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_110001.vcf.gz --id UKB-b:14294 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_110001.txt.gz --cohort_cases 88770 --cohort_controls 189558 --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-14294/UKB-b-14294_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14294/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-14294/UKB-b-14294_data.vcf.gz ...
Read summary statistics for 8925971 SNPs.
Dropped 8388 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, 1286895 SNPs remain.
After merging with regression SNP LD, 1286895 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0383 (0.0023)
Lambda GC: 1.2376
Mean Chi^2: 1.2459
Intercept: 1.0398 (0.0076)
Ratio: 0.162 (0.0308)
Analysis finished at Thu Oct 17 14:44:58 2019
Total time elapsed: 1.0m:34.49s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9474,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 45,
    "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": 90538,
    "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": 1286895,
    "ldsc_nsnp_merge_regression_ld": 1286895,
    "ldsc_observed_scale_h2_beta": 0.0383,
    "ldsc_observed_scale_h2_se": 0.0023,
    "ldsc_intercept_beta": 1.0398,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.2376,
    "ldsc_mean_chisq": 1.2459,
    "ldsc_ratio": 0.1619
}

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 8917622 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 8925971 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 8.645364e+00 5.759098e+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 7.878950e+07 5.634347e+07 828.0000000 3.242513e+07 6.935202e+07 1.145597e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.360000e-05 4.162200e-03 -0.0510647 -1.751100e-03 -2.130000e-05 1.700800e-03 4.445410e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.245700e-03 2.339300e-03 0.0012028 1.430200e-03 2.172500e-03 4.442600e-03 2.733260e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.735964e-01 2.956673e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.735949e-01 2.956413e-01 0.0000000 2.110426e-01 4.636570e-01 7.300630e-01 1.000000e+00 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.220109e-01 2.587448e-01 0.0039430 2.141300e-02 1.040660e-01 3.503750e-01 9.960570e-01 ▇▂▁▁▁
numeric AF_reference 90538 0.9898568 NA NA NA NA NA NA NA 2.221582e-01 2.506698e-01 0.0000000 1.877000e-02 1.212060e-01 3.484420e-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 -0.0011459 0.0022158 0.6100002 0.6050661 0.624734 0.7821490 NA
1 54676 rs2462492 C T -0.0032096 0.0021933 0.1400000 0.1433619 0.399608 NA NA
1 86028 rs114608975 T C -0.0014551 0.0035180 0.6800001 0.6791547 0.103207 0.0277556 NA
1 91536 rs6702460 G T -0.0040489 0.0021613 0.0610000 0.0610193 0.457235 0.4207270 NA
1 234313 rs8179466 C T 0.0050601 0.0042637 0.2399999 0.2353134 0.074452 NA NA
1 534192 rs6680723 C T -0.0005496 0.0024653 0.8200001 0.8235961 0.241253 NA NA
1 546697 rs12025928 A G 0.0002930 0.0030658 0.9199999 0.9238734 0.913022 NA NA
1 693731 rs12238997 A G 0.0026707 0.0020671 0.2000000 0.1963500 0.116229 0.1417730 NA
1 705882 rs72631875 G A 0.0009376 0.0030187 0.7600007 0.7561047 0.067636 0.0315495 NA
1 706368 rs55727773 A G 0.0028650 0.0015305 0.0610000 0.0612154 0.516034 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0004374 0.0018501 0.8100000 0.8131062 0.137513 0.2052720 NA
22 51219387 rs9616832 T C 0.0000291 0.0024039 0.9900000 0.9903381 0.073414 0.0654952 NA
22 51219704 rs147475742 G A 0.0012351 0.0032249 0.6999999 0.7017199 0.041679 0.0473243 NA
22 51221190 rs369304721 G A 0.0022007 0.0032124 0.4899999 0.4933003 0.049623 NA NA
22 51221731 rs115055839 T C -0.0001242 0.0024057 0.9599999 0.9588417 0.072895 0.0625000 NA
22 51222100 rs114553188 G T 0.0006171 0.0028260 0.8300000 0.8271334 0.054339 0.0880591 NA
22 51223637 rs375798137 G A 0.0009120 0.0028398 0.7499995 0.7480983 0.053968 0.0788738 NA
22 51229805 rs9616985 T C -0.0004406 0.0024142 0.8600001 0.8552006 0.072744 0.0730831 NA
22 51232488 rs376461333 A G 0.0032473 0.0056925 0.5700002 0.5683716 0.019977 NA NA
22 51237063 rs3896457 T C -0.0015740 0.0014715 0.2800000 0.2847804 0.297371 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624734 ES:SE:LP:AF:ID  -0.00114587:0.00221583:0.21467:0.624734:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399608 ES:SE:LP:AF:ID  -0.0032096:0.00219327:0.853872:0.399608:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103207 ES:SE:LP:AF:ID  -0.0014551:0.00351799:0.167491:0.103207:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457235 ES:SE:LP:AF:ID  -0.00404894:0.00216133:1.21467:0.457235:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074452 ES:SE:LP:AF:ID  0.00506012:0.00426373:0.619789:0.074452:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241253 ES:SE:LP:AF:ID  -0.00054957:0.0024653:0.0861861:0.241253:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913022 ES:SE:LP:AF:ID  