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_1160.vcf.gz --id UKB-b:20300 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41246_1160.txt.gz --cohort_cases 27510 --cohort_controls 418183 --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-20300/UKB-b-20300_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20300/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20300/UKB-b-20300_data.vcf.gz ...
Read summary statistics for 7386643 SNPs.
Dropped 4963 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, 1273763 SNPs remain.
After merging with regression SNP LD, 1273763 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0183 (0.0016)
Lambda GC: 1.1716
Mean Chi^2: 1.1995
Intercept: 1.0404 (0.0081)
Ratio: 0.2025 (0.0404)
Analysis finished at Thu Oct 17 14:43:40 2019
Total time elapsed: 1.0m:28.13s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9389,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 3.2148e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 10,
    "n_p_sig": 556,
    "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": 68358,
    "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": 1273763,
    "ldsc_nsnp_merge_regression_ld": 1273763,
    "ldsc_observed_scale_h2_beta": 0.0183,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0404,
    "ldsc_intercept_se": 0.0081,
    "ldsc_lambda_gc": 1.1716,
    "ldsc_mean_chisq": 1.1995,
    "ldsc_ratio": 0.2025
}
 

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 7381702 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 7386643 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 8.663779e+00 5.763627e+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 7.863974e+07 5.644509e+07 828.0000000 3.217884e+07 6.905666e+07 1.145198e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.200000e-06 1.124800e-03 -0.0096820 -5.772000e-04 3.500000e-06 5.859000e-04 2.276810e-02 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.499000e-04 4.929000e-04 0.0004893 5.577000e-04 7.389000e-04 1.215500e-03 5.315700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.772492e-01 2.944812e-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 4.772517e-01 2.944572e-01 0.0000000 2.166917e-01 4.683615e-01 7.320286e-01 9.999995e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.635440e-01 2.606734e-01 0.0127230 4.907600e-02 1.620870e-01 4.152990e-01 9.872760e-01 ▇▂▂▁▁
numeric AF_reference 68358 0.9907457 NA NA NA NA NA NA NA 2.622650e-01 2.525414e-01 0.0000000 5.491210e-02 1.755190e-01 4.091450e-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 0.0011422 0.0009002 0.2000000 0.2044911 0.623782 0.7821490 NA
1 54676 rs2462492 C T -0.0002194 0.0008918 0.8100000 0.8057125 0.400412 NA NA
1 86028 rs114608975 T C -0.0000143 0.0014257 0.9900000 0.9919980 0.103539 0.0277556 NA
1 91536 rs6702460 G T 0.0009237 0.0008779 0.2900000 0.2927370 0.456877 0.4207270 NA
1 234313 rs8179466 C T 0.0009805 0.0017314 0.5700002 0.5711589 0.074468 NA NA
1 534192 rs6680723 C T 0.0022358 0.0010029 0.0259998 0.0257916 0.240938 NA NA
1 546697 rs12025928 A G -0.0001802 0.0012512 0.8900000 0.8855011 0.913476 NA NA
1 693731 rs12238997 A G -0.0003010 0.0008407 0.7199992 0.7203061 0.116360 0.1417730 NA
1 705882 rs72631875 G A -0.0008844 0.0012316 0.4700002 0.4727320 0.067338 0.0315495 NA
1 706368 rs55727773 A G -0.0000086 0.0006227 0.9900000 0.9889474 0.515733 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0010375 0.0007512 0.1700000 0.1672574 0.137985 0.2052720 NA
22 51219387 rs9616832 T C 0.0012790 0.0009748 0.1900002 0.1894870 0.073787 0.0654952 NA
22 51219704 rs147475742 G A 0.0016050 0.0013063 0.2200002 0.2191768 0.041974 0.0473243 NA
22 51221190 rs369304721 G A 0.0025479 0.0013039 0.0510000 0.0506896 0.049768 NA NA
22 51221731 rs115055839 T C 0.0012951 0.0009754 0.1800002 0.1842380 0.073279 0.0625000 NA
22 51222100 rs114553188 G T 0.0004660 0.0011490 0.6899999 0.6850507 0.054474 0.0880591 NA
22 51223637 rs375798137 G A 0.0003951 0.0011546 0.7300002 0.7321984 0.054103 0.0788738 NA
22 51229805 rs9616985 T C 0.0013173 0.0009789 0.1800002 0.1784174 0.073116 0.0730831 NA
22 51232488 rs376461333 A G -0.0010490 0.0023076 0.6499995 0.6494028 0.020045 NA NA
22 51237063 rs3896457 T C 0.0012780 0.0005989 0.0329997 0.0328451 0.298169 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623782 ES:SE:LP:AF:ID  0.00114222:0.000900194:0.69897:0.623782:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400412 ES:SE:LP:AF:ID  -0.000219359:0.000891845:0.091515:0.400412:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103539 ES:SE:LP:AF:ID  -1.42989e-05:0.00142573:0.00436481:0.103539:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456877 ES:SE:LP:AF:ID  0.000923662:0.000877892:0.537602:0.456877:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074468 ES:SE:LP:AF:ID  0.000980548:0.00173136:0.244125:0.074468:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240938 ES:SE:LP:AF:ID  0.0022358:0.0010029:1.58503:0.240938:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913476 ES:SE:LP:AF:ID  -0.000180179:0.00125125:0.05061:0.913476:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11636  ES:SE:LP:AF:ID  -0.00030103:0.000840749:0.142668:0.11636:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067338 ES:SE:LP:AF:ID  -0.000884368:0.00123164:0.327902:0.067338:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515733 ES:SE:LP:AF:ID  -8.62666e-06:0.000622736:0.00436481:0.515733:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033056 ES:SE:LP:AF:ID  0.000907256:0.00156884:0.251812:0.033056:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036676 ES:SE:LP:AF:ID  0.000899442:0.00142512:0.275724:0.036676:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036792 ES:SE:LP:AF:ID  0.00090186:0.00141973:0.275724:0.036792:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036488 ES:SE:LP:AF:ID  0.000911016:0.00143002:0.283997:0.036488:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016432 ES:SE:LP:AF:ID  0.00252864:0.00220226:0.60206:0.016432:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037026 ES:SE:LP:AF:ID  0.00100333:0.00141424:0.318759:0.037026:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037127 ES:SE:LP:AF:ID  0.00105002:0.00140923:0.337242:0.037127:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101226 ES:SE:LP:AF:ID  -0.000807775:0.00102743:0.366532:0.101226:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959059 ES:SE:LP:AF:ID  -0.00072157:0.00135955:0.221849:0.959059:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031438 ES:SE:LP:AF:ID  -0.000873164:0.00246919:0.142668:0.031438:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.0533   ES:SE:LP:AF:ID  -0.00473967:0.00196181:1.79588:0.0533:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036635 ES:SE:LP:AF:ID  0.000939871:0.00141859:0.29243:0.036635:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036953 ES:SE:LP:AF:ID  0.000949918:0.00140561:0.30103:0.036953:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843132 ES:SE:LP:AF:ID  3.32139e-05:0.000728542:0.0177288:0.843132:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055909 ES:SE:LP:AF:ID  -0.00056084:0.00117973:0.200659:0.055909:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122347 ES:SE:LP:AF:ID  -0.000391848:0.00079746:0.207608:0.122347:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025701 ES:SE:LP:AF:ID  0.00219904:0.00196231:0.585027:0.025701:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121589 ES:SE:LP:AF:ID  -0.0002789:0.000797789:0.136677:0.121589:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132415 ES:SE:LP:AF:ID  -0.000224089:0.000786135:0.107905:0.132415:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036865 ES:SE:LP:AF:ID  0.000735447:0.00139147:0.221849:0.036865:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83883  ES:SE:LP:AF:ID  -4.72605e-05:0.000705406:0.0222764:0.83883:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838451 ES:SE:LP:AF:ID  -1.30209e-05:0.000704624:0.00436481:0.838451:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869706 ES:SE:LP:AF:ID  0.000358324:0.000756153:0.19382:0.869706:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129957 ES:SE:LP:AF:ID  -0.000424606:0.000757663:0.236572:0.129957:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037385 ES:SE:LP:AF:ID  0.000687274:0.00136768:0.207608:0.037385:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037629 ES:SE:LP:AF:ID  0.000622164:0.00135905:0.187087:0.037629:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869045 ES:SE:LP:AF:ID  0.000386552:0.000754649:0.21467:0.869045:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869145 ES:SE:LP:AF:ID  0.000381168:0.000754957:0.21467:0.869145:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03759  ES:SE:LP:AF:ID  0.000631482:0.00136487:0.19382:0.03759:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869049 ES:SE:LP:AF:ID  0.000381768:0.000754636:0.21467:0.869049:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837899 ES:SE:LP:AF:ID  2.33524e-05:0.000702656:0.0132283:0.837899:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037604 ES:SE:LP:AF:ID  0.000672753:0.00136676:0.207608:0.037604:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83853  ES:SE:LP:AF:ID  -2.98164e-05:0.000704628:0.0132283:0.83853:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.01377  ES:SE:LP:AF:ID  -0.00239794:0.00246066:0.481486:0.01377:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839655 ES:SE:LP:AF:ID  5.28246e-05:0.000714214:0.0268721:0.839655:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869334 ES:SE:LP:AF:ID  0.000341819:0.000753797:0.187087:0.869334:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868885 ES:SE:LP:AF:ID  0.000289732:0.000751933:0.154902:0.868885:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867829 ES:SE:LP:AF:ID  0.000242512:0.000750441:0.124939:0.867829:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869024 ES:SE:LP:AF:ID  0.000278563:0.000752534:0.148742:0.869024:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869033 ES:SE:LP:AF:ID  0.00027602:0.000752591:0.148742:0.869033:rs4951862