173684:0.309804:0.400415:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10354  ES:SE:LP:AF:ID  -0.000536855:0.00277684:0.0705811:0.10354:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456897 ES:SE:LP:AF:ID  0.00145401:0.00171021:0.39794:0.456897:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074504 ES:SE:LP:AF:ID  0.00372123:0.00337196:0.568636:0.074504:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240946 ES:SE:LP:AF:ID  -0.00154598:0.00195377:0.366532:0.240946:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91346  ES:SE:LP:AF:ID  0.000899028:0.00243657:0.148742:0.91346:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116282 ES:SE:LP:AF:ID  0.000309652:0.00163734:0.0705811:0.116282:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067283 ES:SE:LP:AF:ID  -0.00199581:0.00239899:0.387216:0.067283:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515651 ES:SE:LP:AF:ID  0.0013326:0.00121273:0.568636:0.515651:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033014 ES:SE:LP:AF:ID  -0.00285824:0.00305683:0.455932:0.033014:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036637 ES:SE:LP:AF:ID  -0.00222432:0.0027764:0.376751:0.036637:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03675  ES:SE:LP:AF:ID  -0.00232961:0.00276599:0.39794:0.03675:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036451 ES:SE:LP:AF:ID  -0.00201442:0.00278587:0.327902:0.036451:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016395 ES:SE:LP:AF:ID  -0.000880386:0.00429187:0.0757207:0.016395:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036991 ES:SE:LP:AF:ID  -0.00221704:0.00275497:0.376751:0.036991:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037089 ES:SE:LP:AF:ID  -0.00188924:0.00274548:0.309804:0.037089:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101233 ES:SE:LP:AF:ID  -0.00243853:0.00200028:0.657577:0.101233:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959086 ES:SE:LP:AF:ID  0.00118581:0.0026484:0.187087:0.959086:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031455 ES:SE:LP:AF:ID  0.00595716:0.00480678:0.657577:0.031455:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053264 ES:SE:LP:AF:ID  0.00372924:0.00382404:0.481486:0.053264:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036609 ES:SE:LP:AF:ID  -0.00233668:0.00276311:0.39794:0.036609:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036928 ES:SE:LP:AF:ID  -0.00249893:0.00273793:0.443698:0.036928:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84324  ES:SE:LP:AF:ID  0.000510557:0.00141894:0.142668:0.84324:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.0559   ES:SE:LP:AF:ID  -0.00175146:0.00229744:0.346787:0.0559:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122265 ES:SE:LP:AF:ID  -0.000166461:0.00155319:0.0409586:0.122265:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025721 ES:SE:LP:AF:ID  0.00426014:0.0038195:0.585027:0.025721:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121506 ES:SE:LP:AF:ID  -0.000269167:0.00155387:0.0655015:0.121506:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132323 ES:SE:LP:AF:ID  -0.000844136:0.0015312:0.236572:0.132323:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011129 ES:SE:LP:AF:ID  -0.00337642:0.00556861:0.267606:0.011129:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005705 ES:SE:LP:AF:ID  -0.000212062:0.00718192:0.00877392:0.005705:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002269 ES:SE:LP:AF:ID  0.0150982:0.012086:0.677781:0.002269:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036838 ES:SE:LP:AF:ID  -0.00174934:0.00271044:0.283997:0.036838:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83896  ES:SE:LP:AF:ID  0.000148176:0.0013741:0.0409586:0.83896:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83859  ES:SE:LP:AF:ID  5.50104e-05:0.00137263:0.0132283:0.83859:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869809 ES:SE:LP:AF:ID  -0.000401269:0.00147295:0.102373:0.869809:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129838 ES:SE:LP:AF:ID  0.000442691:0.00147597:0.119186:0.129838:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037348 ES:SE:LP:AF:ID  -0.00225674:0.00266455:0.39794:0.037348:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037592 ES:SE:LP:AF:ID  -0.00234661:0.00264769:0.420216:0.037592:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869151 ES:SE:LP:AF:ID  -0.000501495:0.00147006:0.136677:0.869151:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869248 ES:SE:LP:AF:ID  -0.000446344:0.00147064:0.119186:0.869248:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037551 ES:SE:LP:AF:ID  -0.00233451:0.00265914:0.420216:0.037551:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869154 ES:SE:LP:AF:ID  -0.000490962:0.00147003:0.130768:0.869154:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005128 ES:SE:LP:AF:ID  0.00283385:0.00754072:0.148742:0.005128:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005094 ES:SE:LP:AF:ID  0.00303236:0.00756049:0.161151:0.005094:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838041 ES:SE:LP:AF:ID  4.42733e-06:0.00136881:-0:0.838041:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037564 ES:SE:LP:AF:ID  -0.0020636:0.00266288:0.356547:0.037564:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838673 ES:SE:LP:AF:ID  1.50778e-05:0.00137265:0.00436481:0.838673:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013769 ES:SE:LP:AF:ID  0.00235873:0.00479158:0.207608:0.013769:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005534 ES:SE:LP:AF:ID  -0.0116719:0.00740114:0.958607:0.005534:rs184270342