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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_41246_1480.vcf.gz --id UKB-b:18888 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41246_1480.txt.gz --cohort_cases 49228 --cohort_controls 398299 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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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-18888/UKB-b-18888_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18888/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18888/UKB-b-18888_data.vcf.gz ...
Read summary statistics for 8218361 SNPs.
Dropped 6533 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, 1283963 SNPs remain.
After merging with regression SNP LD, 1283963 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.012 (0.0013)
Lambda GC: 1.1577
Mean Chi^2: 1.1709
Intercept: 1.0658 (0.0071)
Ratio: 0.3848 (0.0414)
Analysis finished at Thu Oct 17 14:42:23 2019
Total time elapsed: 1.0m:30.73s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9442,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 6.2303e-06,
    "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": 77083,
    "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": 1283963,
    "ldsc_nsnp_merge_regression_ld": 1283963,
    "ldsc_observed_scale_h2_beta": 0.012,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0658,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.1577,
    "ldsc_mean_chisq": 1.1709,
    "ldsc_ratio": 0.385
}

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 8211858 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 8218361 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 8.656704e+00 5.762811e+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 7.872763e+07 5.638833e+07 828.0000000 3.231494e+07 6.921295e+07 1.145479e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 6.200000e-06 1.823600e-03 -0.0197911 -8.234000e-04 3.100000e-06 8.315000e-04 2.076240e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.469300e-03 9.265000e-04 0.0006376 7.429000e-04 1.054700e-03 1.950500e-03 9.967800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.780446e-01 2.945457e-01 0.0000001 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 4.780448e-01 2.945200e-01 0.0000001 2.167004e-01 4.706561e-01 7.331622e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.395624e-01 2.603978e-01 0.0071100 3.151000e-02 1.283340e-01 3.796250e-01 9.928900e-01 ▇▂▂▁▁
numeric AF_reference 77083 0.9906206 NA NA NA NA NA NA NA 2.389968e-01 2.522735e-01 0.0000000 3.194890e-02 1.441690e-01 3.753990e-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 -0.0014762 0.0011730 0.2099999 0.2082165 0.623735 0.7821490 NA
1 54676 rs2462492 C T 0.0011489 0.0011623 0.3200000 0.3229179 0.400431 NA NA
1 86028 rs114608975 T C -0.0010265 0.0018579 0.5800000 0.5805980 0.103547 0.0277556 NA
1 91536 rs6702460 G T 0.0005101 0.0011441 0.6600001 0.6556989 0.456865 0.4207270 NA
1 234313 rs8179466 C T -0.0002668 0.0022569 0.9100000 0.9059033 0.074463 NA NA
1 534192 rs6680723 C T 0.0010529 0.0013072 0.4199997 0.4205399 0.240951 NA NA
1 546697 rs12025928 A G 0.0003802 0.0016311 0.8200001 0.8156800 0.913511 NA NA
1 693731 rs12238997 A G 0.0008337 0.0010955 0.4500005 0.4466169 0.116359 0.1417730 NA
1 705882 rs72631875 G A -0.0009209 0.0016056 0.5700002 0.5662527 0.067295 0.0315495 NA
1 706368 rs55727773 A G -0.0012733 0.0008116 0.1199999 0.1166768 0.515738 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0003184 0.0009787 0.7400005 0.7449485 0.138028 0.2052720 NA
22 51219387 rs9616832 T C 0.0005143 0.0012700 0.6899999 0.6855070 0.073813 0.0654952 NA
22 51219704 rs147475742 G A 0.0022556 0.0017016 0.1800002 0.1849893 0.041998 0.0473243 NA
22 51221190 rs369304721 G A 0.0013084 0.0016985 0.4400003 0.4411096 0.049801 NA NA
22 51221731 rs115055839 T C 0.0002583 0.0012708 0.8400000 0.8389366 0.073306 0.0625000 NA
22 51222100 rs114553188 G T 0.0002678 0.0014968 0.8600001 0.8580195 0.054497 0.0880591 NA
22 51223637 rs375798137 G A 0.0002224 0.0015040 0.8800001 0.8824639 0.054126 0.0788738 NA
22 51229805 rs9616985 T C 0.0002030 0.0012754 0.8700001 0.8735333 0.073143 0.0730831 NA
22 51232488 rs376461333 A G 0.0036502 0.0030051 0.2200002 0.2244915 0.020060 NA NA
22 51237063 rs3896457 T C 0.0003655 0.0007805 0.6400000 0.6396217 0.298083 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623735 ES:SE:LP:AF:ID  -0.00147619:0.00117299:0.677781:0.623735:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400431 ES:SE:LP:AF:ID  0.00114887:0.00116226:0.49485:0.400431:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103547 ES:SE:LP:AF:ID  -0.0010265:0.00185788:0.236572:0.103547:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456865 ES:SE:LP:AF:ID  0.000510112:0.00114411:0.180456:0.456865:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074463 ES:SE:LP:AF:ID  -0.00026678:0.00225688:0.0409586:0.074463:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240951 ES:SE:LP:AF:ID  0.00105293:0.0013072:0.376751:0.240951:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913511 