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-14926/UKB-b-14926_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14926/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:49 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14926/UKB-b-14926_data.vcf.gz ...
Read summary statistics for 9577963 SNPs.
Dropped 12218 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, 1288528 SNPs remain.
After merging with regression SNP LD, 1288528 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0336 (0.0019)
Lambda GC: 1.3066
Mean Chi^2: 1.3567
Intercept: 1.0566 (0.0085)
Ratio: 0.1586 (0.0238)
Analysis finished at Thu Oct 17 14:45:33 2019
Total time elapsed: 1.0m:43.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9493,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 7,
    "n_p_sig": 399,
    "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": 143637,
    "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": 1288528,
    "ldsc_nsnp_merge_regression_ld": 1288528,
    "ldsc_observed_scale_h2_beta": 0.0336,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.0566,
    "ldsc_intercept_se": 0.0085,
    "ldsc_lambda_gc": 1.3066,
    "ldsc_mean_chisq": 1.3567,
    "ldsc_ratio": 0.1587
}

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 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 9565806 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 9577963 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 8.627829e+00 5.750912e+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 7.883474e+07 5.629979e+07 828.0000000 3.254933e+07 6.942930e+07 1.145668e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.390000e-05 4.479200e-03 -0.0598261 -1.612800e-03 -9.400000e-06 1.573000e-03 9.040050e-02 ▁▇▆▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.252600e-03 2.794700e-03 0.0010029 1.216800e-03 1.979300e-03 4.407800e-03 5.270300e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.677202e-01 2.975123e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.677228e-01 2.974879e-01 0.0000000 2.017570e-01 4.563868e-01 7.257456e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.083382e-01 2.571754e-01 0.0015510 1.516200e-02 8.485000e-02 3.256130e-01 9.984490e-01 ▇▂▁▁▁
numeric AF_reference 143637 0.9850034 NA NA NA NA NA NA NA 2.103440e-01 2.488538e-01 0.0000000 1.297920e-02 1.048320e-01 3.274760e-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 0.0001628 0.0018452 0.9299999 0.9296732 0.623764 0.7821490 NA
1 54676 rs2462492 C T -0.0017738 0.0018278 0.3300000 0.3318032 0.400406 NA NA
1 86028 rs114608975 T C -0.0005339 0.0029220 0.8600001 0.8550336 0.103563 0.0277556 NA
1 91536 rs6702460 G T -0.0010967 0.0017997 0.5400003 0.5422679 0.456846 0.4207270 NA
1 234313 rs8179466 C T 0.0003385 0.0035485 0.9199999 0.9239973 0.074504 NA NA
1 534192 rs6680723 C T 0.0002431 0.0020559 0.9100000 0.9058813 0.240945 NA NA
1 546697 rs12025928 A G -0.0041200 0.0025652 0.1100001 0.1082468 0.913508 NA NA
1 693731 rs12238997 A G 0.0000242 0.0017226 0.9900000 0.9887938 0.116354 0.1417730 NA
1 705882 rs72631875 G A 0.0041930 0.0025248 0.0969996 0.0967760 0.067273 0.0315495 NA
1 706368 rs55727773 A G -0.0002735 0.0012762 0.8300000 0.8303312 0.515599 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0023286 0.0026793 0.3800004 0.3847850 0.041939 0.0473243 NA
22 51219766 rs182321900 C T 0.0220205 0.0124694 0.0769999 0.0774020 0.001939 NA NA
22 51220146 rs868950473 C T 0.0243146 0.0123538 0.0490004 0.0490464 0.001988 NA NA
22 51221190 rs369304721 G A -0.0006274 0.0026749 0.8100000 0.8145617 0.049719 NA NA
22 51221731 rs115055839 T C -0.0008675 0.0020005 0.6600001 0.6645591 0.073218 0.0625000 NA
22 51222100 rs114553188 G T 0.0057562 0.0023545 0.0140001 0.0144956 0.054475 0.0880591 NA
22 51223637 rs375798137 G A 0.0058099 0.0023659 0.0140001 0.0140627 0.054104 0.0788738 NA
22 51229805 rs9616985 T C -0.0008512 0.0020078 0.6700003 0.6716080 0.073051 0.0730831 NA
22 51232488 rs376461333 A G 0.0080959 0.0047273 0.0870001 0.0867917 0.020054 NA NA
22 51237063 rs3896457 T C 0.0005807 0.0012279 0.6400000 0.6362647 0.297950 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.00016285:0.0018452:0.0315171:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  -0.00177381:0.00182775:0.481486:0.400406:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103563 ES:SE:LP:AF:ID  -0.000533858:0.00292205:0.0655015:0.103563:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.00109672:0.00179971:0.267606:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074504 ES:SE:LP:AF:ID  0.00033853:0.00354854:0.0362122:0.074504:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240945 ES:SE:LP:AF:ID  0.000243082:0.00205592:0.0409586:0.240945:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913508 ES:SE:LP:AF:ID  -0.00411998:0.00256517:0.958607:0.913508:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116354 