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_2316.vcf.gz --id UKB-b:18335 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2316.txt.gz --cohort_cases 95131 --cohort_controls 358828 --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-18335/UKB-b-18335_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18335/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18335/UKB-b-18335_data.vcf.gz ...
Read summary statistics for 8978156 SNPs.
Dropped 8635 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, 1287059 SNPs remain.
After merging with regression SNP LD, 1287059 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0559 (0.0025)
Lambda GC: 1.4298
Mean Chi^2: 1.5567
Intercept: 1.0537 (0.0089)
Ratio: 0.0964 (0.016)
Analysis finished at Thu Oct 17 14:41:57 2019
Total time elapsed: 1.0m:38.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9475,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 52,
    "n_p_sig": 5633,
    "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": 92593,
    "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": 1287059,
    "ldsc_nsnp_merge_regression_ld": 1287059,
    "ldsc_observed_scale_h2_beta": 0.0559,
    "ldsc_observed_scale_h2_se": 0.0025,
    "ldsc_intercept_beta": 1.0537,
    "ldsc_intercept_se": 0.0089,
    "ldsc_lambda_gc": 1.4298,
    "ldsc_mean_chisq": 1.5567,
    "ldsc_ratio": 0.0965
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
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 TRUE
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 8969560 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 8978156 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 8.644110e+00 5.758327e+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 7.879054e+07 5.633809e+07 828.0000000 3.243228e+07 6.935655e+07 1.145474e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.200000e-05 2.976400e-03 -0.0387254 -1.247300e-03 9.500000e-06 1.288400e-03 3.584550e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.238000e-03 1.631200e-03 0.0008188 9.750000e-04 1.489200e-03 3.067800e-03 1.896450e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.553053e-01 3.005815e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.553055e-01 3.005561e-01 0.0000000 1.837953e-01 4.392759e-01 7.153211e-01 1.000000e+00 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.208184e-01 2.586203e-01 0.0036800 2.080800e-02 1.023540e-01 3.484320e-01 9.963200e-01 ▇▂▁▁▁
numeric AF_reference 92593 0.9896869 NA NA NA NA NA NA NA 2.210481e-01 2.505244e-01 0.0000000 1.817090e-02 1.198080e-01 3.466450e-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 -0.0019457 0.0015057 0.2000000 0.1962935 0.623725 0.7821490 NA
1 54676 rs2462492 C T -0.0012133 0.0014918 0.4199997 0.4160544 0.400410 NA NA
1 86028 rs114608975 T C 0.0039110 0.0023853 0.1000000 0.1010829 0.103536 0.0277556 NA
1 91536 rs6702460 G T 0.0000125 0.0014690 0.9900000 0.9931939 0.456859 0.4207270 NA
1 234313 rs8179466 C T -0.0023602 0.0028980 0.4199997 0.4153972 0.074467 NA NA
1 534192 rs6680723 C T 0.0012650 0.0016785 0.4500005 0.4510627 0.240937 NA NA
1 546697 rs12025928 A G -0.0005684 0.0020928 0.7899998 0.7859212 0.913418 NA NA
1 693731 rs12238997 A G 0.0002134 0.0014065 0.8800001 0.8794191 0.116246 0.1417730 NA
1 705882 rs72631875 G A 0.0007199 0.0020608 0.7300002 0.7268289 0.067300 0.0315495 NA
1 706368 rs55727773 A G 0.0004831 0.0010418 0.6400000 0.6428114 0.515828 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0000602 0.0012570 0.9599999 0.9618020 0.138068 0.2052720 NA
22 51219387 rs9616832 T C -0.0003537 0.0016320 0.8300000 0.8284232 0.073768 0.0654952 NA
22 51219704 rs147475742 G A -0.0001713 0.0021871 0.9400001 0.9375670 0.041965 0.0473243 NA
22 51221190 rs369304721 G A 0.0004969 0.0021840 0.8200001 0.8200199 0.049729 NA NA
22 51221731 rs115055839 T C -0.0002649 0.0016330 0.8700001 0.8711573 0.073259 0.0625000 NA
22 51222100 rs114553188 G T -0.0001141 0.0019215 0.9500000 0.9526682 0.054549 0.0880591 NA
22 51223637 rs375798137 G A -0.0000606 0.0019308 0.9699999 0.9749425 0.054179 0.0788738 NA
22 51229805 rs9616985 T C -0.0001253 0.0016389 0.9400001 0.9390648 0.073097 0.0730831 NA
22 51232488 rs376461333 A G -0.0003824 0.0038575 0.9199999 0.9210303 0.020087 NA NA
22 51237063 rs3896457 T C 0.0011379 0.0010024 0.2599998 0.2562965 0.297977 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623725 ES:SE:LP:AF:ID  -0.00194568:0.00150573:0.69897:0.623725:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40041  ES:SE:LP:AF:ID  -0.0012133:0.00149185:0.376751:0.40041:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103536 ES:SE:LP:AF:ID  0.003911:0.0023853:1:0.103536:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  1.2531e-05:0.00146901:0.00436481:0.456859:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074467 ES:SE:LP:AF:ID  -0.00236025:0.00289803:0.376751:0.074467:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240937 ES:SE:LP:AF:ID  0.001265:0.00167851:0.346787:0.240937:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913418 ES:SE:LP:AF:ID  -0.000568441:0.00209285:0.102373:0.913418:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116246 ES:SE:LP:AF:ID  0.00021338:0.00140654:0.0555173:0.116246:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0673   ES:SE:LP:AF:ID  0.000719934:0.0020608:0.136677:0.0673:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515828 ES:SE:LP:AF:ID  0.000483134:0.00104175:0.19382:0.515828:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032943 ES:SE:LP:AF:ID  -0.00233462:0.00262864:0.431798:0.032943:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036559 ES:SE:LP:AF:ID  -0.00256161:0.00238736:0.552842:0.036559:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036675 ES:SE:LP:AF:ID  -0.00224078:0.00237832:0.455932:0.036675:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036374 ES:SE:LP:AF:ID  -0.00254338:0.00239556:0.537602:0.036374:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016428 ES:SE:LP:AF:ID  -0.00308411:0.00368217:0.39794:0.016428:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036916 ES:SE:LP:AF:ID  -0.00211059:0.00236882:0.431798:0.036916:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037012 ES:SE:LP:AF:ID  -0.00185701:0.00236072:0.366532:0.037012:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101187 ES:SE:LP:AF:ID  -0.00311786:0.00171892:1.1549:0.101187:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95916  ES:SE:LP:AF:ID  0.00210384:0.00227688:0.443698:0.95916:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031442 ES:SE:LP:AF:ID  -0.00122995:0.00413031:0.113509:0.031442:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053294 ES:SE:LP:AF:ID  0.00425341:0.00328315:0.69897:0.053294:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036529 ES:SE:LP:AF:ID  -0.00206441:0.00237607:0.420216:0.036529:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036848 ES:SE:LP:AF:ID  -0.00243554:0.0023543:0.522879:0.036848:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843323 ES:SE:LP:AF:ID  0.000936372:0.00121899:0.356547:0.843323:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055859 ES:SE:LP:AF:ID  0.000950028:0.0019738:0.200659:0.055859:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122224 ES:SE:LP:AF:ID  -0.000314949:0.00133424:0.091515:0.122224:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02575  ES:SE:LP:AF:ID  0.00276503:0.00327814:0.39794:0.02575:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121466 ES:SE:LP:AF:ID  -0.000277453:0.00133481:0.0757207:0.121466:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132212 ES:SE:LP:AF:ID  -0.000961133:0.00131561:0.327902:0.132212:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011135 ES:SE:LP:AF:ID  0.00146561:0.00478145:0.119186:0.011135:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005697 ES:SE:LP:AF:ID  -0.00104812:0.00617432:0.0604807:0.005697:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03676  ES:SE:LP:AF:ID  -0.00215684:0.00233057:0.455932:0.03676:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839056 ES:SE:LP:AF:ID  0.000731329:0.0011804:0.267606:0.839056:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838683 ES:SE:LP:AF:ID  0.000731201:0.00117914:0.267606:0.838683:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869866 ES:SE:LP:AF:ID  0.000127633:0.00126531:0.0362122:0.869866:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12978  ES:SE:LP:AF:ID  -0.000124303:0.0012679:0.0362122:0.12978:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037267 ES:SE:LP:AF:ID  -0.00208412:0.00229126:0.443698:0.037267:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037509 ES:SE:LP:AF:ID  -0.00186805:0.00227685:0.387216:0.037509:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869209 ES:SE:LP:AF:ID  0.000195737:0.00126284:0.0555173:0.869209:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869307 ES:SE:LP:AF:ID  0.000121957:0.00126333:0.0362122:0.869307:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037468 ES:SE:LP:AF:ID  -0.00214665:0.00228665:0.455932:0.037468:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869211 ES:SE:LP:AF:ID  0.000183742:0.00126281:0.0555173:0.869211:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005133 ES:SE:LP:AF:ID  -0.00241422:0.00647449:0.148742:0.005133:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005099 ES:SE:LP:AF:ID  -0.00289315:0.00649149:0.180456:0.005099:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838144 ES:SE:LP:AF:ID  0.000773094:0.00117593:0.29243:0.838144:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03748  ES:SE:LP:AF:ID  -0.00207445:0.00228987:0.443698:0.03748:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838775 ES:SE:LP:AF:ID  0.000746431:0.00117924:0.275724:0.838775:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013811 ES:SE:LP:AF:ID  0.00612213:0.00411093:0.853872:0.013811:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005543 ES:SE:LP:AF:ID  -0.00267322:0.00635129:0.173925:0.005543:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839879 ES:SE:LP:AF:ID  0.000717921:0.00119515:0.259637:0.839879:rs3131965