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.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
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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_4195.vcf.gz --id UKB-b:11598 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_4195.txt.gz --cohort_controls 151546 --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-11598/UKB-b-11598_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11598/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-11598/UKB-b-11598_data.vcf.gz ...
Read summary statistics for 9326797 SNPs.
Dropped 10427 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, 1288004 SNPs remain.
After merging with regression SNP LD, 1288004 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.051 (0.0044)
Lambda GC: 1.1453
Mean Chi^2: 1.1667
Intercept: 1.0145 (0.0075)
Ratio: 0.0871 (0.0453)
Analysis finished at Thu Oct 17 14:42:29 2019
Total time elapsed: 1.0m:35.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9488,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 7,
    "n_p_sig": 83,
    "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": 113693,
    "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": 1288004,
    "ldsc_nsnp_merge_regression_ld": 1288004,
    "ldsc_observed_scale_h2_beta": 0.051,
    "ldsc_observed_scale_h2_se": 0.0044,
    "ldsc_intercept_beta": 1.0145,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.1453,
    "ldsc_mean_chisq": 1.1667,
    "ldsc_ratio": 0.087
}

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 9316422 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 9326797 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 8.634468e+00 5.753952e+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 7.881299e+07 5.630869e+07 828.0000000 3.250525e+07 6.939252e+07 1.145427e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.630000e-05 1.302860e-02 -0.1764220 -4.820800e-03 1.420000e-05 4.863800e-03 1.573800e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.000220e-02 7.938300e-03 0.0033374 4.016300e-03 6.357100e-03 1.370690e-02 1.160170e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.838156e-01 2.934877e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.838149e-01 2.934621e-01 0.0000000 2.253941e-01 4.781980e-01 7.380422e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.133665e-01 2.577661e-01 0.0023100 1.731300e-02 9.192900e-02 3.349410e-01 9.976900e-01 ▇▂▁▁▁
numeric AF_reference 113693 0.9878101 NA NA NA NA NA NA NA 2.144387e-01 2.495472e-01 0.0000000 1.477640e-02 1.104230e-01 3.348640e-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 -0.0075926 0.0061518 0.2200002 0.2171249 0.623778 0.7821490 NA
1 54676 rs2462492 C T 0.0085415 0.0061099 0.1600000 0.1621188 0.399250 NA NA
1 86028 rs114608975 T C 0.0078440 0.0097364 0.4199997 0.4204480 0.103813 0.0277556 NA
1 91536 rs6702460 G T 0.0043044 0.0060204 0.4700002 0.4746256 0.456274 0.4207270 NA
1 234313 rs8179466 C T -0.0076770 0.0118874 0.5199996 0.5183998 0.074486 NA NA
1 534192 rs6680723 C T -0.0060845 0.0068817 0.3800004 0.3766139 0.241089 NA NA
1 546697 rs12025928 A G -0.0094140 0.0085376 0.2700001 0.2701756 0.913064 NA NA
1 693731 rs12238997 A G -0.0074893 0.0057377 0.1900002 0.1917965 0.116894 0.1417730 NA
1 705882 rs72631875 G A 0.0065060 0.0083933 0.4400003 0.4382602 0.067604 0.0315495 NA
1 706368 rs55727773 A G -0.0013939 0.0042478 0.7400005 0.7427945 0.515024 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0031111 0.0051443 0.5500004 0.5453275 0.137083 0.2052720 NA
22 51219387 rs9616832 T C -0.0016572 0.0066913 0.8000000 0.8043960 0.072732 0.0654952 NA
22 51219704 rs147475742 G A -0.0030944 0.0089331 0.7300002 0.7290407 0.041665 0.0473243 NA
22 51221190 rs369304721 G A 0.0019502 0.0089530 0.8300000 0.8275652 0.049110 NA NA
22 51221731 rs115055839 T C -0.0006054 0.0066967 0.9299999 0.9279641 0.072205 0.0625000 NA
22 51222100 rs114553188 G T 0.0048465 0.0078376 0.5400003 0.5363378 0.054454 0.0880591 NA
22 51223637 rs375798137 G A 0.0047673 0.0078780 0.5500004 0.5450835 0.054064 0.0788738 NA
22 51229805 rs9616985 T C -0.0009066 0.0067214 0.8900000 0.8927017 0.072060 0.0730831 NA
22 51232488 rs376461333 A G 0.0041286 0.0157424 0.7899998 0.7931206 0.020170 NA NA
22 51237063 rs3896457 T C -0.0024087 0.0040844 0.5600000 0.5553670 0.297651 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623778 ES:SE:LP:AF:ID  -0.00759256:0.00615176:0.657577:0.623778:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39925  ES:SE:LP:AF:ID  0.00854151:0.00610989:0.79588:0.39925:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103813 ES:SE:LP:AF:ID  0.00784405:0.00973637:0.376751:0.103813:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456274 ES:SE:LP:AF:ID  0.00430441:0.00602038:0.327902:0.456274:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074486 ES:SE:LP:AF:ID  -0.00767705:0.0118874:0.283997:0.074486:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241089 ES:SE:LP:AF:ID  -0.00608449:0.00688172:0.420216:0.241089:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913064 