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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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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_103180.vcf.gz --id UKB-b:14166 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_103180.txt.gz --cohort_controls 64944 --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-14166/UKB-b-14166_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14166/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:16 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14166/UKB-b-14166_data.vcf.gz ...
Read summary statistics for 8624944 SNPs.
Dropped 7371 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, 1285749 SNPs remain.
After merging with regression SNP LD, 1285749 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.004 (0.0067)
Lambda GC: 1.006
Mean Chi^2: 1.0068
Intercept: 1.0018 (0.006)
Ratio: 0.2651 (0.8884)
Analysis finished at Thu Oct 17 14:44:50 2019
Total time elapsed: 1.0m:34.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "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": 83097,
    "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": 1285749,
    "ldsc_nsnp_merge_regression_ld": 1285749,
    "ldsc_observed_scale_h2_beta": 0.004,
    "ldsc_observed_scale_h2_se": 0.0067,
    "ldsc_intercept_beta": 1.0018,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.006,
    "ldsc_mean_chisq": 1.0068,
    "ldsc_ratio": 0.2647
}

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 8617607 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 8624944 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 8.650346e+00 5.760989e+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 7.877010e+07 5.637175e+07 828.0000000 3.238532e+07 6.929172e+07 1.145689e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.260000e-05 4.792700e-03 -0.0432235 -2.039100e-03 -4.110000e-05 1.938500e-03 6.371960e-02 ▁▆▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.957900e-03 2.701600e-03 0.0015719 1.851100e-03 2.729300e-03 5.350200e-03 2.709650e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.992132e-01 2.889309e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.992143e-01 2.889054e-01 0.0000000 2.480703e-01 4.987197e-01 7.495543e-01 9.999995e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291182e-01 2.594883e-01 0.0053900 2.519000e-02 1.138980e-01 3.626200e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83097 0.9903655 NA NA NA NA NA NA NA 2.288674e-01 2.514591e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 -0.0003592 0.0028970 0.9000000 0.9013267 0.623813 0.7821490 NA
1 54676 rs2462492 C T 0.0031037 0.0028886 0.2800000 0.2826225 0.399150 NA NA
1 86028 rs114608975 T C 0.0012723 0.0045980 0.7800007 0.7820089 0.103539 0.0277556 NA
1 91536 rs6702460 G T -0.0002618 0.0028412 0.9299999 0.9265696 0.455921 0.4207270 NA
1 234313 rs8179466 C T 0.0000118 0.0056186 1.0000000 0.9983306 0.074457 NA NA
1 534192 rs6680723 C T -0.0001907 0.0032360 0.9500000 0.9530088 0.242058 NA NA
1 546697 rs12025928 A G -0.0060669 0.0040152 0.1299999 0.1307949 0.912866 NA NA
1 693731 rs12238997 A G -0.0061704 0.0026982 0.0219999 0.0222043 0.117310 0.1417730 NA
1 705882 rs72631875 G A -0.0002540 0.0039328 0.9500000 0.9485139 0.067702 0.0315495 NA
1 706368 rs55727773 A G 0.0043459 0.0020027 0.0299999 0.0300074 0.513303 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0067706 0.0024360 0.0054000 0.0054462 0.136310 0.2052720 NA
22 51219387 rs9616832 T C -0.0105780 0.0031751 0.0008600 0.0008635 0.071795 0.0654952 NA
22 51219704 rs147475742 G A -0.0118123 0.0042238 0.0052000 0.0051648 0.041186 0.0473243 NA
22 51221190 rs369304721 G A -0.0166661 0.0042538 0.0000890 0.0000893 0.048369 NA NA
22 51221731 rs115055839 T C -0.0105264 0.0031758 0.0009200 0.0009177 0.071346 0.0625000 NA
22 51222100 rs114553188 G T -0.0032115 0.0036801 0.3800004 0.3828495 0.054847 0.0880591 NA
22 51223637 rs375798137 G A -0.0031172 0.0036993 0.4000000 0.3994278 0.054467 0.0788738 NA
22 51229805 rs9616985 T C -0.0104643 0.0031856 0.0010000 0.0010201 0.071251 0.0730831 NA
22 51232488 rs376461333 A G -0.0093851 0.0073387 0.2000000 0.2009522 0.020454 NA NA
22 51237063 rs3896457 T C 0.0002735 0.0019231 0.8900000 0.8868923 0.298415 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623813 ES:SE:LP:AF:ID  -0.000359191:0.00289704:0.0457575:0.623813:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39915  ES:SE:LP:AF:ID  0.00310369:0.00288864:0.552842:0.39915:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103539 ES:SE:LP:AF:ID  0.00127229:0.00459805:0.107905:0.103539:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455921 ES:SE:LP:AF:ID  -0.000261847:0.00284117:0.0315171:0.455921:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074457 ES:SE:LP:AF:ID  1.17558e-05:0.00561855:-0:0.074457:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242058 ES:SE:LP:AF:ID  -0.000190693:0.00323599:0.0222764:0.242058:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912866 