ES:SE:LP:AF:ID  0.000380222:0.00163112:0.0861861:0.913511:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116359 ES:SE:LP:AF:ID  0.000833734:0.00109548:0.346787:0.116359:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067295 ES:SE:LP:AF:ID  -0.000920927:0.00160558:0.244125:0.067295:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515738 ES:SE:LP:AF:ID  -0.0012733:0.0008116:0.920819:0.515738:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033032 ES:SE:LP:AF:ID  0.000935683:0.00204507:0.187087:0.033032:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036651 ES:SE:LP:AF:ID  0.00105395:0.00185757:0.244125:0.036651:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036767 ES:SE:LP:AF:ID  0.000958791:0.00185054:0.221849:0.036767:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036463 ES:SE:LP:AF:ID  0.000951637:0.00186396:0.21467:0.036463:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016437 ES:SE:LP:AF:ID  -0.000687678:0.00286851:0.091515:0.016437:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037002 ES:SE:LP:AF:ID  0.000919931:0.00184335:0.207608:0.037002:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037103 ES:SE:LP:AF:ID  0.000942447:0.00183687:0.21467:0.037103:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101247 ES:SE:LP:AF:ID  0.00137251:0.00133867:0.508638:0.101247:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95908  ES:SE:LP:AF:ID  0.000301172:0.00177202:0.0604807:0.95908:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031447 ES:SE:LP:AF:ID  -0.00301096:0.00321702:0.455932:0.031447:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05332  ES:SE:LP:AF:ID  -0.00526803:0.00255564:1.40894:0.05332:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036613 ES:SE:LP:AF:ID  0.000919341:0.00184896:0.207608:0.036613:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03693  ES:SE:LP:AF:ID  0.00125895:0.0018321:0.309804:0.03693:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84315  ES:SE:LP:AF:ID  -0.000507572:0.000949378:0.229148:0.84315:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055896 ES:SE:LP:AF:ID  0.000141926:0.00153761:0.0315171:0.055896:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122342 ES:SE:LP:AF:ID  4.21032e-05:0.00103915:0.0132283:0.122342:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025704 ES:SE:LP:AF:ID  0.00341616:0.00255679:0.744727:0.025704:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121582 ES:SE:LP:AF:ID  6.13357e-05:0.00103959:0.0222764:0.121582:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132379 ES:SE:LP:AF:ID  0.00064252:0.00102452:0.275724:0.132379:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011134 ES:SE:LP:AF:ID  0.00232509:0.00372482:0.275724:0.011134:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.03684  ES:SE:LP:AF:ID  0.00126592:0.00181373:0.309804:0.03684:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83885  ES:SE:LP:AF:ID  -0.000349264:0.000919227:0.154902:0.83885:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838469 ES:SE:LP:AF:ID  -0.000274958:0.000918203:0.119186:0.838469:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869706 ES:SE:LP:AF:ID  0.000189903:0.000985325:0.0705811:0.869706:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12996  ES:SE:LP:AF:ID  -0.000201554:0.000987287:0.0757207:0.12996:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037353 ES:SE:LP:AF:ID  0.000849358:0.0017829:0.200659:0.037353:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037598 ES:SE:LP:AF:ID  0.000922521:0.0017716:0.221849:0.037598:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869043 ES:SE:LP:AF:ID  0.000288861:0.000983363:0.113509:0.869043:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869143 ES:SE:LP:AF:ID  0.000336474:0.000983761:0.136677:0.869143:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037558 ES:SE:LP:AF:ID  0.000795369:0.00177926:0.187087:0.037558:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869046 ES:SE:LP:AF:ID  0.00027806:0.000983346:0.107905:0.869046:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837921 ES:SE:LP:AF:ID  -0.000264992:0.000915655:0.113509:0.837921:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037573 ES:SE:LP:AF:ID  0.000846018:0.00178172:0.200659:0.037573:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838549 ES:SE:LP:AF:ID  -0.000294368:0.00091822:0.124939:0.838549:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013768 ES:SE:LP:AF:ID  0.000791693:0.00320674:0.09691:0.013768:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.83967  ES:SE:LP:AF:ID  -0.000192267:0.0009307:0.0757207:0.83967:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869335 ES:SE:LP:AF:ID  8.34123e-05:0.000982267:0.0315171:0.869335:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868885 ES:SE:LP:AF:ID  0.000113123:0.00097983:0.0409586:0.868885:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867826 ES:SE:LP:AF:ID  0.000159029:0.000977899:0.0604807:0.867826:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869026 ES:SE:LP:AF:ID  0.000117151:0.000980618:0.0457575:0.869026:rs4951929