ES:SE:LP:AF:ID  -0.009414:0.00853755:0.568636:0.913064:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116894 ES:SE:LP:AF:ID  -0.00748927:0.00573766:0.721246:0.116894:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067604 ES:SE:LP:AF:ID  0.00650596:0.00839333:0.356547:0.067604:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515024 ES:SE:LP:AF:ID  -0.00139392:0.00424775:0.130768:0.515024:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033571 ES:SE:LP:AF:ID  -0.00479814:0.0106122:0.187087:0.033571:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037272 ES:SE:LP:AF:ID  -0.00272149:0.00963835:0.107905:0.037272:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037398 ES:SE:LP:AF:ID  -0.00243508:0.00960079:0.09691:0.037398:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037056 ES:SE:LP:AF:ID  -0.00299109:0.00967355:0.119186:0.037056:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016376 ES:SE:LP:AF:ID  -0.00593801:0.0150916:0.161151:0.016376:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037638 ES:SE:LP:AF:ID  -0.00296317:0.00956256:0.119186:0.037638:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037737 ES:SE:LP:AF:ID  -0.00294735:0.00953134:0.119186:0.037737:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101553 ES:SE:LP:AF:ID  0.00444942:0.00699685:0.283997:0.101553:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958296 ES:SE:LP:AF:ID  0.00301759:0.0091943:0.130768:0.958296:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031684 ES:SE:LP:AF:ID  -0.0152508:0.0168217:0.443698:0.031684:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052652 ES:SE:LP:AF:ID  -0.0218886:0.0135668:0.958607:0.052652:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03721  ES:SE:LP:AF:ID  -0.000137141:0.00959714:0.00436481:0.03721:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  -0.00401333:0.00951204:0.173925:0.037535:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841985 ES:SE:LP:AF:ID  0.00667277:0.00496509:0.744727:0.841985:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05609  ES:SE:LP:AF:ID  -0.0166703:0.00806319:1.40894:0.05609:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122816 ES:SE:LP:AF:ID  -0.00835221:0.0054459:0.886057:0.122816:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025783 ES:SE:LP:AF:ID  -0.00995037:0.0133806:0.337242:0.025783:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122036 ES:SE:LP:AF:ID  -0.00827729:0.00544856:0.886057:0.122036:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133326 ES:SE:LP:AF:ID  -0.00770004:0.00535901:0.823909:0.133326:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011239 ES:SE:LP:AF:ID  0.0386755:0.0194276:1.3279:0.011239:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005842 ES:SE:LP:AF:ID  0.0126522:0.0248278:0.21467:0.005842:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037484 ES:SE:LP:AF:ID  -0.0038678:0.00941407:0.167491:0.037484:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837749 ES:SE:LP:AF:ID  0.00722813:0.00480805:0.886057:0.837749:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837362 ES:SE:LP:AF:ID  0.00717571:0.00480264:0.853872:0.837362:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  0.00723111:0.00515634:0.79588:0.869087:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.13062  ES:SE:LP:AF:ID  -0.00759962:0.00516649:0.853872:0.13062:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037976 ES:SE:LP:AF:ID  -0.00242977:0.00925902:0.102373:0.037976:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03823  ES:SE:LP:AF:ID  -0.00271765:0.00920027:0.113509:0.03823:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868408 ES:SE:LP:AF:ID  0.0072111:0.00514595:0.79588:0.868408:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868517 ES:SE:LP:AF:ID  0.00729157:0.00514829:0.79588:0.868517:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038161 ES:SE:LP:AF:ID  -0.00188197:0.00924014:0.0757207:0.038161:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868405 ES:SE:LP:AF:ID  0.00709794:0.00514561:0.769551:0.868405:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005106 ES:SE:LP:AF:ID  -0.0114365:0.0265674:0.173925:0.005106:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005076 ES:SE:LP:AF:ID  -0.00961121:0.0266263:0.142668:0.005076:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.836845 ES:SE:LP:AF:ID  0.00651616:0.00479012:0.769551:0.836845:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038173 ES:SE:LP:AF:ID  -0.00196732:0.00925275:0.0809219:0.038173:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.837479 ES:SE:LP:AF:ID  0.00649397:0.00480344:0.744727:0.837479:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013263 ES:SE:LP:AF:ID  6.63857e-05:0.0171811:-0:0.013263:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005456 ES:SE:LP:AF:ID  0.0133767:0.0261106:0.21467:0.005456:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838709 ES:SE:LP:AF:ID  0.0071703:0.00486927:0.853872:0.838709:rs3131965