ES:SE:LP:AF:ID  2.4195e-05:0.00172263:0.00436481:0.116354:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067273 ES:SE:LP:AF:ID  0.00419299:0.00252485:1.01323:0.067273:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515599 ES:SE:LP:AF:ID  -0.000273458:0.00127619:0.0809219:0.515599:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032979 ES:SE:LP:AF:ID  0.00168632:0.00321874:0.221849:0.032979:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  0.00129704:0.00292357:0.180456:0.036594:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036711 ES:SE:LP:AF:ID  0.00160529:0.00291249:0.236572:0.036711:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036411 ES:SE:LP:AF:ID  0.00182164:0.00293343:0.275724:0.036411:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016396 ES:SE:LP:AF:ID  -0.00334742:0.00451707:0.337242:0.016396:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03695  ES:SE:LP:AF:ID  0.00157139:0.00290095:0.229148:0.03695:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037046 ES:SE:LP:AF:ID  0.00188774:0.00289106:0.29243:0.037046:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101247 ES:SE:LP:AF:ID  0.000417355:0.00210511:0.0757207:0.101247:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959119 ES:SE:LP:AF:ID  -0.00308713:0.00278817:0.568636:0.959119:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  -0.00183411:0.00505973:0.142668:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05328  ES:SE:LP:AF:ID  -0.00387164:0.00402339:0.468521:0.05328:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036565 ES:SE:LP:AF:ID  0.00185408:0.00290967:0.283997:0.036565:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036879 ES:SE:LP:AF:ID  0.00181407:0.00288327:0.275724:0.036879:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843219 ES:SE:LP:AF:ID  -0.000564666:0.00149308:0.148742:0.843219:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055932 ES:SE:LP:AF:ID  -0.000377609:0.00241703:0.0555173:0.055932:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122326 ES:SE:LP:AF:ID  -0.000428646:0.00163412:0.102373:0.122326:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025683 ES:SE:LP:AF:ID  -0.0078575:0.00402194:1.29243:0.025683:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12157  ES:SE:LP:AF:ID  -0.000488292:0.0016348:0.113509:0.12157:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132331 ES:SE:LP:AF:ID  0.00100929:0.00161144:0.275724:0.132331:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011145 ES:SE:LP:AF:ID  0.00678814:0.00585508:0.60206:0.011145:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005706 ES:SE:LP:AF:ID  -0.00278744:0.00755905:0.148742:0.005706:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002272 ES:SE:LP:AF:ID  0.0164029:0.0127053:0.69897:0.002272:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036795 ES:SE:LP:AF:ID  0.00126879:0.0028541:0.180456:0.036795:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838954 ES:SE:LP:AF:ID  -0.000936097:0.00144591:0.283997:0.838954:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838582 ES:SE:LP:AF:ID  -0.000920268:0.00144436:0.283997:0.838582:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869756 ES:SE:LP:AF:ID  -0.000544611:0.00154978:0.136677:0.869756:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  0.000149732:0.00155293:0.0362122:0.129892:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037306 ES:SE:LP:AF:ID  0.00186961:0.00280568:0.29243:0.037306:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  0.00170478:0.00278795:0.267606:0.03755:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869099 ES:SE:LP:AF:ID  -0.000501147:0.00154675:0.124939:0.869099:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869196 ES:SE:LP:AF:ID  -0.000557062:0.00154736:0.142668:0.869196:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037508 ES:SE:LP:AF:ID  0.00171551:0.00280002:0.267606:0.037508:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000511756:0.00154672:0.130768:0.869101:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005123 ES:SE:LP:AF:ID  0.00810752:0.00794002:0.508638:0.005123:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005089 ES:SE:LP:AF:ID  0.00822841:0.00796085:0.522879:0.005089:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838034 ES:SE:LP:AF:ID  -0.000903519:0.00144034:0.275724:0.838034:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037521 ES:SE:LP:AF:ID  0.00191684:0.00280395:0.309804:0.037521:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838663 ES:SE:LP:AF:ID  -0.000944323:0.00144439:0.29243:0.838663:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013784 ES:SE:LP:AF:ID  0.000456341:0.0050393:0.0315171:0.013784:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005543 ES:SE:LP:AF:ID  -0.0152831:0.00778147:1.30103:0.005543:rs184270342