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-10454/UKB-b-10454_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10454/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-10454/UKB-b-10454_data.vcf.gz ...
Read summary statistics for 9418961 SNPs.
Dropped 11034 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, 1288203 SNPs remain.
After merging with regression SNP LD, 1288203 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0183 (0.0015)
Lambda GC: 1.1688
Mean Chi^2: 1.1897
Intercept: 1.0391 (0.0072)
Ratio: 0.2062 (0.038)
Analysis finished at Thu Oct 17 14:42:00 2019
Total time elapsed: 1.0m:40.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9489,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 9.7517e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 7,
    "n_p_sig": 188,
    "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": 123854,
    "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": 1288203,
    "ldsc_nsnp_merge_regression_ld": 1288203,
    "ldsc_observed_scale_h2_beta": 0.0183,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0391,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.1688,
    "ldsc_mean_chisq": 1.1897,
    "ldsc_ratio": 0.2061
}

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 9407985 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 9418961 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 8.630397e+00 5.752659e+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 7.883311e+07 5.631196e+07 828.0000000 3.252678e+07 6.941487e+07 1.145674e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.800000e-06 4.197500e-03 -0.0484790 -1.517800e-03 1.100000e-05 1.536500e-03 5.672620e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.167600e-03 2.587400e-03 0.0010268 1.240000e-03 1.982000e-03 4.325900e-03 3.575450e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.804810e-01 2.938647e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.804814e-01 2.938405e-01 0.0000000 2.212067e-01 4.733503e-01 7.349828e-01 1.000000e+00 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.114235e-01 2.575071e-01 0.0019840 1.645800e-02 8.911900e-02 3.313170e-01 9.980160e-01 ▇▂▁▁▁
numeric AF_reference 123854 0.9868506 NA NA NA NA NA NA NA 2.127940e-01 2.492672e-01 0.0000000 1.397760e-02 1.082270e-01 3.320690e-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 0.0007577 0.0018911 0.6899999 0.6886803 0.623819 0.7821490 NA
1 54676 rs2462492 C T 0.0019878 0.0018718 0.2900000 0.2882452 0.400498 NA NA
1 86028 rs114608975 T C -0.0018941 0.0029933 0.5300002 0.5268873 0.103571 0.0277556 NA
1 91536 rs6702460 G T 0.0002661 0.0018436 0.8900000 0.8852319 0.456956 0.4207270 NA
1 234313 rs8179466 C T -0.0056010 0.0036370 0.1199999 0.1235622 0.074516 NA NA
1 534192 rs6680723 C T -0.0002663 0.0021068 0.9000000 0.8993981 0.240958 NA NA
1 546697 rs12025928 A G 0.0016245 0.0026254 0.5400003 0.5360716 0.913384 NA NA
1 693731 rs12238997 A G -0.0009969 0.0017651 0.5700002 0.5722208 0.116305 0.1417730 NA
1 705882 rs72631875 G A -0.0024243 0.0025851 0.3500000 0.3483466 0.067368 0.0315495 NA
1 706368 rs55727773 A G 0.0000970 0.0013077 0.9400001 0.9408422 0.515850 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0026849 0.0015775 0.0890000 0.0887514 0.137904 0.2052720 NA
22 51219387 rs9616832 T C 0.0028798 0.0020472 0.1600000 0.1595013 0.073752 0.0654952 NA
22 51219704 rs147475742 G A 0.0028747 0.0027443 0.2900000 0.2948648 0.041943 0.0473243 NA
22 51221190 rs369304721 G A 0.0027182 0.0027380 0.3200000 0.3208245 0.049745 NA NA
22 51221731 rs115055839 T C 0.0029864 0.0020484 0.1400000 0.1448651 0.073247 0.0625000 NA
22 51222100 rs114553188 G T 0.0033238 0.0024123 0.1700000 0.1682437 0.054410 0.0880591 NA
22 51223637 rs375798137 G A 0.0034287 0.0024239 0.1600000 0.1571951 0.054042 0.0788738 NA
22 51229805 rs9616985 T C 0.0030357 0.0020558 0.1400000 0.1397723 0.073079 0.0730831 NA
22 51232488 rs376461333 A G 0.0063555 0.0048410 0.1900002 0.1892395 0.020027 NA NA
22 51237063 rs3896457 T C -0.0012050 0.0012576 0.3400001 0.3379710 0.298174 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623819 ES:SE:LP:AF:ID  0.000757671:0.00189112:0.161151:0.623819:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400498 ES:SE:LP:AF:ID  0.00198777:0.00187176:0.537602:0.400498:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103571 ES:SE:LP:AF:ID  -0.00189408:0.00299334:0.275724:0.103571:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456956 ES:SE:LP:AF:ID  0.000266107:0.00184361:0.05061:0.456956:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074516 ES:SE:LP:AF:ID  -0.00560103:0.00363705:0.920819:0.074516:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240958 ES:SE:LP:AF:ID  -0.000266344:0.00210679:0.0457575:0.240958:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913384 ES:SE:LP:AF:ID  0.00162451:0.00262541:0.267606:0.913384:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116305 