ES:SE:LP:AF:ID  -0.00606688:0.00401521:0.886057:0.912866:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11731  ES:SE:LP:AF:ID  -0.00617037:0.00269819:1.65758:0.11731:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067702 ES:SE:LP:AF:ID  -0.000253953:0.0039328:0.0222764:0.067702:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513303 ES:SE:LP:AF:ID  0.00434591:0.00200273:1.52288:0.513303:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033663 ES:SE:LP:AF:ID  -0.00287665:0.00499285:0.251812:0.033663:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037439 ES:SE:LP:AF:ID  -0.00256538:0.00452858:0.244125:0.037439:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037625 ES:SE:LP:AF:ID  -0.00255702:0.00450488:0.244125:0.037625:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037202 ES:SE:LP:AF:ID  -0.00267848:0.00454606:0.251812:0.037202:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016275 ES:SE:LP:AF:ID  -0.00349324:0.00713086:0.207608:0.016275:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037842 ES:SE:LP:AF:ID  -0.00283042:0.00448948:0.275724:0.037842:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037936 ES:SE:LP:AF:ID  -0.00261491:0.00447522:0.251812:0.037936:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102738 ES:SE:LP:AF:ID  -0.00496933:0.00326826:0.886057:0.102738:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958108 ES:SE:LP:AF:ID  0.0033024:0.00432234:0.356547:0.958108:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031691 ES:SE:LP:AF:ID  0.00570004:0.007913:0.327902:0.031691:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052725 ES:SE:LP:AF:ID  -0.00504629:0.0063737:0.366532:0.052725:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037432 ES:SE:LP:AF:ID  -0.00243587:0.0045044:0.229148:0.037432:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037698 ES:SE:LP:AF:ID  -0.00264421:0.00446734:0.259637:0.037698:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841459 ES:SE:LP:AF:ID  0.0044526:0.00233349:1.25181:0.841459:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056335 ES:SE:LP:AF:ID  -0.0104165:0.00379045:2.22185:0.056335:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123073 ES:SE:LP:AF:ID  -0.00530929:0.00256299:1.42022:0.123073:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025132 ES:SE:LP:AF:ID  0.00384414:0.00638247:0.259637:0.025132:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122326 ES:SE:LP:AF:ID  -0.00522037:0.00256382:1.37675:0.122326:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134127 ES:SE:LP:AF:ID  -0.00454239:0.00251685:1.14874:0.134127:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011558 ES:SE:LP:AF:ID  -0.00684947:0.00896965:0.346787:0.011558:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.0061   ES:SE:LP:AF:ID  0.00467115:0.0113904:0.167491:0.0061:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03758  ES:SE:LP:AF:ID  -0.0032974:0.00442601:0.337242:0.03758:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837048 ES:SE:LP:AF:ID  0.00546561:0.00225737:1.82391:0.837048:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836752 ES:SE:LP:AF:ID  0.00540519:0.00225572:1.76955:0.836752:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868567 ES:SE:LP:AF:ID  0.00641075:0.00242384:2.08619:0.868567:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131    ES:SE:LP:AF:ID  -0.00612051:0.00243006:1.92082:0.131:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038025 ES:SE:LP:AF:ID  -0.00341353:0.00435656:0.366532:0.038025:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038271 ES:SE:LP:AF:ID  -0.00352686:0.00432955:0.376751:0.038271:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86798  ES:SE:LP:AF:ID  0.00641908:0.00241994:2.09691:0.86798:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868054 ES:SE:LP:AF:ID  0.00639165:0.00242093:2.08092:0.868054:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038179 ES:SE:LP:AF:ID  -0.00342974:0.00434955:0.366532:0.038179:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867991 ES:SE:LP:AF:ID  0.0064132:0.00241988:2.09691:0.867991:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  -0.00895906:0.0121279:0.337242:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836177 ES:SE:LP:AF:ID  0.00555818:0.00224911:1.88606:0.836177:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038183 ES:SE:LP:AF:ID  -0.00348278:0.0043559:0.376751:0.038183:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836811 ES:SE:LP:AF:ID  0.00554444:0.00225527:1.85387:0.836811:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013031 ES:SE:LP:AF:ID  0.0170053:0.00815889:1.4318:0.013031:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005662 ES:SE:LP:AF:ID  0.00158346:0.012112:0.0457575:0.005662:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838126 ES:SE:LP:AF:ID  0.00587909:0.00228701:2:0.838126:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868233 ES:SE:LP:AF:ID  0.00645797:0.00241677:2.12494:0.868233:rs3115858