0.000292956:0.00306581:0.0362122:0.913022:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116229 ES:SE:LP:AF:ID  0.00267071:0.00206708:0.69897:0.116229:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067636 ES:SE:LP:AF:ID  0.000937599:0.00301867:0.119186:0.067636:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516034 ES:SE:LP:AF:ID  0.00286498:0.00153049:1.21467:0.516034:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033221 ES:SE:LP:AF:ID  -0.00266777:0.00384815:0.309804:0.033221:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036858 ES:SE:LP:AF:ID  -0.00330686:0.00349533:0.468521:0.036858:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036973 ES:SE:LP:AF:ID  -0.0034218:0.00348203:0.481486:0.036973:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036666 ES:SE:LP:AF:ID  -0.00320896:0.00350769:0.443698:0.036666:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016386 ES:SE:LP:AF:ID  0.00770929:0.00542234:0.79588:0.016386:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037224 ES:SE:LP:AF:ID  -0.00390022:0.00346814:0.585027:0.037224:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037327 ES:SE:LP:AF:ID  -0.00360764:0.00345619:0.522879:0.037327:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10132  ES:SE:LP:AF:ID  -0.00143002:0.0025226:0.244125:0.10132:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958751 ES:SE:LP:AF:ID  0.0023995:0.00333092:0.327902:0.958751:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031432 ES:SE:LP:AF:ID  -0.0157555:0.0060821:2.01773:0.031432:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053065 ES:SE:LP:AF:ID  -0.00326153:0.00484455:0.30103:0.053065:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036836 ES:SE:LP:AF:ID  -0.00384836:0.00347845:0.568636:0.036836:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037129 ES:SE:LP:AF:ID  -0.00386802:0.00344781:0.585027:0.037129:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.842972 ES:SE:LP:AF:ID  -0.00109557:0.00178974:0.267606:0.842972:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055829 ES:SE:LP:AF:ID  0.00084016:0.0028999:0.113509:0.055829:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12231  ES:SE:LP:AF:ID  0.00180338:0.0019603:0.443698:0.12231:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025441 ES:SE:LP:AF:ID  0.000457653:0.00484603:0.0362122:0.025441:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121537 ES:SE:LP:AF:ID  0.00206226:0.00196128:0.537602:0.121537:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132407 ES:SE:LP:AF:ID  0.000229939:0.00193205:0.0409586:0.132407:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011196 ES:SE:LP:AF:ID  -0.0176564:0.00700409:1.92082:0.011196:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005813 ES:SE:LP:AF:ID  -0.0180567:0.00898251:1.35655:0.005813:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037048 ES:SE:LP:AF:ID  -0.00338207:0.00341314:0.49485:0.037048:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838827 ES:SE:LP:AF:ID  -0.000371486:0.0017337:0.0809219:0.838827:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838431 ES:SE:LP:AF:ID  -0.000433526:0.00173172:0.09691:0.838431:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869749 ES:SE:LP:AF:ID  -0.00139859:0.00185836:0.346787:0.869749:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129911 ES:SE:LP:AF:ID  0.0013535:0.00186212:0.327902:0.129911:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037562 ES:SE:LP:AF:ID  -0.0036323:0.00335461:0.552842:0.037562:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037807 ES:SE:LP:AF:ID  -0.0036256:0.00333306:0.552842:0.037807:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869068 ES:SE:LP:AF:ID  -0.00156407:0.00185458:0.39794:0.869068:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869167 ES:SE:LP:AF:ID  -0.00152638:0.00185531:0.387216:0.869167:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037772 ES:SE:LP:AF:ID  -0.00343638:0.00334742:0.522879:0.037772:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869073 ES:SE:LP:AF:ID  -0.00158805:0.00185456:0.408935:0.869073:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005197 ES:SE:LP:AF:ID  -0.0107839:0.00945099:0.60206:0.005197:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005163 ES:SE:LP:AF:ID  -0.0106637:0.00947582:0.585027:0.005163:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837864 ES:SE:LP:AF:ID  -0.000693097:0.00172696:0.161151:0.837864:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037787 ES:SE:LP:AF:ID  -0.00351272:0.0033522:0.537602:0.037787:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838504 ES:SE:LP:AF:ID  -0.000778071:0.00173187:0.187087:0.838504:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013752 ES:SE:LP:AF:ID  -0.00537753:0.00605708:0.431798:0.013752:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005436 ES:SE:LP:AF:ID  -0.0233873:0.00944265:1.88606:0.005436:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839648 ES:SE:LP:AF:ID  -0.000580296:0.00175534:0.130768:0.839648:rs3131965