ES:SE:LP:AF:ID  -0.000996883:0.00176507:0.244125:0.116305:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067368 ES:SE:LP:AF:ID  -0.00242431:0.0025851:0.455932:0.067368:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51585  ES:SE:LP:AF:ID  9.70491e-05:0.00130774:0.0268721:0.51585:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033007 ES:SE:LP:AF:ID  0.00122361:0.0032955:0.148742:0.033007:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036636 ES:SE:LP:AF:ID  0.00119652:0.00299262:0.161151:0.036636:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036744 ES:SE:LP:AF:ID  0.00116993:0.00298176:0.161151:0.036744:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036446 ES:SE:LP:AF:ID  0.0013767:0.00300323:0.187087:0.036446:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016454 ES:SE:LP:AF:ID  0.00629251:0.00461849:0.769551:0.016454:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036986 ES:SE:LP:AF:ID  0.00131753:0.00296984:0.180456:0.036986:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037083 ES:SE:LP:AF:ID  0.00154275:0.00295969:0.221849:0.037083:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101225 ES:SE:LP:AF:ID  -0.000412388:0.00215671:0.0705811:0.101225:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959109 ES:SE:LP:AF:ID  -0.00104562:0.00285563:0.148742:0.959109:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031463 ES:SE:LP:AF:ID  0.00423241:0.00517922:0.387216:0.031463:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053271 ES:SE:LP:AF:ID  -0.00266784:0.00412151:0.283997:0.053271:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036595 ES:SE:LP:AF:ID  0.00197524:0.00297915:0.29243:0.036595:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036911 ES:SE:LP:AF:ID  0.00188939:0.00295206:0.283997:0.036911:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843211 ES:SE:LP:AF:ID  -0.000124289:0.00152954:0.0268721:0.843211:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055888 ES:SE:LP:AF:ID  -0.00162529:0.00247736:0.29243:0.055888:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1223   ES:SE:LP:AF:ID  -0.00100823:0.00167427:0.259637:0.1223:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02571  ES:SE:LP:AF:ID  -0.000313842:0.00411596:0.0268721:0.02571:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  -0.000933585:0.00167496:0.236572:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132331 ES:SE:LP:AF:ID  -0.000983417:0.00165091:0.259637:0.132331:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011118 ES:SE:LP:AF:ID  -0.0056324:0.0060067:0.455932:0.011118:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005711 ES:SE:LP:AF:ID  -0.00443278:0.00773568:0.244125:0.005711:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002257 ES:SE:LP:AF:ID  -0.0155058:0.0130719:0.619789:0.002257:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036838 ES:SE:LP:AF:ID  0.0019939:0.00292161:0.309804:0.036838:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838913 ES:SE:LP:AF:ID  0.000545961:0.00148133:0.148742:0.838913:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83854  ES:SE:LP:AF:ID  0.000522091:0.00147966:0.142668:0.83854:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869782 ES:SE:LP:AF:ID  0.00183047:0.00158795:0.60206:0.869782:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129875 ES:SE:LP:AF:ID  -0.00156817:0.00159115:0.49485:0.129875:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037341 ES:SE:LP:AF:ID  0.00166775:0.00287252:0.251812:0.037341:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037582 ES:SE:LP:AF:ID  0.00162738:0.00285449:0.244125:0.037582:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869125 ES:SE:LP:AF:ID  0.00175899:0.00158479:0.568636:0.869125:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  0.00180485:0.0015854:0.60206:0.869221:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037542 ES:SE:LP:AF:ID  0.00173656:0.00286674:0.267606:0.037542:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  0.00176262:0.00158476:0.568636:0.869126:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005127 ES:SE:LP:AF:ID  -0.000203712:0.00813266:0.00877392:0.005127:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005092 ES:SE:LP:AF:ID  -0.000147267:0.00815412:0.00436481:0.005092:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.83799  ES:SE:LP:AF:ID  0.000522661:0.00147554:0.142668:0.83799:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037553 ES:SE:LP:AF:ID  0.00176667:0.00287085:0.267606:0.037553:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838624 ES:SE:LP:AF:ID  0.000496873:0.00147971:0.130768:0.838624:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013763 ES:SE:LP:AF:ID  0.006959:0.00516576:0.744727:0.013763:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005554 ES:SE:LP:AF:ID  -3.98693e-05:0.00796082:-0:0.005554:rs184270342